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Sample records for fuzzy integrated methodology

  1. Application of integrated fuzzy VIKOR & AHP methodology to contractor ranking

    Directory of Open Access Journals (Sweden)

    Mohamad Rahim Ramezaniyan

    2012-08-01

    Full Text Available Contractor selection is a critical activity, which plays an important role in the overall success of any construction project. The implementation of fuzzy multiple criteria decision attribute (MCDA in selecting contractors has the advantage of rendering subjective and implicit decision making more objective and transparent. An additional merit of fuzzy MCDA is the ability to accommodate quantitative and qualitative information. In this paper, an integrated VIKOR–AHP methodology is proposed to make a selection among the alternative contractors in one of Iranian construction industry projects. In the proposed methodology, the weights of the selection criteria are determined by fuzzy pairwise comparison matrices of AHP.

  2. An Innovative Fuzzy-Logic-Based Methodology for Trend Identification

    International Nuclear Information System (INIS)

    Wang Xin; Tsoukalas, Lefteri H.; Wei, Thomas Y.C.; Reifman, Jaques

    2001-01-01

    A new fuzzy-logic-based methodology for on-line signal trend identification is introduced. The methodology may be used for detecting the onset of nuclear power plant (NPP) transients at the earliest possible time and could be of great benefit to diagnostic, maintenance, and performance-monitoring programs. Although signal trend identification is complicated by the presence of noise, fuzzy methods can help capture important features of on-line signals, integrate the information included in these features, and classify incoming NPP signals into increasing, decreasing, and steady-state trend categories. A computer program named PROTREN is developed and tested for the purpose of verifying this methodology using NPP and simulation data. The results indicate that the new fuzzy-logic-based methodology is capable of detecting transients accurately, it identifies trends reliably and does not misinterpret a steady-state signal as a transient one

  3. Multicriteria renewable energy planning using an integrated fuzzy VIKOR and AHP methodology: The case of Istanbul

    International Nuclear Information System (INIS)

    Kaya, Tolga; Kahraman, Cengiz

    2010-01-01

    The purpose of this study is twofold: first, it is aimed at determining the best renewable energy alternative for Istanbul by using an integrated VIKOR-AHP methodology. Second, a selection among alternative energy production sites in this city is made using the same approach. In the proposed VIKOR-AHP methodology, the weights of the selection criteria are determined by pairwise comparison matrices of AHP. In energy decision making problems, the judgments of decision makers are usually vague. As it is relatively difficult for decision makers to provide exact values for the criteria, the evaluation data for the alternative energy policies should be expressed in linguistic terms. In order to model this kind of uncertainty in human preferences, fuzzy logic is applied very successfully. Thus, both classical VIKOR and classical AHP procedures are performed under fuzzy environment. The originality of the paper comes from the application of the proposed integrated VIKOR-AHP methodology to the selection of the best energy policy and production site. It is found that wind energy is the most appropriate renewable energy option and Catalca district is the best area among the alternatives for establishing wind turbines in Istanbul.

  4. Multi-attribute Evaluation of Website Quality in E-business Using an Integrated Fuzzy AHPTOPSIS Methodology

    Directory of Open Access Journals (Sweden)

    Tolga Kaya

    2010-09-01

    Full Text Available Success of an e-business company is strongly associated with the relative quality of its website compared to that of its competitors. The purpose of this study is to propose a multi-attribute e-business website quality evaluation methodology based on a modified fuzzy TOPSIS approach. In the proposed methodology, weights of the evaluation criteria are generated by a fuzzy AHP procedure. In performance evaluation problems, the judgments of the experts may usually be vague in form. As fuzzy logic can successfully deal with this kind of uncertainty in human preferences, both classical TOPSIS and classical AHP procedures are implemented under fuzzy environment. The proposed TOPSIS-AHP methodology has successfully been applied to a multi-attribute website quality evaluation problem in Turkish e-business market. Nine sub-criteria under four main categories are used in the evaluation of the most popular e-business websites of Turkey. A sensitivity analysis is also provided.

  5. Fuzzy Itand#244; Integral Driven by a Fuzzy Brownian Motion

    Directory of Open Access Journals (Sweden)

    Didier Kumwimba Seya

    2015-11-01

    Full Text Available In this paper we take into account the fuzzy stochastic integral driven by fuzzy Brownian motion. To define the metric between two fuzzy numbers and to take into account the limit of a sequence of fuzzy numbers, we invoke the Hausdorff metric. First this fuzzy stochastic integral is constructed for fuzzy simple stochastic functions, then the construction is done for fuzzy stochastic integrable functions.

  6. Fuzzy measures and integrals

    Czech Academy of Sciences Publication Activity Database

    Mesiar, Radko

    2005-01-01

    Roč. 28, č. 156 (2005), s. 365-370 ISSN 0165-0114 R&D Projects: GA ČR(CZ) GA402/04/1026 Institutional research plan: CEZ:AV0Z10750506 Keywords : fuzzy measures * fuzzy integral * regular fuzzy integral Subject RIV: BA - General Mathematics Impact factor: 1.039, year: 2005

  7. Neuro-fuzzy Control of Integrating Processes

    Directory of Open Access Journals (Sweden)

    Anna Vasičkaninová

    2011-11-01

    Full Text Available Fuzzy technology is adaptive and easily applicable in different areas.Fuzzy logic provides powerful tools to capture the perceptionof natural phenomena. The paper deals with tuning of neuro-fuzzy controllers for integrating plant and for integrating plantswith time delay. The designed approach is verified on three examples by simulations and compared plants with classical PID control.Designed fuzzy controllers lead to better closed-loop control responses then classical PID controllers.

  8. Choquet Integral of Fuzzy-Number-Valued Functions: The Differentiability of the Primitive with respect to Fuzzy Measures and Choquet Integral Equations

    Directory of Open Access Journals (Sweden)

    Zengtai Gong

    2014-01-01

    Full Text Available This paper deals with the Choquet integral of fuzzy-number-valued functions based on the nonnegative real line. We firstly give the definitions and the characterizations of the Choquet integrals of interval-valued functions and fuzzy-number-valued functions based on the nonadditive measure. Furthermore, the operational schemes of above several classes of integrals on a discrete set are investigated which enable us to calculate Choquet integrals in some applications. Secondly, we give a representation of the Choquet integral of a nonnegative, continuous, and increasing fuzzy-number-valued function with respect to a fuzzy measure. In addition, in order to solve Choquet integral equations of fuzzy-number-valued functions, a concept of the Laplace transformation for the fuzzy-number-valued functions in the sense of Choquet integral is introduced. For distorted Lebesgue measures, it is shown that Choquet integral equations of fuzzy-number-valued functions can be solved by the Laplace transformation. Finally, an example is given to illustrate the main results at the end of the paper.

  9. Soft computing integrating evolutionary, neural, and fuzzy systems

    CERN Document Server

    Tettamanzi, Andrea

    2001-01-01

    Soft computing encompasses various computational methodologies, which, unlike conventional algorithms, are tolerant of imprecision, uncertainty, and partial truth. Soft computing technologies offer adaptability as a characteristic feature and thus permit the tracking of a problem through a changing environment. Besides some recent developments in areas like rough sets and probabilistic networks, fuzzy logic, evolutionary algorithms, and artificial neural networks are core ingredients of soft computing, which are all bio-inspired and can easily be combined synergetically. This book presents a well-balanced integration of fuzzy logic, evolutionary computing, and neural information processing. The three constituents are introduced to the reader systematically and brought together in differentiated combinations step by step. The text was developed from courses given by the authors and offers numerous illustrations as

  10. An extensible six-step methodology to automatically generate fuzzy DSSs for diagnostic applications.

    Science.gov (United States)

    d'Acierno, Antonio; Esposito, Massimo; De Pietro, Giuseppe

    2013-01-01

    The diagnosis of many diseases can be often formulated as a decision problem; uncertainty affects these problems so that many computerized Diagnostic Decision Support Systems (in the following, DDSSs) have been developed to aid the physician in interpreting clinical data and thus to improve the quality of the whole process. Fuzzy logic, a well established attempt at the formalization and mechanization of human capabilities in reasoning and deciding with noisy information, can be profitably used. Recently, we informally proposed a general methodology to automatically build DDSSs on the top of fuzzy knowledge extracted from data. We carefully refine and formalize our methodology that includes six stages, where the first three stages work with crisp rules, whereas the last three ones are employed on fuzzy models. Its strength relies on its generality and modularity since it supports the integration of alternative techniques in each of its stages. The methodology is designed and implemented in the form of a modular and portable software architecture according to a component-based approach. The architecture is deeply described and a summary inspection of the main components in terms of UML diagrams is outlined as well. A first implementation of the architecture has been then realized in Java following the object-oriented paradigm and used to instantiate a DDSS example aimed at accurately diagnosing breast masses as a proof of concept. The results prove the feasibility of the whole methodology implemented in terms of the architecture proposed.

  11. Reliability modelling of repairable systems using Petri nets and fuzzy Lambda-Tau methodology

    International Nuclear Information System (INIS)

    Knezevic, J.; Odoom, E.R.

    2001-01-01

    A methodology is developed which uses Petri nets instead of the fault tree methodology and solves for reliability indices utilising fuzzy Lambda-Tau method. Fuzzy set theory is used for representing the failure rate and repair time instead of the classical (crisp) set theory because fuzzy numbers allow expert opinions, linguistic variables, operating conditions, uncertainty and imprecision in reliability information to be incorporated into the system model. Petri nets are used because unlike the fault tree methodology, the use of Petri nets allows efficient simultaneous generation of minimal cut and path sets

  12. Optimal solution of full fuzzy transportation problems using total integral ranking

    Science.gov (United States)

    Sam’an, M.; Farikhin; Hariyanto, S.; Surarso, B.

    2018-03-01

    Full fuzzy transportation problem (FFTP) is a transportation problem where transport costs, demand, supply and decision variables are expressed in form of fuzzy numbers. To solve fuzzy transportation problem, fuzzy number parameter must be converted to a crisp number called defuzzyfication method. In this new total integral ranking method with fuzzy numbers from conversion of trapezoidal fuzzy numbers to hexagonal fuzzy numbers obtained result of consistency defuzzyfication on symmetrical fuzzy hexagonal and non symmetrical type 2 numbers with fuzzy triangular numbers. To calculate of optimum solution FTP used fuzzy transportation algorithm with least cost method. From this optimum solution, it is found that use of fuzzy number form total integral ranking with index of optimism gives different optimum value. In addition, total integral ranking value using hexagonal fuzzy numbers has an optimal value better than the total integral ranking value using trapezoidal fuzzy numbers.

  13. A Combined Fuzzy-AHP and Fuzzy-GRA Methodology for Hydrogen Energy Storage Method Selection in Turkey

    Directory of Open Access Journals (Sweden)

    Aytac Yildiz

    2013-06-01

    Full Text Available In this paper, we aim to select the most appropriate Hydrogen Energy Storage (HES method for Turkey from among the alternatives of tank, metal hydride and chemical storage, which are determined based on expert opinions and literature review. Thus, we propose a Buckley extension based fuzzy Analytical Hierarchical Process (Fuzzy-AHP and linear normalization based fuzzy Grey Relational Analysis (Fuzzy-GRA combined Multi Criteria Decision Making (MCDM methodology. This combined approach can be applied to a complex decision process, which often makes sense with subjective data or vague information; and used to solve to solve HES selection problem with different defuzzification methods. The proposed approach is unique both in the HES literature and the MCDM literature.

  14. An experimental methodology for a fuzzy set preference model

    Science.gov (United States)

    Turksen, I. B.; Willson, Ian A.

    1992-01-01

    A flexible fuzzy set preference model first requires approximate methodologies for implementation. Fuzzy sets must be defined for each individual consumer using computer software, requiring a minimum of time and expertise on the part of the consumer. The amount of information needed in defining sets must also be established. The model itself must adapt fully to the subject's choice of attributes (vague or precise), attribute levels, and importance weights. The resulting individual-level model should be fully adapted to each consumer. The methodologies needed to develop this model will be equally useful in a new generation of intelligent systems which interact with ordinary consumers, controlling electronic devices through fuzzy expert systems or making recommendations based on a variety of inputs. The power of personal computers and their acceptance by consumers has yet to be fully utilized to create interactive knowledge systems that fully adapt their function to the user. Understanding individual consumer preferences is critical to the design of new products and the estimation of demand (market share) for existing products, which in turn is an input to management systems concerned with production and distribution. The question of what to make, for whom to make it and how much to make requires an understanding of the customer's preferences and the trade-offs that exist between alternatives. Conjoint analysis is a widely used methodology which de-composes an overall preference for an object into a combination of preferences for its constituent parts (attributes such as taste and price), which are combined using an appropriate combination function. Preferences are often expressed using linguistic terms which cannot be represented in conjoint models. Current models are also not implemented an individual level, making it difficult to reach meaningful conclusions about the cause of an individual's behavior from an aggregate model. The combination of complex aggregate

  15. Resource integrated planning through fuzzy techniques

    Energy Technology Data Exchange (ETDEWEB)

    Haddad, J; Torres, G Lambert [Escola Federal de Engenharia de Itajuba, MG (Brazil); Jannuzzi, G de M. [Universidade Estadual de Campinas, SP (Brazil). Faculdade de Engenharia Mecanica

    1994-12-31

    A methodology for decision-making in studies involving energy saving by using the Fuzzy Sets Theory is presented. The Fuzzy Sets Theory permits to handle and to operate exact and non-exact propositions, that is, to incorporate both numerical data (exact) and the knowledge of either the expert or the analyst (inexact). The basic concepts of this theory are presented with its main operations and properties. Following, some criteria and technical-economical parameters used in the planning of the generation expansion are shown and, finally, the Theory of the Fuzzy Sets is applied aiming to establish electrical power generation and conservation strategies considering the power demand. (author) 6 refs., 8 tabs.

  16. Bounded solutions for fuzzy differential and integral equations

    Energy Technology Data Exchange (ETDEWEB)

    Nieto, Juan J. [Departamento de Analisis Matematico Facultad de Matematicas Universidad de Santiago de Compostela, 15782 (Spain)] e-mail: amnieto@usc.es; Rodriguez-Lopez, Rosana [Departamento de Analisis Matematico Facultad de Matematicas Universidad de Santiago de Compostela, 15782 (Spain)] e-mail: amrosana@usc.es

    2006-03-01

    We find sufficient conditions for the boundness of every solution of first-order fuzzy differential equations as well as certain fuzzy integral equations. Our results are based on several theorems concerning crisp differential and integral inequalities.

  17. Inclusive integral evaluation for mammograms using the hierarchical fuzzy integral (HFI) model

    International Nuclear Information System (INIS)

    Amano, Takashi; Yamashita, Kazuya; Arao, Shinichi; Kitayama, Akira; Hayashi, Akiko; Suemori, Shinji; Ohkura, Yasuhiko

    2000-01-01

    Physical factors (physically evaluated values) and psychological factors (fuzzy measurements) of breast x-ray images were comprehensively evaluated by applying breast x-ray images to an extended stratum-type fuzzy integrating model. In addition, x-ray images were evaluated collectively by integrating the quality (sharpness, graininess, and contrast) of x-ray images and three representative shadows (fibrosis, calcification, tumor) in the breast x-ray images. We selected the most appropriate system for radiography of the breast from three kinds of intensifying screens and film systems for evaluation by this method and investigated the relationship between the breast x-ray images and noise equivalent quantum number, which is called the overall physical evaluation method, and between the breast x-ray images and psychological evaluation by a visual system with a stratum-type fuzzy integrating model. We obtained a linear relationship between the breast x-ray image and noise-equivalent quantum number, and linearity between the breast x-ray image and psychological evaluation by the visual system. Therefore, the determination of fuzzy measurement, which is a scale for fuzzy evaluation of psychological factors of the observer, and physically evaluated values with a stratum-type fuzzy integrating model enabled us to make a comprehensive evaluation of x-ray images that included both psychological and physical aspects. (author)

  18. An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation.

    Directory of Open Access Journals (Sweden)

    Huu-Tho Nguyen

    Full Text Available Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process and a fuzzy COmplex PRoportional ASsessment (COPRAS for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment.

  19. Integrated development environment for fuzzy logic applications

    Science.gov (United States)

    Pagni, Andrea; Poluzzi, Rinaldo; Rizzotto, GianGuido; Lo Presti, Matteo

    1993-12-01

    During the last five years, Fuzzy Logic has gained enormous popularity, both in the academic and industrial worlds, breaking up the traditional resistance against changes thanks to its innovative approach to problems formalization. The success of this new methodology is pushing the creation of a brand new class of devices, called Fuzzy Machines, to overcome the limitations of traditional computing systems when acting as Fuzzy Systems and adequate Software Tools to efficiently develop new applications. This paper aims to present a complete development environment for the definition of fuzzy logic based applications. The environment is also coupled with a sophisticated software tool for semiautomatic synthesis and optimization of the rules with stability verifications. Later it is presented the architecture of WARP, a dedicate VLSI programmable chip allowing to compute in real time a fuzzy control process. The article is completed with two application examples, which have been carried out exploiting the aforementioned tools and devices.

  20. Integration of neural networks with fuzzy reasoning for measuring operational parameters in a nuclear reactor

    International Nuclear Information System (INIS)

    Ikonomopoulos, A.; Tsoukalas, L.H.

    1993-01-01

    A novel approach is described for measuring variables with operational significance in a complex system such as a nuclear reactor. The methodology is based on the integration of artificial neural networks with fuzzy reasoning. Neural networks are used to map dynamic time series to a set of user-defined linguistic labels called fuzzy values. The process takes place in a manner analogous to that of measurement. Hence, the entire procedure is referred to as virtual measurement and its software implementation as a virtual measuring device. An optimization algorithm based on information criteria and fuzzy algebra augments the process and assists in the identification of different states of the monitored parameter. The proposed technique is applied for monitoring parameters such as performance, valve position, transient type, and reactivity. The results obtained from the application of the neural network-fuzzy reasoning integration in a high power research reactor clearly demonstrate the excellent tolerance of the virtual measuring device to faulty signals as well as its ability to accommodate noisy inputs

  1. An Intuitionistic Fuzzy Methodology for Component-Based Software Reliability Optimization

    DEFF Research Database (Denmark)

    Madsen, Henrik; Grigore, Albeanu; Popenţiuvlǎdicescu, Florin

    2012-01-01

    Component-based software development is the current methodology facilitating agility in project management, software reuse in design and implementation, promoting quality and productivity, and increasing the reliability and performability. This paper illustrates the usage of intuitionistic fuzzy...... degree approach in modelling the quality of entities in imprecise software reliability computing in order to optimize management results. Intuitionistic fuzzy optimization algorithms are proposed to be used for complex software systems reliability optimization under various constraints....

  2. Renewable energy integration in smart grids-multicriteria assessment using the fuzzy analytical hierarchy process

    OpenAIRE

    JANJIC, ALEKSANDAR; SAVIC, SUZANA; VELIMIROVIC, LAZAR; NIKOLIC, VESNA

    2015-01-01

    Unlike the traditional way of efficiency assessment of renewable energy sources integration, the smart grid concept is introducing new goals and objectives regarding increased use of renewable electricity sources, grid security, energy conservation, energy efficiency, and deregulated energy market. Possible benefits brought by renewable sources integration are evaluated by the degree of the approach to the ideal smart grid. In this paper, fuzzy analytical hierarchy process methodology for the...

  3. Mapa digital de solos: uma proposta metodológica usando inferência fuzzy Digital soil map: a methodological proposal using fuzzy inference

    Directory of Open Access Journals (Sweden)

    Claudia C. Nolasco-Carvalho

    2009-02-01

    Full Text Available Elaborou-se um mapa digital de solos de uma área na região de Mucugê, BA, com o objetivo de avaliar o uso de geotecnologias na cartografia de solos. A metodologia desenvolvida a partir do modelo de inferência para solos - SoLIM , requer o conhecimento prévio da área por um especialista em mapeamento e está alicerçada na equação dos fatores de formação do solo e no modelo de distribuição dos solos na paisagem. Os dados, advindos do Modelo Digital do Terreno - MDT, da vegetação e da geologia, foram associados ao conhecimento do pedólogo e integrados em ambiente SIG (Sistema de Informações Geográficas sob inferência fuzzy. A modelagem por lógica fuzzy permitiu apontar as incertezas e transições da cobertura pedológica e gerou um mapa digital de solo que, quando comparado com o mapa convencional da área, mostrou menor generalização no domínio de espaços e parâmetros, ou seja, um refinamento da escala, porém a aplicabilidade da metodologia depende da validação de campo e da repetição em outras áreas.A digital soil map was elaborated for an area in the region of Mucugê-BA using data integration derived from a digital elevation model (DEM of the vegetation and geology that was associated with a soil scientist's knowledge and correlated in a GIS environment (Geography Information System under fuzzy inference, as a methodological proposal. The methodology was developed and based on the soil-land inference model - SoLIM, on the soil factor equation and the soil-landscape model. The fuzzy logic is able to simulate the uncertainty and transitions that often appear in pedologic systems. The results show that the methodology allows the generation of digital soil maps with increased scale and to reduce soil classe generalizations in the space and parameter domain. However, this methodology is very dependent upon the soil expert's knowledge and accuracy of the data base. To verify the applicability of the methodology the

  4. On the Power of Fuzzy Markup Language

    CERN Document Server

    Loia, Vincenzo; Lee, Chang-Shing; Wang, Mei-Hui

    2013-01-01

    One of the most successful methodology that arose from the worldwide diffusion of Fuzzy Logic is Fuzzy Control. After the first attempts dated in the seventies, this methodology has been widely exploited for controlling many industrial components and systems. At the same time, and very independently from Fuzzy Logic or Fuzzy Control, the birth of the Web has impacted upon almost all aspects of computing discipline. Evolution of Web, Web 2.0 and Web 3.0 has been making scenarios of ubiquitous computing much more feasible;  consequently information technology has been thoroughly integrated into everyday objects and activities. What happens when Fuzzy Logic meets Web technology? Interesting results might come out, as you will discover in this book. Fuzzy Mark-up Language is a son of this synergistic view, where some technological issues of Web are re-interpreted taking into account the transparent notion of Fuzzy Control, as discussed here.  The concept of a Fuzzy Control that is conceived and modeled in terms...

  5. Efficient explicit formulation for practical fuzzy structural analysis

    Indian Academy of Sciences (India)

    This paper presents a practical approach based on High Dimensional Model Representation (HDMR) for analysing the response of structures with fuzzy parameters. The proposed methodology involves integrated finite element modelling, HDMR based response surface generation, and explicit fuzzy analysis procedures.

  6. Numerical method for solving linear Fredholm fuzzy integral equations of the second kind

    Energy Technology Data Exchange (ETDEWEB)

    Abbasbandy, S. [Department of Mathematics, Imam Khomeini International University, P.O. Box 288, Ghazvin 34194 (Iran, Islamic Republic of)]. E-mail: saeid@abbasbandy.com; Babolian, E. [Faculty of Mathematical Sciences and Computer Engineering, Teacher Training University, Tehran 15618 (Iran, Islamic Republic of); Alavi, M. [Department of Mathematics, Arak Branch, Islamic Azad University, Arak 38135 (Iran, Islamic Republic of)

    2007-01-15

    In this paper we use parametric form of fuzzy number and convert a linear fuzzy Fredholm integral equation to two linear system of integral equation of the second kind in crisp case. We can use one of the numerical method such as Nystrom and find the approximation solution of the system and hence obtain an approximation for fuzzy solution of the linear fuzzy Fredholm integral equations of the second kind. The proposed method is illustrated by solving some numerical examples.

  7. The fuzzy TOPSIS and generalized Choquet fuzzy integral algorithm for nuclear power plant site selection - a case study from Turkey

    International Nuclear Information System (INIS)

    Kurt, Ünal

    2014-01-01

    The location selection for nuclear power plant (NPP) is a strategic decision, which has significant impact on the economic operation of the plant and sustainable development of the region. This paper proposes fuzzy TOPSIS and generalized Choquet fuzzy integral algorithm for evaluation and selection of optimal locations for NPP in Turkey. Many sub-criteria such as geological, social, touristic, transportation abilities, cooling water capacity and nearest to consumptions markets are taken into account. Among the evaluated locations, according to generalized Choquet fuzzy integral method, Inceburun–Sinop was selected as a study site due to its highest performance and meeting most of the investigated criteria. The Inceburun-Sinop is selected by generalized Choquet fuzzy integral and fuzzy TOPSIS Iğneada–Kırklareli took place in the first turn. The Mersin–Akkuyu is not selected in both methods. (author)

  8. A risk assessment methodology for incorporating uncertainties using fuzzy concepts

    International Nuclear Information System (INIS)

    Cho, Hyo-Nam; Choi, Hyun-Ho; Kim, Yoon-Bae

    2002-01-01

    This paper proposes a new methodology for incorporating uncertainties using fuzzy concepts into conventional risk assessment frameworks. This paper also introduces new forms of fuzzy membership curves, designed to consider the uncertainty range that represents the degree of uncertainties involved in both probabilistic parameter estimates and subjective judgments, since it is often difficult or even impossible to precisely estimate the occurrence rate of an event in terms of one single crisp probability. It is to be noted that simple linguistic variables such as 'High/Low' and 'Good/Bad' have the limitations in quantifying the various risks inherent in construction projects, but only represent subjective mental cognition adequately. Therefore, in this paper, the statements that include some quantification with giving specific value or scale, such as 'Close to any value' or 'Higher/Lower than analyzed value', are used in order to get over the limitations. It may be stated that the proposed methodology will be very useful for the systematic and rational risk assessment of construction projects

  9. Fuzzy knowledge bases integration based on ontology

    OpenAIRE

    Ternovoy, Maksym; Shtogrina, Olena

    2012-01-01

    the paper describes the approach for fuzzy knowledge bases integration with the usage of ontology. This approach is based on metadata-base usage for integration of different knowledge bases with common ontology. The design process of metadata-base is described.

  10. A new methodological development for solving linear bilevel integer programming problems in hybrid fuzzy environment

    Directory of Open Access Journals (Sweden)

    Animesh Biswas

    2016-04-01

    Full Text Available This paper deals with fuzzy goal programming approach to solve fuzzy linear bilevel integer programming problems with fuzzy probabilistic constraints following Pareto distribution and Frechet distribution. In the proposed approach a new chance constrained programming methodology is developed from the view point of managing those probabilistic constraints in a hybrid fuzzy environment. A method of defuzzification of fuzzy numbers using ?-cut has been adopted to reduce the problem into a linear bilevel integer programming problem. The individual optimal value of the objective of each DM is found in isolation to construct the fuzzy membership goals. Finally, fuzzy goal programming approach is used to achieve maximum degree of each of the membership goals by minimizing under deviational variables in the decision making environment. To demonstrate the efficiency of the proposed approach, a numerical example is provided.

  11. Speed control for a two-mass drive system using integrated fuzzy estimator and hybrid fuzzy PD/PI controller

    International Nuclear Information System (INIS)

    Pai, N-S; Kuo, Y-P

    2008-01-01

    This paper presents a novel speed control scheme for a 2- mass motor drive system. The speed controller is based on the estimated state feedback compensation. The integrated fuzzy observer can give a fast and accuracy estimation of the unmeasured states. Two kinds of hybrid fuzzy proportional-derivative and proportional-integral (HF PD/PI) are proposed to cope with this speed control problem. The first is the static HF PD/PI controller and the second is the dynamic one. Simulation results show that the developed integrated fuzzy observer provide the better estimation performance than that of the Kalman filter and the proposed control schemes can effectively track the desired speed in the presence of load disturbance

  12. Multi-response optimization of surface integrity characteristics of EDM process using grey-fuzzy logic-based hybrid approach

    Directory of Open Access Journals (Sweden)

    Shailesh Dewangan

    2015-09-01

    Full Text Available Surface integrity remains one of the major areas of concern in electric discharge machining (EDM. During the current study, grey-fuzzy logic-based hybrid optimization technique is utilized to determine the optimal settings of EDM process parameters with an aim to improve surface integrity aspects after EDM of AISI P20 tool steel. The experiment is designed using response surface methodology (RSM considering discharge current (Ip, pulse-on time (Ton, tool-work time (Tw and tool-lift time (Tup as process parameters. Various surface integrity characteristics such as white layer thickness (WLT, surface crack density (SCD and surface roughness (SR are considered during the current research work. Grey relational analysis (GRA combined with fuzzy-logic is used to determine grey fuzzy reasoning grade (GFRG. The optimal solution based on this analysis is found to be Ip = 1 A, Ton = 10 μs, Tw = 0.2 s, and Tup = 0.0 s. Analysis of variance (ANOVA results clearly indicate that Ton is the most contributing parameter followed by Ip, for multiple performance characteristics of surface integrity.

  13. Aumann Fuzzy Improper Integral and Its Application to Solve Fuzzy Integro-Differential Equations by Laplace Transform Method

    Directory of Open Access Journals (Sweden)

    Elhassan Eljaoui

    2018-01-01

    Full Text Available We introduce the Aumann fuzzy improper integral to define the convolution product of a fuzzy mapping and a crisp function in this paper. The Laplace convolution formula is proved in this case and used to solve fuzzy integro-differential equations with kernel of convolution type. Then, we report and correct an error in the article by Salahshour et al. dealing with the same topic.

  14. THERP and HEART integrated methodology for human error assessment

    Science.gov (United States)

    Castiglia, Francesco; Giardina, Mariarosa; Tomarchio, Elio

    2015-11-01

    THERP and HEART integrated methodology is proposed to investigate accident scenarios that involve operator errors during high-dose-rate (HDR) treatments. The new approach has been modified on the basis of fuzzy set concept with the aim of prioritizing an exhaustive list of erroneous tasks that can lead to patient radiological overexposures. The results allow for the identification of human errors that are necessary to achieve a better understanding of health hazards in the radiotherapy treatment process, so that it can be properly monitored and appropriately managed.

  15. Fuzzy image processing and applications with Matlab

    CERN Document Server

    Chaira, Tamalika

    2009-01-01

    In contrast to classical image analysis methods that employ ""crisp"" mathematics, fuzzy set techniques provide an elegant foundation and a set of rich methodologies for diverse image-processing tasks. However, a solid understanding of fuzzy processing requires a firm grasp of essential principles and background knowledge.Fuzzy Image Processing and Applications with MATLAB® presents the integral science and essential mathematics behind this exciting and dynamic branch of image processing, which is becoming increasingly important to applications in areas such as remote sensing, medical imaging,

  16. Methodology of analysis sustainable development of Ukraine by using the theory fuzzy logic

    Directory of Open Access Journals (Sweden)

    Methodology of analysis sustainable development of Ukraine by using the theory fuzzy logic

    2016-02-01

    Full Text Available Article objective is analysis of the theoretical and methodological aspects for the assessment of sustainable development in times of crisis. The methodical approach to the analysis of sustainable development territory taking into account the assessment of the level of economic security has been proposed. A necessity of development of the complex methodical approach to the accounting of the indeterminacy properties and multicriterial in the tasks to provide economic safety on the basis of using the fuzzy logic theory (or the fuzzy sets theory was proved. The results of using the method of fuzzy sets of during the 2002-2012 years the dynamics of changes dynamics of sustainable development in Ukraine were presented.

  17. Two Stage Fuzzy Methodology to Evaluate the Credit Risks of Investment Projects

    OpenAIRE

    O. Badagadze; G. Sirbiladze; I. Khutsishvili

    2014-01-01

    The work proposes a decision support methodology for the credit risk minimization in selection of investment projects. The methodology provides two stages of projects’ evaluation. Preliminary selection of projects with minor credit risks is made using the Expertons Method. The second stage makes ranking of chosen projects using the Possibilistic Discrimination Analysis Method. The latter is a new modification of a well-known Method of Fuzzy Discrimination Analysis.

  18. Fuzzy Clustering based Methodology for Multidimensional Data Analysis in Computational Forensic Domain

    OpenAIRE

    Kilian Stoffel; Paul Cotofrei; Dong Han

    2012-01-01

    As interdisciplinary domain requiring advanced and innovative methodologies the computational forensics domain is characterized by data being simultaneously large scaled and uncertain multidimensional and approximate. Forensic domain experts trained to discover hidden pattern from crime data are limited in their analysis without the assistance of a computational intelligence approach. In this paper a methodology and an automatic procedure based on fuzzy set theory and designed to infer precis...

  19. Human error probability quantification using fuzzy methodology in nuclear plants

    International Nuclear Information System (INIS)

    Nascimento, Claudio Souza do

    2010-01-01

    This work obtains Human Error Probability (HEP) estimates from operator's actions in response to emergency situations a hypothesis on Research Reactor IEA-R1 from IPEN. It was also obtained a Performance Shaping Factors (PSF) evaluation in order to classify them according to their influence level onto the operator's actions and to determine these PSF actual states over the plant. Both HEP estimation and PSF evaluation were done based on Specialists Evaluation using interviews and questionnaires. Specialists group was composed from selected IEA-R1 operators. Specialist's knowledge representation into linguistic variables and group evaluation values were obtained through Fuzzy Logic and Fuzzy Set Theory. HEP obtained values show good agreement with literature published data corroborating the proposed methodology as a good alternative to be used on Human Reliability Analysis (HRA). (author)

  20. A novel methodology improves reservoir characterization models using geologic fuzzy variables

    Energy Technology Data Exchange (ETDEWEB)

    Soto B, Rodolfo [DIGITOIL, Maracaibo (Venezuela); Soto O, David A. [Texas A and M University, College Station, TX (United States)

    2004-07-01

    One of the research projects carried out in Cusiana field to explain its rapid decline during the last years was to get better permeability models. The reservoir of this field has a complex layered system that it is not easy to model using conventional methods. The new technique included the development of porosity and permeability maps from cored wells following the same trend of the sand depositions for each facie or layer according to the sedimentary facie and the depositional system models. Then, we used fuzzy logic to reproduce those maps in three dimensions as geologic fuzzy variables. After multivariate statistical and factor analyses, we found independence and a good correlation coefficient between the geologic fuzzy variables and core permeability and porosity. This means, the geologic fuzzy variable could explain the fabric, the grain size and the pore geometry of the reservoir rock trough the field. Finally, we developed a neural network permeability model using porosity, gamma ray and the geologic fuzzy variable as input variables. This model has a cross-correlation coefficient of 0.873 and average absolute error of 33% compared with the actual model with a correlation coefficient of 0.511 and absolute error greater than 250%. We tested different methodologies, but this new one showed dramatically be a promiser way to get better permeability models. The use of the models have had a high impact in the explanation of well performance and workovers, and reservoir simulation models. (author)

  1. A fuzzy inventory model with acceptable shortage using graded mean integration value method

    Science.gov (United States)

    Saranya, R.; Varadarajan, R.

    2018-04-01

    In many inventory models uncertainty is due to fuzziness and fuzziness is the closed possible approach to reality. In this paper, we proposed a fuzzy inventory model with acceptable shortage which is completely backlogged. We fuzzily the carrying cost, backorder cost and ordering cost using Triangular and Trapezoidal fuzzy numbers to obtain the fuzzy total cost. The purpose of our study is to defuzzify the total profit function by Graded Mean Integration Value Method. Further a numerical example is also given to demonstrate the developed crisp and fuzzy models.

  2. Composite Gauss-Legendre Formulas for Solving Fuzzy Integration

    Directory of Open Access Journals (Sweden)

    Xiaobin Guo

    2014-01-01

    Full Text Available Two numerical integration rules based on composition of Gauss-Legendre formulas for solving integration of fuzzy numbers-valued functions are investigated in this paper. The methods' constructions are presented and the corresponding convergence theorems are shown in detail. Two numerical examples are given to illustrate the proposed algorithms finally.

  3. Adaptive Fuzzy Integral Sliding-Mode Regulator for Induction Motor Using Nonlinear Sliding Surface

    OpenAIRE

    Yong-Kun Lu

    2015-01-01

    An adaptive fuzzy integral sliding-mode controller using nonlinear sliding surface is designed for the speed regulator of a field-oriented induction motor drive in this paper. Combining the conventional integral sliding surface with fractional-order integral, a nonlinear sliding surface is proposed for the integral sliding-mode speed control, which can overcome the windup problem and the convergence speed problem. An adaptive fuzzy control term is utilized to approximate the uncertainty. The ...

  4. Fuzzy-TLX: using fuzzy integrals for evaluating human mental workload with NASA-Task Load indeX in laboratory and field studies.

    Science.gov (United States)

    Mouzé-Amady, Marc; Raufaste, Eric; Prade, Henri; Meyer, Jean-Pierre

    2013-01-01

    The aim of this study was to assess mental workload in which various load sources must be integrated to derive reliable workload estimates. We report a new algorithm for computing weights from qualitative fuzzy integrals and apply it to the National Aeronautics and Space Administration -Task Load indeX (NASA-TLX) subscales in order to replace the standard pair-wise weighting technique (PWT). In this paper, two empirical studies were reported: (1) In a laboratory experiment, age- and task-related variables were investigated in 53 male volunteers and (2) In a field study, task- and job-related variables were studied on aircrews during 48 commercial flights. The results found in this study were as follows: (i) in the experimental setting, fuzzy estimates were highly correlated with classical (using PWT) estimates; (ii) in real work conditions, replacing PWT by automated fuzzy treatments simplified the NASA-TLX completion; (iii) the algorithm for computing fuzzy estimates provides a new classification procedure sensitive to various variables of work environments and (iv) subjective and objective measures can be used for the fuzzy aggregation of NASA-TLX subscales. NASA-TLX, a classical tool for mental workload assessment, is based on a weighted sum of ratings from six subscales. A new algorithm, which impacts on input data collection and computes weights and indexes from qualitative fuzzy integrals, is evaluated through laboratory and field studies. Pros and cons are discussed.

  5. A Hybrid Neuro-Fuzzy Model For Integrating Large Earth-Science Datasets

    Science.gov (United States)

    Porwal, A.; Carranza, J.; Hale, M.

    2004-12-01

    A GIS-based hybrid neuro-fuzzy approach to integration of large earth-science datasets for mineral prospectivity mapping is described. It implements a Takagi-Sugeno type fuzzy inference system in the framework of a four-layered feed-forward adaptive neural network. Each unique combination of the datasets is considered a feature vector whose components are derived by knowledge-based ordinal encoding of the constituent datasets. A subset of feature vectors with a known output target vector (i.e., unique conditions known to be associated with either a mineralized or a barren location) is used for the training of an adaptive neuro-fuzzy inference system. Training involves iterative adjustment of parameters of the adaptive neuro-fuzzy inference system using a hybrid learning procedure for mapping each training vector to its output target vector with minimum sum of squared error. The trained adaptive neuro-fuzzy inference system is used to process all feature vectors. The output for each feature vector is a value that indicates the extent to which a feature vector belongs to the mineralized class or the barren class. These values are used to generate a prospectivity map. The procedure is demonstrated by an application to regional-scale base metal prospectivity mapping in a study area located in the Aravalli metallogenic province (western India). A comparison of the hybrid neuro-fuzzy approach with pure knowledge-driven fuzzy and pure data-driven neural network approaches indicates that the former offers a superior method for integrating large earth-science datasets for predictive spatial mathematical modelling.

  6. An integrated multi attribute decision model for energy efficiency processes in petrochemical industry applying fuzzy set theory

    International Nuclear Information System (INIS)

    Taylan, Osman; Kaya, Durmus; Demirbas, Ayhan

    2016-01-01

    Graphical abstract: Evaluation of compressors by comparing the different cost parameters. - Highlights: • Fuzzy sets and systems are used for decision making in MCDM problems. • An integrated Fuzzy AHP and fuzzy TOPSIS approaches are employed for compressor selection. • Compressor selection is a highly complex and non-linear process. • This approach increases the efficiency, reliability of alternative scenarios, and reduces the pay-back period. - Abstract: Energy efficient technologies offered by the market increases productivity. However, decision making for these technologies is usually obstructed in the firms and comes up with organizational barriers. Compressor selection in petrochemical industry requires assessment of several criteria such as ‘reliability, energy consumption, initial investment, capacity, pressure, and maintenance cost.’ Therefore, air compressor selection is a multi-attribute decision making (MADM) problem. The aim of this study is to select the most eligible compressor(s) so as to avoid the high energy consumption due to the capacity and maintenance costs. It is also aimed to avoid failures due to the reliability problems and high pressure. MADM usually takes place in a vague and imprecise environment. Soft computing techniques such as fuzzy sets and system can be used for decision making where vague and imprecise knowledge is available. In this study, an integrated fuzzy analytical hierarchy process (FAHP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS) methodologies are employed for the compressor selection. Fuzzy AHP was used to determine the weights of criteria and fuzzy TOPSIS was employed to order the scenarios according to their superiority. The total effect of all criteria was determined for all alternative scenarios to make an optimal decision. Moreover, the types of compressor, carbon emission, waste heat recovery and their capacities were analyzed and compared by statistical

  7. Logistics Service Provider Selection through an Integrated Fuzzy Multicriteria Decision Making Approach

    OpenAIRE

    Gülşen Akman; Kasım Baynal

    2014-01-01

    Nowadays, the demand of third-party logistics provider becomes an increasingly important issue for companies to improve their customer service and to decrease logistics costs. This paper presents an integrated fuzzy approach for the evaluation and selection of 3rd party logistics service providers. This method consists of two techniques: (1) use fuzzy analytic hierarchy process to identify weights of evaluation criteria; (2) apply fuzzy technique for order preference by similarity to ideal so...

  8. A concurrent optimization model for supplier selection with fuzzy quality loss

    International Nuclear Information System (INIS)

    Rosyidi, C.; Murtisari, R.; Jauhari, W.

    2017-01-01

    The purpose of this research is to develop a concurrent supplier selection model to minimize the purchasing cost and fuzzy quality loss considering process capability and assembled product specification. Design/methodology/approach: This research integrates fuzzy quality loss in the model to concurrently solve the decision making in detailed design stage and manufacturing stage. Findings: The resulted model can be used to concurrently select the optimal supplier and determine the tolerance of the components. The model balances the purchasing cost and fuzzy quality loss. Originality/value: An assembled product consists of many components which must be purchased from the suppliers. Fuzzy quality loss is integrated in the supplier selection model to allow the vagueness in final assembly by grouping the assembly into several grades according to the resulted assembly tolerance.

  9. A concurrent optimization model for supplier selection with fuzzy quality loss

    Energy Technology Data Exchange (ETDEWEB)

    Rosyidi, C.; Murtisari, R.; Jauhari, W.

    2017-07-01

    The purpose of this research is to develop a concurrent supplier selection model to minimize the purchasing cost and fuzzy quality loss considering process capability and assembled product specification. Design/methodology/approach: This research integrates fuzzy quality loss in the model to concurrently solve the decision making in detailed design stage and manufacturing stage. Findings: The resulted model can be used to concurrently select the optimal supplier and determine the tolerance of the components. The model balances the purchasing cost and fuzzy quality loss. Originality/value: An assembled product consists of many components which must be purchased from the suppliers. Fuzzy quality loss is integrated in the supplier selection model to allow the vagueness in final assembly by grouping the assembly into several grades according to the resulted assembly tolerance.

  10. Fuzzy adaptive integration scheme for low-cost SINS/GPS navigation system

    Science.gov (United States)

    Nourmohammadi, Hossein; Keighobadi, Jafar

    2018-01-01

    Due to weak stand-alone accuracy as well as poor run-to-run stability of micro-electro mechanical system (MEMS)-based inertial sensors, special approaches are required to integrate low-cost strap-down inertial navigation system (SINS) with global positioning system (GPS), particularly in long-term applications. This paper aims to enhance long-term performance of conventional SINS/GPS navigation systems using a fuzzy adaptive integration scheme. The main concept behind the proposed adaptive integration is the good performance of attitude-heading reference system (AHRS) in low-accelerated motions and its degradation in maneuvered or accelerated motions. Depending on vehicle maneuvers, gravity-based attitude angles can be intelligently utilized to improve orientation estimation in the SINS. Knowledge-based fuzzy inference system is developed for decision-making between the AHRS and the SINS according to vehicle maneuvering conditions. Inertial measurements are the main input data of the fuzzy system to determine the maneuvering level during the vehicle motions. Accordingly, appropriate weighting coefficients are produced to combine the SINS/GPS and the AHRS, efficiently. The assessment of the proposed integrated navigation system is conducted via real data in airborne tests.

  11. Expected value based fuzzy programming approach to solve integrated supplier selection and inventory control problem with fuzzy demand

    Science.gov (United States)

    Sutrisno; Widowati; Sunarsih; Kartono

    2018-01-01

    In this paper, a mathematical model in quadratic programming with fuzzy parameter is proposed to determine the optimal strategy for integrated inventory control and supplier selection problem with fuzzy demand. To solve the corresponding optimization problem, we use the expected value based fuzzy programming. Numerical examples are performed to evaluate the model. From the results, the optimal amount of each product that have to be purchased from each supplier for each time period and the optimal amount of each product that have to be stored in the inventory for each time period were determined with minimum total cost and the inventory level was sufficiently closed to the reference level.

  12. FUZZY DECISION ANALYSIS FOR INTEGRATED ENVIRONMENTAL VULNERABILITY ASSESSMENT OF THE MID-ATLANTIC REGION

    Science.gov (United States)

    A fuzzy decision analysis method for integrating ecological indicators is developed. This is a combination of a fuzzy ranking method and the Analytic Hierarchy Process (AHP). The method is capable ranking ecosystems in terms of environmental conditions and suggesting cumula...

  13. A risk assessment methodology using intuitionistic fuzzy set in FMEA

    Science.gov (United States)

    Chang, Kuei-Hu; Cheng, Ching-Hsue

    2010-12-01

    Most current risk assessment methods use the risk priority number (RPN) value to evaluate the risk of failure. However, conventional RPN methodology has been criticised as having five main shortcomings as follows: (1) the assumption that the RPN elements are equally weighted leads to over simplification; (2) the RPN scale itself has some non-intuitive statistical properties; (3) the RPN elements have many duplicate numbers; (4) the RPN is derived from only three factors mainly in terms of safety; and (5) the conventional RPN method has not considered indirect relations between components. To address the above issues, an efficient and comprehensive algorithm to evaluate the risk of failure is needed. This article proposes an innovative approach, which integrates the intuitionistic fuzzy set (IFS) and the decision-making trial and evaluation laboratory (DEMATEL) approach on risk assessment. The proposed approach resolves some of the shortcomings of the conventional RPN method. A case study, which assesses the risk of 0.15 µm DRAM etching process, is used to demonstrate the effectiveness of the proposed approach. Finally, the result of the proposed method is compared with the listing approaches of risk assessment methods.

  14. A dynamic multimedia fuzzy-stochastic integrated environmental risk assessment approach for contaminated sites management

    Energy Technology Data Exchange (ETDEWEB)

    Hu, Yan; Wen, Jing-ya; Li, Xiao-li; Wang, Da-zhou; Li, Yu, E-mail: liyuxx8@hotmail.com

    2013-10-15

    Highlights: • Using interval mathematics to describe spatial and temporal variability and parameter uncertainty. • Using fuzzy theory to quantify variability of environmental guideline values. • Using probabilistic approach to integrate interval concentrations and fuzzy environmental guideline. • Establishment of dynamic multimedia environmental integrated risk assessment framework. -- Abstract: A dynamic multimedia fuzzy-stochastic integrated environmental risk assessment approach was developed for contaminated sites management. The contaminant concentrations were simulated by a validated interval dynamic multimedia fugacity model, and different guideline values for the same contaminant were represented as a fuzzy environmental guideline. Then, the probability of violating environmental guideline (Pv) can be determined by comparison between the modeled concentrations and the fuzzy environmental guideline, and the constructed relationship between the Pvs and environmental risk levels was used to assess the environmental risk level. The developed approach was applied to assess the integrated environmental risk at a case study site in China, simulated from 1985 to 2020. Four scenarios were analyzed, including “residential land” and “industrial land” environmental guidelines under “strict” and “loose” strictness. It was found that PAH concentrations will increase steadily over time, with soil found to be the dominant sink. Source emission in soil was the leading input and atmospheric sedimentation was the dominant transfer process. The integrated environmental risks primarily resulted from petroleum spills and coke ovens, while the soil environmental risks came from coal combustion. The developed approach offers an effective tool for quantifying variability and uncertainty in the dynamic multimedia integrated environmental risk assessment and the contaminated site management.

  15. A dynamic multimedia fuzzy-stochastic integrated environmental risk assessment approach for contaminated sites management

    International Nuclear Information System (INIS)

    Hu, Yan; Wen, Jing-ya; Li, Xiao-li; Wang, Da-zhou; Li, Yu

    2013-01-01

    Highlights: • Using interval mathematics to describe spatial and temporal variability and parameter uncertainty. • Using fuzzy theory to quantify variability of environmental guideline values. • Using probabilistic approach to integrate interval concentrations and fuzzy environmental guideline. • Establishment of dynamic multimedia environmental integrated risk assessment framework. -- Abstract: A dynamic multimedia fuzzy-stochastic integrated environmental risk assessment approach was developed for contaminated sites management. The contaminant concentrations were simulated by a validated interval dynamic multimedia fugacity model, and different guideline values for the same contaminant were represented as a fuzzy environmental guideline. Then, the probability of violating environmental guideline (Pv) can be determined by comparison between the modeled concentrations and the fuzzy environmental guideline, and the constructed relationship between the Pvs and environmental risk levels was used to assess the environmental risk level. The developed approach was applied to assess the integrated environmental risk at a case study site in China, simulated from 1985 to 2020. Four scenarios were analyzed, including “residential land” and “industrial land” environmental guidelines under “strict” and “loose” strictness. It was found that PAH concentrations will increase steadily over time, with soil found to be the dominant sink. Source emission in soil was the leading input and atmospheric sedimentation was the dominant transfer process. The integrated environmental risks primarily resulted from petroleum spills and coke ovens, while the soil environmental risks came from coal combustion. The developed approach offers an effective tool for quantifying variability and uncertainty in the dynamic multimedia integrated environmental risk assessment and the contaminated site management

  16. Integrated circuit implementation of fuzzy controllers

    OpenAIRE

    Huertas Díaz, José Luis; Sánchez Solano, Santiago; Baturone Castillo, María Iluminada; Barriga Barros, Ángel

    1996-01-01

    This paper presents mixed-signal current-mode CMOS circuits to implement programmable fuzzy controllers that perform the singleton or zero-order Sugeno’s method. Design equations to characterize these circuits are provided to explain the precision and speed that they offer. This analysis is illustrated with the experimental results of prototypes integrated in standard CMOS technologies. These tests show that an equivalent precision of 6 bits is achieved. The connection of these...

  17. Fractional order integration and fuzzy logic based filter for denoising of echocardiographic image.

    Science.gov (United States)

    Saadia, Ayesha; Rashdi, Adnan

    2016-12-01

    Ultrasound is widely used for imaging due to its cost effectiveness and safety feature. However, ultrasound images are inherently corrupted with speckle noise which severely affects the quality of these images and create difficulty for physicians in diagnosis. To get maximum benefit from ultrasound imaging, image denoising is an essential requirement. To perform image denoising, a two stage methodology using fuzzy weighted mean and fractional integration filter has been proposed in this research work. In stage-1, image pixels are processed by applying a 3 × 3 window around each pixel and fuzzy logic is used to assign weights to the pixels in each window, replacing central pixel of the window with weighted mean of all neighboring pixels present in the same window. Noise suppression is achieved by assigning weights to the pixels while preserving edges and other important features of an image. In stage-2, the resultant image is further improved by fractional order integration filter. Effectiveness of the proposed methodology has been analyzed for standard test images artificially corrupted with speckle noise and real ultrasound B-mode images. Results of the proposed technique have been compared with different state-of-the-art techniques including Lsmv, Wiener, Geometric filter, Bilateral, Non-local means, Wavelet, Perona et al., Total variation (TV), Global Adaptive Fractional Integral Algorithm (GAFIA) and Improved Fractional Order Differential (IFD) model. Comparison has been done on quantitative and qualitative basis. For quantitative analysis different metrics like Peak Signal to Noise Ratio (PSNR), Speckle Suppression Index (SSI), Structural Similarity (SSIM), Edge Preservation Index (β) and Correlation Coefficient (ρ) have been used. Simulations have been done using Matlab. Simulation results of artificially corrupted standard test images and two real Echocardiographic images reveal that the proposed method outperforms existing image denoising techniques

  18. Interval-Valued Intuitionistic Fuzzy Multicriteria Group Decision Making Based on VIKOR and Choquet Integral

    Directory of Open Access Journals (Sweden)

    Chunqiao Tan

    2013-01-01

    Full Text Available An effective decision making approach based on VIKOR and Choquet integral is developed to solve multicriteria group decision making problem with conflicting criteria and interdependent subjective preference of decision makers in a fuzzy environment where preferences of decision makers with respect to criteria are represented by interval-valued intuitionistic fuzzy sets. First, an interval-valued intuitionistic fuzzy Choquet integral operator is given. Some of its properties are investigated in detail. The extended VIKOR decision procedure based on the proposed operator is developed for solving the multicriteria group decision making problem where the interactive criteria weight is measured by Shapley value. An illustrative example is given for demonstrating the applicability of the proposed decision procedure for solving the multi-criteria group decision making problem in interval-valued intuitionistic fuzzy environment.

  19. Evaluation of pull production control strategies under uncertainty: An integrated fuzzy AHP-TOPSIS approach

    Directory of Open Access Journals (Sweden)

    Aydin Torkabadi

    2018-03-01

    Full Text Available Purpose: Just-In-Time (JIT production has continuously been considered by industrial practitioners and researchers as a leading strategy for the yet popular Lean production. Pull Production Control Policies (PPCPs are the major enablers of JIT that locally control the level of inventory by authorizing the production in each station. Aiming to improve the PPCPs, three authorization mechanisms: Kanban, constant-work-in-process (ConWIP, and a hybrid system, are evaluated by considering uncertainty. Design/methodology/approach: Multi-Criteria Decision Making (MCDM methods are successful in evaluating alternatives with respect to several objectives. The proposed approach of this study applies the fuzzy set theory together with an integrated Analytical Hierarchy Process (AHP and a Technique for Order Performance by Similarity to Ideal Solution (TOPSIS method. Findings: The study finds that hybrid Kanban-ConWIP pull production control policies have a better performance in controlling the studied multi-layer multi-stage manufacturing and assembly system. Practical implications: To examine the approach a real case from automobile electro mechanical part production industry is studied. The production system consists of multiple levels of manufacturing, feeding a multi-stage assembly line with stochastic processing times to satisfy the changing demand. Originality/value: This study proposes the integrated Kanban-ConWIP hybrid pull control policies and implements several alternatives on a multi-stage and multi-layer manufacturing and assembly production system. An integrated Fuzzy AHP TOPSIS method is developed to evaluate the alternatives with respect to several JIT criteria.

  20. Application of integrated QFD and fuzzy AHP approach in selection of suppliers

    Directory of Open Access Journals (Sweden)

    Bojana Jovanović

    2014-10-01

    Full Text Available Supplier selection is a widely considered issue in the field of management, especially in quality management. In this paper, in the selection of suppliers of electronic components we used the integrated QFD and fuzzy AHP approaches. The QFD method is used as a tool for translating stakeholder needs into evaluating criteria for suppliers. The fuzzy AHP approach is used as a tool for prioritizing stakeholders, stakeholders’ requirements, evaluating criteria and, finally, for prioritizing suppliers. The paper showcases a case study of implementation of the integrated QFD and fuzzy AHP approaches in the selection of the electronic components supplier in one Serbian company that produces electronic devices. Also presented is the algorithm of implementation of the proposed approach. To the best of our knowledge, this is the first implementation of the proposed approach in a Serbian company.

  1. Fuzzy attitude control for a nanosatellite in leo orbit

    Science.gov (United States)

    Calvo, Daniel; Laverón-Simavilla, Ana; Lapuerta, Victoria; Aviles, Taisir

    Fuzzy logic controllers are flexible and simple, suitable for small satellites Attitude Determination and Control Subsystems (ADCS). In this work, a tailored fuzzy controller is designed for a nanosatellite and is compared with a traditional Proportional Integrative Derivative (PID) controller. Both control methodologies are compared within the same specific mission. The orbit height varies along the mission from injection at around 380 km down to a 200 km height orbit, and the mission requires pointing accuracy over the whole time. Due to both the requirements imposed by such a low orbit, and the limitations in the power available for the attitude control, a robust and efficient ADCS is required. For these reasons a fuzzy logic controller is implemented as the brain of the ADCS and its performance and efficiency are compared to a traditional PID. The fuzzy controller is designed in three separated controllers, each one acting on one of the Euler angles of the satellite in an orbital frame. The fuzzy memberships are constructed taking into account the mission requirements, the physical properties of the satellite and the expected performances. Both methodologies, fuzzy and PID, are fine-tuned using an automated procedure to grant maximum efficiency with fixed performances. Finally both methods are probed in different environments to test their characteristics. The simulations show that the fuzzy controller is much more efficient (up to 65% less power required) in single maneuvers, achieving similar, or even better, precision than the PID. The accuracy and efficiency improvement of the fuzzy controller increase with orbit height because the environmental disturbances decrease, approaching the ideal scenario. A brief mission description is depicted as well as the design process of both ADCS controllers. Finally the validation process and the results obtained during the simulations are described. Those results show that the fuzzy logic methodology is valid for small

  2. An Integrated MCDM Model for Conveyor Equipment Evaluation and Selection in an FMC Based on a Fuzzy AHP and Fuzzy ARAS in the Presence of Vagueness

    Science.gov (United States)

    Nguyen, Huu-Tho; Md Dawal, Siti Zawiah; Nukman, Yusoff; P. Rifai, Achmad; Aoyama, Hideki

    2016-01-01

    The conveyor system plays a vital role in improving the performance of flexible manufacturing cells (FMCs). The conveyor selection problem involves the evaluation of a set of potential alternatives based on qualitative and quantitative criteria. This paper presents an integrated multi-criteria decision making (MCDM) model of a fuzzy AHP (analytic hierarchy process) and fuzzy ARAS (additive ratio assessment) for conveyor evaluation and selection. In this model, linguistic terms represented as triangular fuzzy numbers are used to quantify experts’ uncertain assessments of alternatives with respect to the criteria. The fuzzy set is then integrated into the AHP to determine the weights of the criteria. Finally, a fuzzy ARAS is used to calculate the weights of the alternatives. To demonstrate the effectiveness of the proposed model, a case study is performed of a practical example, and the results obtained demonstrate practical potential for the implementation of FMCs. PMID:27070543

  3. Development of fuzzy air quality index using soft computing approach.

    Science.gov (United States)

    Mandal, T; Gorai, A K; Pathak, G

    2012-10-01

    Proper assessment of air quality status in an atmosphere based on limited observations is an essential task for meeting the goals of environmental management. A number of classification methods are available for estimating the changing status of air quality. However, a discrepancy frequently arises from the quality criteria of air employed and vagueness or fuzziness embedded in the decision making output values. Owing to inherent imprecision, difficulties always exist in some conventional methodologies like air quality index when describing integrated air quality conditions with respect to various pollutants parameters and time of exposure. In recent years, the fuzzy logic-based methods have demonstrated to be appropriated to address uncertainty and subjectivity in environmental issues. In the present study, a methodology based on fuzzy inference systems (FIS) to assess air quality is proposed. This paper presents a comparative study to assess status of air quality using fuzzy logic technique and that of conventional technique. The findings clearly indicate that the FIS may successfully harmonize inherent discrepancies and interpret complex conditions.

  4. Chaos Synchronization Based on Unknown Input Proportional Multiple-Integral Fuzzy Observer

    Directory of Open Access Journals (Sweden)

    T. Youssef

    2013-01-01

    Full Text Available This paper presents an unknown input Proportional Multiple-Integral Observer (PIO for synchronization of chaotic systems based on Takagi-Sugeno (TS fuzzy chaotic models subject to unmeasurable decision variables and unknown input. In a secure communication configuration, this unknown input is regarded as a message encoded in the chaotic system and recovered by the proposed PIO. Both states and outputs of the fuzzy chaotic models are subject to polynomial unknown input with kth derivative zero. Using Lyapunov stability theory, sufficient design conditions for synchronization are proposed. The PIO gains matrices are obtained by resolving linear matrix inequalities (LMIs constraints. Simulation results show through two TS fuzzy chaotic models the validity of the proposed method.

  5. Human reliability analysis of performing tasks in plants based on fuzzy integral

    International Nuclear Information System (INIS)

    Washio, Takashi; Kitamura, Yutaka; Takahashi, Hideaki

    1991-01-01

    The effective improvement of the human working conditions in nuclear power plants might be a solution for the enhancement of the operation safety. The human reliability analysis (HRA) gives a methodological basis of the improvement based on the evaluation of human reliability under various working conditions. This study investigates some difficulties of the human reliability analysis using conventional linear models and recent fuzzy integral models, and provides some solutions to the difficulties. The following practical features of the provided methods are confirmed in comparison with the conventional methods: (1) Applicability to various types of tasks (2) Capability of evaluating complicated dependencies among working condition factors (3) A priori human reliability evaluation based on a systematic task analysis of human action processes (4) A conversion scheme to probability from indices representing human reliability. (author)

  6. Fuzzy hybrid MCDM approach for selection of wind turbine service technicians

    Directory of Open Access Journals (Sweden)

    Goutam Kumar Bose

    2016-01-01

    Full Text Available This research paper is aimed to present a fuzzy Hybrid Multi-criteria decision making (MCDM methodology for selecting employees. The present study aspires to present the hybrid approach of Fuzzy multiple MCDM techniques with tactical viewpoint to support the recruitment process of wind turbine service technicians. The methodology is based on the application of Fuzzy ARAS (Additive Ratio Assessment and Fuzzy MOORA (Multi-Objective Optimization on basis of Ratio Analysis which are integrated through group decision making (GDM method in the model for selection of wind turbine service technicians’ ranking. Here a group of experts from different fields of expertise are engaged to finalize the decision. Series of tests are conducted regarding physical fitness, technical written test, practical test along with general interview and medical examination to facilitate the final selection using the above techniques. In contrast to single decision making approaches, the proposed group decision making model efficiently supports the wind turbine service technicians ranking process. The effectiveness of the proposed approach manifest from the case study of service technicians required for the maintenance department of wind power plant using Fuzzy ARAS and Fuzzy MOORA. This set of potential technicians is evaluated based on five main criteria.

  7. Fuzzy Decision Analysis for Integrated Environmental Vulnerability Assessment of the Mid-Atlantic Region

    Science.gov (United States)

    Liem T. Tran; C. Gregory Knight; Robert V. O' Neill; Elizabeth R. Smith; Kurt H. Riitters; James D. Wickham

    2002-01-01

    A fuzzy decision analysis method for integrating ecological indicators was developed. This was a combination of a fuzzy ranking method and the analytic hierarchy process (AHP). The method was capable of ranking ecosystems in terms of environmental conditions and suggesting cumulative impacts across a large region. Using data on land cover, population, roads, streams,...

  8. Fuzzy comprehensive evaluation for grid-connected performance of integrated distributed PV-ES systems

    Science.gov (United States)

    Lv, Z. H.; Li, Q.; Huang, R. W.; Liu, H. M.; Liu, D.

    2016-08-01

    Based on the discussion about topology structure of integrated distributed photovoltaic (PV) power generation system and energy storage (ES) in single or mixed type, this paper focuses on analyzing grid-connected performance of integrated distributed photovoltaic and energy storage (PV-ES) systems, and proposes a comprehensive evaluation index system. Then a multi-level fuzzy comprehensive evaluation method based on grey correlation degree is proposed, and the calculations for weight matrix and fuzzy matrix are presented step by step. Finally, a distributed integrated PV-ES power generation system connected to a 380 V low voltage distribution network is taken as the example, and some suggestions are made based on the evaluation results.

  9. Integrating Fuzzy AHP and Fuzzy ARAS for evaluating financial performance

    Directory of Open Access Journals (Sweden)

    Abdolhamid Safaei Ghadikolaei

    2014-09-01

    Full Text Available Multi Criteria Decision Making (MCDM is an advanced field of Operation Research; recently MCDM methods are efficient and common tools for performance evaluation in many areas such as finance and economy. The aim of this study is to show one of applications of mathematics in real word. This study with considering value based measures and accounting based measures simultaneously, provided a hybrid approach of MCDM methods in fuzzy environment for financial performance evaluation of automotive and parts manufacturing industry of Tehran stock exchange (TSE.for this purpose Fuzzy analytic hierarchy process (FAHP is applied to determine the relative important of each criterion, then The companies are ranked according their financial performance by using fuzzy additive ratio assessment (Fuzzy ARAS method. The finding of this study showed effective of this approach in evaluating financial performance.

  10. Intuitionistic fuzzy calculus

    CERN Document Server

    Lei, Qian

    2017-01-01

    This book offers a comprehensive and systematic review of the latest research findings in the area of intuitionistic fuzzy calculus. After introducing the intuitionistic fuzzy numbers’ operational laws and their geometrical and algebraic properties, the book defines the concept of intuitionistic fuzzy functions and presents the research on the derivative, differential, indefinite integral and definite integral of intuitionistic fuzzy functions. It also discusses some of the methods that have been successfully used to deal with continuous intuitionistic fuzzy information or data, which are different from the previous aggregation operators focusing on discrete information or data. Mainly intended for engineers and researchers in the fields of fuzzy mathematics, operations research, information science and management science, this book is also a valuable textbook for postgraduate and advanced undergraduate students alike.

  11. Fuzzy Adaptive Cubature Kalman Filter for Integrated Navigation Systems.

    Science.gov (United States)

    Tseng, Chien-Hao; Lin, Sheng-Fuu; Jwo, Dah-Jing

    2016-07-26

    This paper presents a sensor fusion method based on the combination of cubature Kalman filter (CKF) and fuzzy logic adaptive system (FLAS) for the integrated navigation systems, such as the GPS/INS (Global Positioning System/inertial navigation system) integration. The third-degree spherical-radial cubature rule applied in the CKF has been employed to avoid the numerically instability in the system model. In processing navigation integration, the performance of nonlinear filter based estimation of the position and velocity states may severely degrade caused by modeling errors due to dynamics uncertainties of the vehicle. In order to resolve the shortcoming for selecting the process noise covariance through personal experience or numerical simulation, a scheme called the fuzzy adaptive cubature Kalman filter (FACKF) is presented by introducing the FLAS to adjust the weighting factor of the process noise covariance matrix. The FLAS is incorporated into the CKF framework as a mechanism for timely implementing the tuning of process noise covariance matrix based on the information of degree of divergence (DOD) parameter. The proposed FACKF algorithm shows promising accuracy improvement as compared to the extended Kalman filter (EKF), unscented Kalman filter (UKF), and CKF approaches.

  12. Fuzzy Adaptive Cubature Kalman Filter for Integrated Navigation Systems

    Directory of Open Access Journals (Sweden)

    Chien-Hao Tseng

    2016-07-01

    Full Text Available This paper presents a sensor fusion method based on the combination of cubature Kalman filter (CKF and fuzzy logic adaptive system (FLAS for the integrated navigation systems, such as the GPS/INS (Global Positioning System/inertial navigation system integration. The third-degree spherical-radial cubature rule applied in the CKF has been employed to avoid the numerically instability in the system model. In processing navigation integration, the performance of nonlinear filter based estimation of the position and velocity states may severely degrade caused by modeling errors due to dynamics uncertainties of the vehicle. In order to resolve the shortcoming for selecting the process noise covariance through personal experience or numerical simulation, a scheme called the fuzzy adaptive cubature Kalman filter (FACKF is presented by introducing the FLAS to adjust the weighting factor of the process noise covariance matrix. The FLAS is incorporated into the CKF framework as a mechanism for timely implementing the tuning of process noise covariance matrix based on the information of degree of divergence (DOD parameter. The proposed FACKF algorithm shows promising accuracy improvement as compared to the extended Kalman filter (EKF, unscented Kalman filter (UKF, and CKF approaches.

  13. Green Supplier Evaluation by Using an Integrated Fuzzy AHP- VIKOR Approach

    Directory of Open Access Journals (Sweden)

    Mehdi HakimiAsl

    2016-08-01

    Full Text Available In the previous decade, fossil energy resources shortage and environmental challenges such as air and water pollution, global warming, and greenhouse-gas emissions, etc. have increased environmental concerns considerably. Since, one of the most practical and useful solutions to decrease environmental pollutants is to deploy green purchasing and clean energies by organizations or even governments. Thus, the construction of renewable-energy power plants and, consequently, the green supplier selection for these plants’ equipment has become more important. With this respect, this article presents a novel approach to assess and select green suppliers of a solar power plant. The proposed approach integrates Fuzzy Analytic Hierarchy Process and VIKOR (Vise Kriterijumska Optimizacija I Kompromisno Resenje methodologies. The results demonstrate the efficiency of the proposed approach as a practical tool to assist managers and CEOs (Chief Executive Officers of electric power industry in assessing suppliers of solar power plant’s equipment.

  14. Optimal Partner Combination for Joint Distribution Alliance using Integrated Fuzzy EW-AHP and TOPSIS for Online Shopping

    Directory of Open Access Journals (Sweden)

    Yandong He

    2016-04-01

    Full Text Available With the globalization of online shopping, deterioration of the ecological environment and the increasing pressure of urban transportation, a novel logistics service mode—joint distribution (JD—was developed. Selecting the optimal partner combination is important to ensure the joint distribution alliance (JDA is sustainable and stable, taking into consideration conflicting criteria. In this paper, we present an integrated fuzzy entropy weight, fuzzy analytic hierarchy process (fuzzy EW-AHP and fuzzy technique for order preference by similarity to an ideal solution (TOPSIS approach to select the optimal partner combination of JDA. A three-phase approach is proposed. In the first phase, we identify partner combination evaluation criteria using an economy-society-environment-flexibility (ESEF framework from a perspective that considers sustainability. In the second phase, the criteria weights and criteria combination performance of different partner combinations were calculated by using an integrated fuzzy EW-AHP approach considering the objective and subjective factors of experts. In the third phase, the JDA partner combinations are ranked by employing fuzzy TOPSIS approach. The sensitivity analysis is considered for the optimal partner combination. Taking JDA in Chongqing for example, the results indicate the alternative partner combination 3 (PC3 is always ranked first no matter how the criteria weights change. It is effective and robust to apply the integrated fuzzy EW-AHP and TOPSIS approach to the partner selection of JDA.

  15. A generic methodology for developing fuzzy decision models

    NARCIS (Netherlands)

    Bosma, R.; Berg, van den J.; Kaymak, U.; Udo, H.; Verreth, J.

    2012-01-01

    An important paradigm in decision-making models is utility-maximization where most models do not include actors’ motives. Fuzzy set theory on the other hand offers a method to simulate human decisionmaking. However, the literature describing expert-driven fuzzy logic models, rarely gives precise

  16. A generic methodology for developing fuzzy decision models

    NARCIS (Netherlands)

    Bosma, R.H.; Berg, van den J.; Kaymak, Uzay; Udo, H.M.J.; Verreth, J.A.J.

    2012-01-01

    An important paradigm in decision-making models is utility-maximization where most models do not include actors’ motives. Fuzzy set theory on the other hand offers a method to simulate human decision-making. However, the literature describing expert-driven fuzzy logic models, rarely gives precise

  17. Determining the number of kanbans for dynamic production systems: An integrated methodology

    Directory of Open Access Journals (Sweden)

    Özlem Uzun Araz

    2016-08-01

    Full Text Available Just-in-time (JIT is a management philosophy that reduces the inventory levels and eliminates manufacturing wastes by producing only the right quantity at the right time. A kanban system is one of the key elements of JIT philosophy. Kanbans are used to authorize production and to control movement of materials in JIT systems. In Kanban systems, the efficiency of the manufacturing system depends on several factors such as number of kanbans, container size etc. Hence, determining the number of kanbans is a critical decision in Kanban systems. The aim of this study is to develop a methodology that can be used in order to determine the number of kanbans in a dynamic production environment. In this methodology, the changes in system state is monitored in real time manner, and the number of the kanbans are dynamically re-arranged. The proposed methodology integrates simulation, neural networks and Mamdani type fuzzy inference system. The methodology is modelled in simulation environment and applied on a hypothetic production system. We also performed several comparisons for different control policies to show the effectiveness of the proposed methodology.

  18. Utilization integrated Fuzzy-QFD and TOPSIS approach in supplier selection

    Directory of Open Access Journals (Sweden)

    2016-02-01

    Full Text Available Supplier selection is a typical multi-attribute problem that involves both qualitative and quantitative factors. To deal with this problem, different techniques have suggested. Being based on purely mathematical data, these techniques have significant drawbacks especially when we want to consider qualitative factors, which are very important in supplier selection and are not easy to measure. Some innovative approaches, based on artificial intelligence techniques such as Fuzzy Logic match very well with decision-making situations especially when decision makers express heterogeneous judgments. In this research, by the combination of Fuzzy logic and the House of Quality (HOQ, qualitative criteria are considered in the forward parts of car suppliers’ selection process in Sazehgostar SAIPA Company. Then, TOPSIS technique is adopted to consider quantitative metrics. Finally, by combining of Fuzzy QFD and TOPSIS techniques, these suppliers will be selected and ranked in this Company. Concern to the both qualitative and quantitative criteria, is the important point used in this research and also methodology utilized, counts innovative aspect. Limited number of experts associated with each piece and unavailability of some quantitative criteria has been limitations across of this study’s accomplishment.

  19. Applying Fuzzy Multiobjective Integrated Logistics Model to Green Supply Chain Problems

    Directory of Open Access Journals (Sweden)

    Chui-Yu Chiu

    2014-01-01

    Full Text Available The aim of this paper is attempting to explore the optimal way of supply chain management within the domain of environmental responsibility and concerns. The background of this research involves the issue of green supply chain management (GSCM and the concept of the multiobjective integrated logistics model. More specifically, in this paper, we suggest the fuzzy multiobjective integrated logistics model with the transportation cost and demand fuzziness to solve green supply chain problems in the uncertain environment which is illustrated via the detailed numerical example. Results and the sensitivity analysis of the numerical example indicate that when the governmental subsidy value increased the profits of the reverse chain also increased. The finding shows that the governmental subsidy policy could remain of significant influence for used-product reverse logistics chain.

  20. Comparison of Fuzzy AHP and Fuzzy TOPSIS for Road Pavement Maintenance Prioritization: Methodological Exposition and Case Study

    OpenAIRE

    Yashon O. Ouma; J. Opudo; S. Nyambenya

    2015-01-01

    For road pavement maintenance and repairs prioritization, a multiattribute approach that compares fuzzy Analytical Hierarchy Process (AHP) and fuzzy Technique for Order Preference by Ideal Situation (TOPSIS) is evaluated. The pavement distress data was collected through empirical condition surveys and rating by pavement experts. In comparison to the crisp AHP, the fuzzy AHP and fuzzy TOPSIS pairwise comparison techniques are considered to be more suitable for the subjective analysis of the pa...

  1. Uncertainty analysis of flexible rotors considering fuzzy parameters and fuzzy-random parameters

    Directory of Open Access Journals (Sweden)

    Fabian Andres Lara-Molina

    Full Text Available Abstract The components of flexible rotors are subjected to uncertainties. The main sources of uncertainties include the variation of mechanical properties. This contribution aims at analyzing the dynamics of flexible rotors under uncertain parameters modeled as fuzzy and fuzzy random variables. The uncertainty analysis encompasses the modeling of uncertain parameters and the numerical simulation of the corresponding flexible rotor model by using an approach based on fuzzy dynamic analysis. The numerical simulation is accomplished by mapping the fuzzy parameters of the deterministic flexible rotor model. Thereby, the flexible rotor is modeled by using both the Fuzzy Finite Element Method and the Fuzzy Stochastic Finite Element Method. Numerical simulations illustrate the methodology conveyed in terms of orbits and frequency response functions subject to uncertain parameters.

  2. A comparative analysis for multiattribute selection among renewable energy alternatives using fuzzy axiomatic design and fuzzy analytic hierarchy process

    Energy Technology Data Exchange (ETDEWEB)

    Kahraman, Cengiz; Kaya, Ihsan; Cebi, Selcuk [Istanbul Technical University, Department of Industrial Engineering, 34367, Macka-Istanbul (Turkey)

    2009-10-15

    Renewable energy is the energy generated from natural resources such as sunlight, wind, rain, tides and geothermal heat which are renewable. Energy resources are very important in perspective of economics and politics for all countries. Hence, the selection of the best alternative for any country takes an important role for energy investments. Among decision-making methodologies, axiomatic design (AD) and analytic hierarchy process (AHP) are often used in the literature. The fuzzy set theory is a powerful tool to treat the uncertainty in case of incomplete or vague information. In this paper, fuzzy multicriteria decision- making methodologies are suggested for the selection among renewable energy alternatives. The first methodology is based on the AHP which allows the evaluation scores from experts to be linguistic expressions, crisp, or fuzzy numbers, while the second is based on AD principles under fuzziness which evaluates the alternatives under objective or subjective criteria with respect to the functional requirements obtained from experts. The originality of the paper comes from the fuzzy AD application to the selection of the best renewable energy alternative and the comparison with fuzzy AHP. In the application of the proposed methodologies the most appropriate renewable energy alternative is determined for Turkey. (author)

  3. An integrated approach for solving a MCDM problem, Combination of Entropy Fuzzy and F-PROMETHEE techniques

    Directory of Open Access Journals (Sweden)

    Amin Shahmardan

    2013-09-01

    Full Text Available Purpose: The intention of this paper is the presentation of a new integrated approach for solving a multi attribute decision making problem by the use of Entropy Fuzzy and F- PROMETHEE (fuzzy preference ranking method for enrichment evaluation techniques. Design/methodology/approach: In these sorts of multi attribute decision making problem, a number of criteria and alternatives are put forward as input data. Ranking of these alternatives according to mentioned criteria is regarded as the outcome of solving these kinds of problems. Initially, weights of criteria are determined by implementation of Entropy Fuzzy method. According to determined weights, F-PROMETHEE method is exerted to rank these alternatives in terms of desirability of DM (decision maker. Findings: Being in an uncertain environment and vagueness of DM’s judgments, lead us to implement an algorithm which can deal with these constraints properly. This technique namely called Entropy Fuzzy as a weighting method and F-PROMETHEE is performed to fulfill this approach more precisely according to tangible and intangible aspects. The main finding of applied approach is the final ranking of alternatives helping DM to have a more reliable decision. Originality/Value: The main contribution of this approach is the giving real significance to DM’s attitudes about mentioned criteria in determined alternatives which is not elucidate in former approaches like Analytical Hierarchy Process (AHP. Furthermore, previous methods like Shanon Entropy do not pay attention sufficiently to satisfaction degree of each criterion in proposed alternatives, regarding to DM’s statements. Comprehensive explanations about these procedures have been made in miscellaneous sections of this article.

  4. A neural fuzzy controller learning by fuzzy error propagation

    Science.gov (United States)

    Nauck, Detlef; Kruse, Rudolf

    1992-01-01

    In this paper, we describe a procedure to integrate techniques for the adaptation of membership functions in a linguistic variable based fuzzy control environment by using neural network learning principles. This is an extension to our work. We solve this problem by defining a fuzzy error that is propagated back through the architecture of our fuzzy controller. According to this fuzzy error and the strength of its antecedent each fuzzy rule determines its amount of error. Depending on the current state of the controlled system and the control action derived from the conclusion, each rule tunes the membership functions of its antecedent and its conclusion. By this we get an unsupervised learning technique that enables a fuzzy controller to adapt to a control task by knowing just about the global state and the fuzzy error.

  5. The first order fuzzy predicate logic (I)

    International Nuclear Information System (INIS)

    Sheng, Y.M.

    1986-01-01

    Some analysis tools of fuzzy measures, Sugeno's integrals, etc. are introduced into the semantic of the first order predicate logic to explain the concept of fuzzy quantifiers. The truth value of a fuzzy quantification proposition is represented by Sugeno's integral. With this framework, several important notions of formation rules, fuzzy valutions and fuzzy validity are discussed

  6. Integration of fuzzy reasoning approach (FRA and fuzzy analytic hierarchy process (FAHP for risk assessment in mining industry

    Directory of Open Access Journals (Sweden)

    Shikha Verma

    2014-10-01

    Full Text Available Purpose: Mining industry has always been known for its unsafe working environment. This industry is one of the most hazard prone industries. To maintain safety in workplace timely assessment of risk associated with different operations performed to extract ore from the ore body has become necessity. To serve the said purpose, present work demonstrates a robust hybrid risk assessment approach for mining industry.Design/Methodology: Accident data from 1995 to 2012 is reviewed to identify hazards contributed to negative outcomes. The FRA approach is implemented to evaluate the risk levels associated with identified hazard factors. Thereafter AHP pairwise comparison matrix is developed to obtain priority weights for the hazard factors. Final priority of hazards based on severity of level of risk associated with them is obtained considering the outcome of FRA approach in terms of risk score for the hazards, combined with the priority weights obtained from AHP technique.Findings: Defuzzified FAHP weight of hazard factors, this weight gives priority sequence of hazards to be considered for development of plan of mitigation.Originality/Value: Risk assessment is a requirement of the Occupational Health and Safety Act 2000 (Section 7& 8. The data required to assess the risk is uncertain, and in such case fuzzy approach is well suited to process the data and get the crisp output. The output of fuzzy approach is made robust with its integration to AHP. In this way FAHP can be used as robust technique for risk assessment in this industry and this technique develops an efficient safety management system for the achievement of goal to develop the workplace with zero accident, which many other countries have already achieved.

  7. Application of fuzzy set theory for integral assessment of agricultural products quality

    Science.gov (United States)

    Derkanosova, N. M.; Ponomareva, I. N.; Shurshikova, G. V.; Vasilenko, O. A.

    2018-05-01

    The methodology of integrated assessment of quality and safety of agricultural products, approbated by the example of indicators of wheat grain in relation to the provision of consumer properties of bakery products, was developed. Determination of the level of quality of the raw ingredients will allow direct using of agricultural raw materials for food production, taking into account ongoing technology, types of products, and, respectively, rational use of resource potential of the agricultural sector. The mathematical tool of the proposed method is a fuzzy set theory. The fuzzy classifier to evaluate the properties of the grain is formed. The set of six indicators normalized by the national standard is determined; values are ordered and represented by linguistic variables with a trapeziform membership function; the rules for calculation of membership functions are presented. Specific criteria values for individual indicators in shaping the quality of the finished products are considered. For one of the samples of wheat grain values of membership; functions of the linguistic variable "level" for all indicators and the linguistic variable "level of quality" were calculated. It is established that the studied sample of grain obtains the 2 (average) level of quality. Accordingly, it can be recommended for the production of bakery products with higher requirements for the structural-mechanical properties bakery and puff pastry products hearth bread and flour confectionery products of the group of hard dough cookies and crackers

  8. Integration of fuzzy theory into Kano model for classification of service quality elements: A case study in a machinery industry of China

    Directory of Open Access Journals (Sweden)

    Qingliang Meng

    2015-11-01

    Full Text Available Purpose: The purpose of study is to meet customer requirements and improve customer satisfaction that aims to classify customer requirements more effectively. And the classification is focused on the customer psychology. Design/methodology/approach: In this study, considering the advantages of Kano model in taking into account both customer’s consuming psychology and motivation, and combining with fuzzy theory which is effective to cope with uncertainty and ambiguity, a Kano model based on fuzzy theory is proposed. In view of the strong subjectivity of traditional Kano questionnaires, a fuzzy Kano questionnaire to classify the service quality elements more objectively is proposed. Furthermore, this study will also develop a mathematical calculation performance according to the quality classification of fuzzy Kano model. It’s more objective than traditional Kano model to realize the service quality elements classification. With this method, the accurate mentality can be fully reasonable reflected in some unknown circumstances. Finally, an empirical study in Xuzhou Construction Machinery Group Co., Ltd, the largest manufacturing industry in China, is showed to testify its feasibility and validity. Findings: The calculation results indicate that the proposed model has good performance in classifying customer requirements. With this method, the accurate mentality can be fully reasonable reflected in unknown circumstances and it is more objective than traditional Kano model to classify the service quality elements. Originality/value: This study provides a method to integrate fuzzy theory and Kano model, and develops a mathematical calculation performance according to the quality classification of fuzzy Kano model.

  9. Fuzzy-Rule-Based Object Identification Methodology for NAVI System

    Directory of Open Access Journals (Sweden)

    Yaacob Sazali

    2005-01-01

    Full Text Available We present an object identification methodology applied in a navigation assistance for visually impaired (NAVI system. The NAVI has a single board processing system (SBPS, a digital video camera mounted headgear, and a pair of stereo earphones. The captured image from the camera is processed by the SBPS to generate a specially structured stereo sound suitable for vision impaired people in understanding the presence of objects/obstacles in front of them. The image processing stage is designed to identify the objects in the captured image. Edge detection and edge-linking procedures are applied in the processing of image. A concept of object preference is included in the image processing scheme and this concept is realized using a fuzzy-rule base. The blind users are trained with the stereo sound produced by NAVI for achieving a collision-free autonomous navigation.

  10. Fuzzy-Rule-Based Object Identification Methodology for NAVI System

    Science.gov (United States)

    Nagarajan, R.; Sainarayanan, G.; Yaacob, Sazali; Porle, Rosalyn R.

    2005-12-01

    We present an object identification methodology applied in a navigation assistance for visually impaired (NAVI) system. The NAVI has a single board processing system (SBPS), a digital video camera mounted headgear, and a pair of stereo earphones. The captured image from the camera is processed by the SBPS to generate a specially structured stereo sound suitable for vision impaired people in understanding the presence of objects/obstacles in front of them. The image processing stage is designed to identify the objects in the captured image. Edge detection and edge-linking procedures are applied in the processing of image. A concept of object preference is included in the image processing scheme and this concept is realized using a fuzzy-rule base. The blind users are trained with the stereo sound produced by NAVI for achieving a collision-free autonomous navigation.

  11. Intellectual technologies in the problems of thermal power engineering control: formalization of fuzzy information processing results using the artificial intelligence methodology

    Science.gov (United States)

    Krokhin, G.; Pestunov, A.

    2017-11-01

    Exploitation conditions of power stations in variable modes and related changes of their technical state actualized problems of creating models for decision-making and state recognition basing on diagnostics using the fuzzy logic for identification their state and managing recovering processes. There is no unified methodological approach for obtaining the relevant information is a case of fuzziness and inhomogeneity of the raw information about the equipment state. The existing methods for extracting knowledge are usually unable to provide the correspondence between of the aggregates model parameters and the actual object state. The switchover of the power engineering from the preventive repair to the one, which is implemented according to the actual technical state, increased the responsibility of those who estimate the volume and the duration of the work. It may lead to inadequacy of the diagnostics and the decision-making models if corresponding methodological preparations do not take fuzziness into account, because the nature of the state information is of this kind. In this paper, we introduce a new model which formalizes the equipment state using not only exact information, but fuzzy as well. This model is more adequate to the actual state, than traditional analogs, and may be used in order to increase the efficiency and the service period of the power installations.

  12. FUZZY NEURAL NETWORK FOR OBJECT IDENTIFICATION ON INTEGRATED CIRCUIT LAYOUTS

    Directory of Open Access Journals (Sweden)

    A. A. Doudkin

    2015-01-01

    Full Text Available Fuzzy neural network model based on neocognitron is proposed to identify layout objects on images of topological layers of integrated circuits. Testing of the model on images of real chip layouts was showed a highеr degree of identification of the proposed neural network in comparison to base neocognitron.

  13. Comparison of Fuzzy AHP and Fuzzy TOPSIS for Road Pavement Maintenance Prioritization: Methodological Exposition and Case Study

    Directory of Open Access Journals (Sweden)

    Yashon O. Ouma

    2015-01-01

    Full Text Available For road pavement maintenance and repairs prioritization, a multiattribute approach that compares fuzzy Analytical Hierarchy Process (AHP and fuzzy Technique for Order Preference by Ideal Situation (TOPSIS is evaluated. The pavement distress data was collected through empirical condition surveys and rating by pavement experts. In comparison to the crisp AHP, the fuzzy AHP and fuzzy TOPSIS pairwise comparison techniques are considered to be more suitable for the subjective analysis of the pavement conditions for automated maintenance prioritization. From the case study results, four pavement maintenance objectives were determined as road safety, pavement surface preservation, road operational status and standards, and road aesthetics, with corresponding depreciating significance weights of W=0.37,0.31,0.22,0.10T. The top three maintenance functions were identified as Thin Hot Mix Asphalt (HMA overlays, resurfacing and slurry seals, which were a result of pavement cracking, potholes, raveling, and patching, while the bottom three were cape seal, micro surfacing, and fog seal. The two methods gave nearly the same prioritization ranking. In general, the fuzzy AHP approach tended to overestimate the maintenance prioritization ranking as compared to the fuzzy TOPSIS.

  14. A VIRTUAL REALITY EXPOSURE THERAPY FOR PTSD PATIENTS CONTROLLED BY A FUZZY LOGIC SYSTEM

    OpenAIRE

    Rosa Maria Esteves Moreira da Costa; Fernando Moraes de Oliveira; Regina Serrão Lanzillotti; Raquel Gonçalves; Luis Alfredo Vidal de Carvalho

    2014-01-01

    This paper describes the main characteristics of two integrated systems that explore Virtual Reality technology and Fuzzy Logic to support and to control the assessment of people with Post-Traumatic Stress Disorder during the Virtual Reality Exposure Therapy. The integration of different technologies, the development methodology and the test procedures are described throughout the paper.

  15. Analytical Support for Selecting the Best Investment Project in the Presence of Fuzzy Data

    Directory of Open Access Journals (Sweden)

    Kotsyuba Oleksiy S.

    2017-12-01

    Full Text Available The article is dedicated to the problem of optimal choice in the field of real investments in case of fuzzy estimates of financial and economic parameters. The general methodological basis of the research is an integrated approach to solving decision-making problems under conditions of uncertainty, conflict, and risk generated by them, based on the game theory, proposed by R. I. Trukhayev. In recent decades, it has been actively developed in papers by the followers of the scientific school of riskology under the leadership of V. V. Vitlinsky. One of the system-forming components of the above integration and game methodology is the classifier of information situations (there singled out seven of them. In this case, the description of possible states of the economic environment by a fuzzy set (a subset corresponds to the seventh information situation. An attempt was made to develop a methodical apparatus for the task of selecting the best investment project from a variety of alternative projects in the presence of fuzzy data. As a result, a model based on the use of convolutions of local criteria is formulated. In accordance with the accepted methodological guidelines, the structure of the generalized (integral indicator of the economic attractiveness (efficiency of real investment provides for three hierarchical levels: 1 the level of detailed criteria in terms of partial criteria (financial effect, profitability, payback period, 2 the level of partial criteria, 3 the level presenting the very generalized indicator. In the basic version of the proposed model, among the possible techniques (methods for aggregating indicators detailing the aspects of fuzzy estimates of partial criteria, the preference is given to the method by which they are joined by a combined, additive and multiplicative convolution.

  16. A Fuzzy Integral Ensemble Method in Visual P300 Brain-Computer Interface

    Directory of Open Access Journals (Sweden)

    Francesco Cavrini

    2016-01-01

    Full Text Available We evaluate the possibility of application of combination of classifiers using fuzzy measures and integrals to Brain-Computer Interface (BCI based on electroencephalography. In particular, we present an ensemble method that can be applied to a variety of systems and evaluate it in the context of a visual P300-based BCI. Offline analysis of data relative to 5 subjects lets us argue that the proposed classification strategy is suitable for BCI. Indeed, the achieved performance is significantly greater than the average of the base classifiers and, broadly speaking, similar to that of the best one. Thus the proposed methodology allows realizing systems that can be used by different subjects without the need for a preliminary configuration phase in which the best classifier for each user has to be identified. Moreover, the ensemble is often capable of detecting uncertain situations and turning them from misclassifications into abstentions, thereby improving the level of safety in BCI for environmental or device control.

  17. Human error probability quantification using fuzzy methodology in nuclear plants; Aplicacao da metodologia fuzzy na quantificacao da probabilidade de erro humano em instalacoes nucleares

    Energy Technology Data Exchange (ETDEWEB)

    Nascimento, Claudio Souza do

    2010-07-01

    This work obtains Human Error Probability (HEP) estimates from operator's actions in response to emergency situations a hypothesis on Research Reactor IEA-R1 from IPEN. It was also obtained a Performance Shaping Factors (PSF) evaluation in order to classify them according to their influence level onto the operator's actions and to determine these PSF actual states over the plant. Both HEP estimation and PSF evaluation were done based on Specialists Evaluation using interviews and questionnaires. Specialists group was composed from selected IEA-R1 operators. Specialist's knowledge representation into linguistic variables and group evaluation values were obtained through Fuzzy Logic and Fuzzy Set Theory. HEP obtained values show good agreement with literature published data corroborating the proposed methodology as a good alternative to be used on Human Reliability Analysis (HRA). (author)

  18. Fuzzy logic and neural networks in artificial intelligence and pattern recognition

    Science.gov (United States)

    Sanchez, Elie

    1991-10-01

    With the use of fuzzy logic techniques, neural computing can be integrated in symbolic reasoning to solve complex real world problems. In fact, artificial neural networks, expert systems, and fuzzy logic systems, in the context of approximate reasoning, share common features and techniques. A model of Fuzzy Connectionist Expert System is introduced, in which an artificial neural network is designed to construct the knowledge base of an expert system from, training examples (this model can also be used for specifications of rules in fuzzy logic control). Two types of weights are associated with the synaptic connections in an AND-OR structure: primary linguistic weights, interpreted as labels of fuzzy sets, and secondary numerical weights. Cell activation is computed through min-max fuzzy equations of the weights. Learning consists in finding the (numerical) weights and the network topology. This feedforward network is described and first illustrated in a biomedical application (medical diagnosis assistance from inflammatory-syndromes/proteins profiles). Then, it is shown how this methodology can be utilized for handwritten pattern recognition (characters play the role of diagnoses): in a fuzzy neuron describing a number for example, the linguistic weights represent fuzzy sets on cross-detecting lines and the numerical weights reflect the importance (or weakness) of connections between cross-detecting lines and characters.

  19. Genetic algorithm-based fuzzy-PID control methodologies for enhancement of energy efficiency of a dynamic energy system

    International Nuclear Information System (INIS)

    Jahedi, G.; Ardehali, M.M.

    2011-01-01

    The simplicity in coding the heuristic judgment of experienced operator by means of fuzzy logic can be exploited for enhancement of energy efficiency. Fuzzy logic has been used as an effective tool for scheduling conventional PID controllers gain coefficients (F-PID). However, to search for the most desirable fuzzy system characteristics that allow for best performance of the energy system with minimum energy input, optimization techniques such as genetic algorithm (GA) could be utilized and the control methodology is identified as GA-based F-PID (GA-F-PID). The objective of this study is to examine the performance of PID, F-PID, and GA-F-PID controllers for enhancement of energy efficiency of a dynamic energy system. The performance evaluation of the controllers is accomplished by means of two cost functions that are based on the quadratic forms of the energy input and deviation from a setpoint temperature, referred to as energy and comfort costs, respectively. The GA-F-PID controller is examined in two different forms, namely, global form and local form. For the global form, all possible combinations of fuzzy system characteristics in the search domain are explored by GA for finding the fittest chromosome for all discrete time intervals during the entire operation period. For the local form, however, GA is used in each discrete time interval to find the fittest chromosome for implementation. The results show that the global form GA-F-PID and local form GA-F-PID control methodologies, in comparison with PID controller, achieve higher energy efficiency by lowering energy costs by 51.2%, and 67.8%, respectively. Similarly, the comfort costs for deviation from setpoint are enhanced by 54.4%, and 62.4%, respectively. It is determined that GA-F-PID performs better in local from than global form.

  20. A VIRTUAL REALITY EXPOSURE THERAPY FOR PTSD PATIENTS CONTROLLED BY A FUZZY LOGIC SYSTEM

    Directory of Open Access Journals (Sweden)

    Rosa Maria Esteves Moreira da Costa

    2014-06-01

    Full Text Available This paper describes the main characteristics of two integrated systems that explore Virtual Reality technology and Fuzzy Logic to support and to control the assessment of people with Post-Traumatic Stress Disorder during the Virtual Reality Exposure Therapy. The integration of different technologies, the development methodology and the test procedures are described throughout the paper.

  1. A virtual reality exposure therapy for PTSD patients controlled by a fuzzy logic system

    OpenAIRE

    Oliveira, F. M.; Lanzillotti, R. S.; Da Costa, R. M. E. M.; Gonçalves, R.; Ventura, P.; Carvalho, L. A. V. de

    2014-01-01

    This paper describes the main characteristics of two integrated systems that explore Virtual Reality technology and Fuzzy Logic to support and to control the assessment of people with Post-Traumatic Stress Disorder during the Virtual Reality Exposure Therapy. The integration of different technologies, the development methodology and the test procedures are described throughout the paper. Peer Reviewed

  2. Designing High-Performance Fuzzy Controllers Combining IP Cores and Soft Processors

    Directory of Open Access Journals (Sweden)

    Oscar Montiel-Ross

    2012-01-01

    Full Text Available This paper presents a methodology to integrate a fuzzy coprocessor described in VHDL (VHSIC Hardware Description Language to a soft processor embedded into an FPGA, which increases the throughput of the whole system, since the controller uses parallelism at the circuitry level for high-speed-demanding applications, the rest of the application can be written in C/C++. We used the ARM 32-bit soft processor, which allows sequential and parallel programming. The FLC coprocessor incorporates a tuning method that allows to manipulate the system response. We show experimental results using a fuzzy PD+I controller as the embedded coprocessor.

  3. Linguistic fuzzy selection of liquid levelmeters in nuclear facilities

    International Nuclear Information System (INIS)

    Ghyym, S. H.

    1999-01-01

    In this work, a selection methodology of liquid levelmeters, especially, level sensors in non-nuclear category, to be installed in nuclear facilities is developed using a linguistic fuzzy approach. Depending on defuzzification techniques, the linguistic fuzzy methodology leads to either linguistic (exactly, fully-linguistic) or cardinal (i.e., semi-linguistic) evaluation. In the case of the linguistic method, for each alternative, fuzzy preference index is converted to linguistic utility value by means of a similarity measure determining the degree of similarity between fuzzy index and linguistic ratings. For the cardinal method, the index is translated to cardinal overall utility value. According to these values, alternatives of interest are linguistically or numerically evaluated and a suitable alternative can be selected. Under given selection criteria, the suitable selections out of some liquid levelmeters for nuclear facilities are dealt with using the linguistic fuzzy methodology proposed. Then, linguistic fuzzy evaluation results are compared with numerical results available in the literature. It is found that as to a suitable option the linguistic fuzzy selection is in agreement with the crisp numerical selection. In addition, this comparison shows that the fully-linguistic method facilitates linguistic interpretation regarding evaluation results

  4. Linguistic fuzzy selection of liquid levelmeters in nuclear facilities

    Energy Technology Data Exchange (ETDEWEB)

    Ghyym, S. H. [KEPRI, Taejon (Korea, Republic of)

    1999-10-01

    In this work, a selection methodology of liquid levelmeters, especially, level sensors in non-nuclear category, to be installed in nuclear facilities is developed using a linguistic fuzzy approach. Depending on defuzzification techniques, the linguistic fuzzy methodology leads to either linguistic (exactly, fully-linguistic) or cardinal (i.e., semi-linguistic) evaluation. In the case of the linguistic method, for each alternative, fuzzy preference index is converted to linguistic utility value by means of a similarity measure determining the degree of similarity between fuzzy index and linguistic ratings. For the cardinal method, the index is translated to cardinal overall utility value. According to these values, alternatives of interest are linguistically or numerically evaluated and a suitable alternative can be selected. Under given selection criteria, the suitable selections out of some liquid levelmeters for nuclear facilities are dealt with using the linguistic fuzzy methodology proposed. Then, linguistic fuzzy evaluation results are compared with numerical results available in the literature. It is found that as to a suitable option the linguistic fuzzy selection is in agreement with the crisp numerical selection. In addition, this comparison shows that the fully-linguistic method facilitates linguistic interpretation regarding evaluation results.

  5. Set-valued and fuzzy stochastic integral equations driven by semimartingales under Osgood condition

    Directory of Open Access Journals (Sweden)

    Malinowski Marek T.

    2015-01-01

    Full Text Available We analyze the set-valued stochastic integral equations driven by continuous semimartingales and prove the existence and uniqueness of solutions to such equations in the framework of the hyperspace of nonempty, bounded, convex and closed subsets of the Hilbert space L2 (consisting of square integrable random vectors. The coefficients of the equations are assumed to satisfy the Osgood type condition that is a generalization of the Lipschitz condition. Continuous dependence of solutions with respect to data of the equation is also presented. We consider equations driven by semimartingale Z and equations driven by processes A;M from decomposition of Z, where A is a process of finite variation and M is a local martingale. These equations are not equivalent. Finally, we show that the analysis of the set-valued stochastic integral equations can be extended to a case of fuzzy stochastic integral equations driven by semimartingales under Osgood type condition. To obtain our results we use the set-valued and fuzzy Maruyama type approximations and Bihari’s inequality.

  6. Efficient modeling of vector hysteresis using fuzzy inference systems

    International Nuclear Information System (INIS)

    Adly, A.A.; Abd-El-Hafiz, S.K.

    2008-01-01

    Vector hysteresis models have always been regarded as important tools to determine which multi-dimensional magnetic field-media interactions may be predicted. In the past, considerable efforts have been focused on mathematical modeling methodologies of vector hysteresis. This paper presents an efficient approach based upon fuzzy inference systems for modeling vector hysteresis. Computational efficiency of the proposed approach stems from the fact that the basic non-local memory Preisach-type hysteresis model is approximated by a local memory model. The proposed computational low-cost methodology can be easily integrated in field calculation packages involving massive multi-dimensional discretizations. Details of the modeling methodology and its experimental testing are presented

  7. Numerical simulation and analysis of fuzzy PID and PSD control methodologies as dynamic energy efficiency measures

    International Nuclear Information System (INIS)

    Ardehali, M.M.; Saboori, M.; Teshnelab, M.

    2004-01-01

    Energy efficiency enhancement is achieved by utilizing control algorithms that reduce overshoots and undershoots as well as unnecessary fluctuations in the amount of energy input to energy consuming systems during transient operation periods. It is hypothesized that application of control methodologies with characteristics that change with time and according to the system dynamics, identified as dynamic energy efficiency measures (DEEM), achieves the desired enhancement. The objective of this study is to simulate and analyze the effects of fuzzy logic based tuning of proportional integral derivative (F-PID) and proportional sum derivative (F-PSD) controllers for a heating and cooling energy system while accounting for the dynamics of the major system components. The procedure to achieve the objective includes utilization of fuzzy logic rules to determine the PID and PSD controllers gain coefficients so that the control laws for regulating the heat exchangers heating or cooling energy inputs are determined in each time step of the operation period. The performances of the F-PID and F-PSD controllers are measured by means of two cost functions that are based on quadratic forms of the energy input and deviation from a set point temperature. It is found that application of the F-PID control algorithm, as a DEEM, results in lower costs for energy input and deviation from a set point temperature by 24% and 17% as compared to a PID and 13% and 8% as compared to a PSD, respectively. It is also shown that the F-PSD performance is better than that of the F-PID controller

  8. A fuzzy logic based PROMETHEE method for material selection problems

    Directory of Open Access Journals (Sweden)

    Muhammet Gul

    2018-03-01

    Full Text Available Material selection is a complex problem in the design and development of products for diverse engineering applications. This paper presents a fuzzy PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation method based on trapezoidal fuzzy interval numbers that can be applied to the selection of materials for an automotive instrument panel. Also, it presents uniqueness in making a significant contribution to the literature in terms of the application of fuzzy decision-making approach to material selection problems. The method is illustrated, validated, and compared against three different fuzzy MCDM methods (fuzzy VIKOR, fuzzy TOPSIS, and fuzzy ELECTRE in terms of its ranking performance. Also, the relationships between the compared methods and the proposed scenarios for fuzzy PROMETHEE are evaluated via the Spearman’s correlation coefficient. Styrene Maleic Anhydride and Polypropylene are determined optionally as suitable materials for the automotive instrument panel case. We propose a generic fuzzy MCDM methodology that can be practically implemented to material selection problem. The main advantages of the methodology are consideration of the vagueness, uncertainty, and fuzziness to decision making environment.

  9. On the Difference between Traditional and Deductive Fuzzy Logic

    Czech Academy of Sciences Publication Activity Database

    Běhounek, Libor

    2008-01-01

    Roč. 159, č. 10 (2008), s. 1153-1164 ISSN 0165-0114 R&D Projects: GA AV ČR KJB100300502 Institutional research plan: CEZ:AV0Z10300504 Keywords : deductive fuzzy logic * fuzzy elements * gradual sets * entropy of fuzzy sets * aggregation * membership degrees * methodology of fuzzy mathematics Subject RIV: BA - General Mathematics Impact factor: 1.833, year: 2008

  10. Model predictive control using fuzzy decision functions

    NARCIS (Netherlands)

    Kaymak, U.; Costa Sousa, da J.M.

    2001-01-01

    Fuzzy predictive control integrates conventional model predictive control with techniques from fuzzy multicriteria decision making, translating the goals and the constraints to predictive control in a transparent way. The information regarding the (fuzzy) goals and the (fuzzy) constraints of the

  11. Recent Fuzzy Generalisations of Rough Sets Theory: A Systematic Review and Methodological Critique of the Literature

    Directory of Open Access Journals (Sweden)

    Abbas Mardani

    2017-01-01

    Full Text Available Rough set theory has been used extensively in fields of complexity, cognitive sciences, and artificial intelligence, especially in numerous fields such as expert systems, knowledge discovery, information system, inductive reasoning, intelligent systems, data mining, pattern recognition, decision-making, and machine learning. Rough sets models, which have been recently proposed, are developed applying the different fuzzy generalisations. Currently, there is not a systematic literature review and classification of these new generalisations about rough set models. Therefore, in this review study, the attempt is made to provide a comprehensive systematic review of methodologies and applications of recent generalisations discussed in the area of fuzzy-rough set theory. On this subject, the Web of Science database has been chosen to select the relevant papers. Accordingly, the systematic and meta-analysis approach, which is called “PRISMA,” has been proposed and the selected articles were classified based on the author and year of publication, author nationalities, application field, type of study, study category, study contribution, and journal in which the articles have appeared. Based on the results of this review, we found that there are many challenging issues related to the different application area of fuzzy-rough set theory which can motivate future research studies.

  12. Fuzzy systems for process identification and control

    International Nuclear Information System (INIS)

    Gorrini, V.; Bersini, H.

    1994-01-01

    Various issues related to the automatic construction and on-line adaptation of fuzzy controllers are addressed. A Direct Adaptive Fuzzy Control (this is an adaptive control methodology requiring a minimal knowledge of the processes to be coupled with) derived in a way reminiscent of neurocontrol methods, is presented. A classical fuzzy controller and a fuzzy realization of a PID controller is discussed. These systems implement a highly non-linear control law, and provide to be quite robust, even in the case of noisy inputs. In order to identify dynamic processes of order superior to one, we introduce a more complex architecture, called Recurrent Fuzzy System, that use some fuzzy internal variables to perform an inferential chaining.I

  13. An Extended Genetic Algorithm for Distributed Integration of Fuzzy Process Planning and Scheduling

    Directory of Open Access Journals (Sweden)

    Shuai Zhang

    2016-01-01

    Full Text Available The distributed integration of process planning and scheduling (DIPPS aims to simultaneously arrange the two most important manufacturing stages, process planning and scheduling, in a distributed manufacturing environment. Meanwhile, considering its advantage corresponding to actual situation, the triangle fuzzy number (TFN is adopted in DIPPS to represent the machine processing and transportation time. In order to solve this problem and obtain the optimal or near-optimal solution, an extended genetic algorithm (EGA with innovative three-class encoding method, improved crossover, and mutation strategies is proposed. Furthermore, a local enhancement strategy featuring machine replacement and order exchange is also added to strengthen the local search capability on the basic process of genetic algorithm. Through the verification of experiment, EGA achieves satisfactory results all in a very short period of time and demonstrates its powerful performance in dealing with the distributed integration of fuzzy process planning and scheduling (DIFPPS.

  14. Efficient solution of a multi objective fuzzy transportation problem

    Science.gov (United States)

    Vidhya, V.; Ganesan, K.

    2018-04-01

    In this paper we present a methodology for the solution of multi-objective fuzzy transportation problem when all the cost and time coefficients are trapezoidal fuzzy numbers and the supply and demand are crisp numbers. Using a new fuzzy arithmetic on parametric form of trapezoidal fuzzy numbers and a new ranking method all efficient solutions are obtained. The proposed method is illustrated with an example.

  15. Fuzzy production planning models for an unreliable production system with fuzzy production rate and stochastic/fuzzy demand rate

    Directory of Open Access Journals (Sweden)

    K. A. Halim

    2011-01-01

    Full Text Available In this article, we consider a single-unit unreliable production system which produces a single item. During a production run, the production process may shift from the in-control state to the out-of-control state at any random time when it produces some defective items. The defective item production rate is assumed to be imprecise and is characterized by a trapezoidal fuzzy number. The production rate is proportional to the demand rate where the proportionality constant is taken to be a fuzzy number. Two production planning models are developed on the basis of fuzzy and stochastic demand patterns. The expected cost per unit time in the fuzzy sense is derived in each model and defuzzified by using the graded mean integration representation method. Numerical examples are provided to illustrate the optimal results of the proposed fuzzy models.

  16. Prioritizing critical success factors for reverse logistics implementation using fuzzy-TOPSIS methodology

    Science.gov (United States)

    Agrawal, Saurabh; Singh, Rajesh K.; Murtaza, Qasim

    2016-03-01

    Electronics industry is one of the fastest growing industries in the world. In India also, there are high turnovers and growing demand of electronics product especially after post liberalization in early nineties. These products generate e-waste which has become big environmental issue. Industries can handle these e-waste and product returns efficiently by developing reverse logistics (RL) system. A thorough study of critical success factors (CSFs) and their ordered implementation is essential for successful RL implementation. The aim of the study is to review the CSFs, and to prioritize them for RL implementation in Indian electronics industry. Twelve CSFs were identified through literature review, and discussion with the experts from the Indian electronics industry. Fuzzy-Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach is proposed for prioritizing these CSFs. Perusal of literature indicates that fuzzy-TOPSIS has not been applied earlier for prioritization of CSFs in Indian electronics industry. Five Indian electronics companies were selected for evaluation of this methodology. Results indicate that most of the identified factors are crucial for the RL implementation. Top management awareness, resource management, economic factors, and contracts terms and conditions are top four prioritized factor, and process capabilities and skilled workers is the least prioritized factor. The findings will be useful for successful RL implementation in Indian electronics industry.

  17. Fuzzy logic applications to control engineering

    Science.gov (United States)

    Langari, Reza

    1993-12-01

    This paper presents the results of a project presently under way at Texas A&M which focuses on the use of fuzzy logic in integrated control of manufacturing systems. The specific problems investigated here include diagnosis of critical tool wear in machining of metals via a neuro-fuzzy algorithm, as well as compensation of friction in mechanical positioning systems via an adaptive fuzzy logic algorithm. The results indicate that fuzzy logic in conjunction with conventional algorithmic based approaches or neural nets can prove useful in dealing with the intricacies of control/monitoring of manufacturing systems and can potentially play an active role in multi-modal integrated control systems of the future.

  18. Fuzzy model-based control of a nuclear reactor

    International Nuclear Information System (INIS)

    Van Den Durpel, L.; Ruan, D.

    1994-01-01

    The fuzzy model-based control of a nuclear power reactor is an emerging research topic world-wide. SCK-CEN is dealing with this research in a preliminary stage, including two aspects, namely fuzzy control and fuzzy modelling. The aim is to combine both methodologies in contrast to conventional model-based PID control techniques, and to state advantages of including fuzzy parameters as safety and operator feedback. This paper summarizes the general scheme of this new research project

  19. Signal trend identification with fuzzy methods

    International Nuclear Information System (INIS)

    Reifman, J.; Tsoukalas, L. H.; Wang, X.; Wei, T. Y. C.

    1999-01-01

    A fuzzy-logic-based methodology for on-line signal trend identification is introduced. Although signal trend identification is complicated by the presence of noise, fuzzy logic can help capture important features of on-line signals and classify incoming power plant signals into increasing, decreasing and steady-state trend categories. In order to verify the methodology, a code named PROTREN is developed and tested using plant data. The results indicate that the code is capable of detecting transients accurately, identifying trends reliably, and not misinterpreting a steady-state signal as a transient one

  20. Landscape evaluation of heterogeneous areas using fuzzy sets

    Directory of Open Access Journals (Sweden)

    Ralf-Uwe Syrbe

    1998-02-01

    Full Text Available Landscape evaluation is an interesting field for fuzzy approaches, because it happens on the transition line between natural and social systems. Both are very complex. Therefore, transformation of scientific results to politically significant statements on environmental problems demands intelligent support. Particularly landscape planners need methods to gather natural facts of an area and assess them in consideration of its meaning to society as a whole. Since each land unit is heterogeneous, a special methodology is necessary. Such an evaluation technique was developed within a Geographical Information System (ARC/INFO. The methodology combines several known methods with fuzzy approaches to catch the intrinsic fuzziness of ecological systems as well as the heterogeneity of landscape. Additionally, a way will be discussed to vary the fuzzy inference in order to consider spatial relations of various landscape elements. Fuzzy logic is used to process the data uncertainty, to simulate the vagueness of knowledge about ecological functionality, and to model the spatial structure of landscape. Fuzzy sets describe the attributes of thematically defined land units and their assessment results. In this way, the available information will be preserved in their full diversity. The fuzzy operations are executed by AML-programs (ARC/INFO Macro Language. With such a tight coupling, it is possible to use the geographical functions (neighbourhoods, distances, etc. of GIS within the fuzzy system directly.

  1. Frontiers of higher order fuzzy sets

    CERN Document Server

    Tahayori, Hooman

    2015-01-01

    Frontiers of Higher Order Fuzzy Sets, strives to improve the theoretical aspects of general and Interval Type-2 fuzzy sets and provides a unified representation theorem for higher order fuzzy sets. Moreover, the book elaborates on the concept of gradual elements and their integration with the higher order fuzzy sets. This book also introduces new frameworks for information granulation based on general T2FSs, IT2FSs, Gradual elements, Shadowed sets and rough sets. In particular, the properties and characteristics of the new proposed frameworks are studied. Such new frameworks are shown to be more capable to be exploited in real applications. Higher order fuzzy sets that are the result of the integration of general T2FSs, IT2FSs, gradual elements, shadowed sets and rough sets will be shown to be suitable to be applied in the fields of bioinformatics, business, management, ambient intelligence, medicine, cloud computing and smart grids. Presents new variations of fuzzy set frameworks and new areas of applicabili...

  2. Methodology based in the fuzzy logic for constructing the objective functions in optimization problems of nuclear fuel: application to the cells radial design

    International Nuclear Information System (INIS)

    Barragan M, A.M.; Martin del Campo M, C.; Palomera P, M.A.

    2005-01-01

    A methodology based on Fuzzy Logic for the construction of the objective function of the optimization problems of nuclear fuel is described. It was created an inference system that responds, in certain form, as a human expert when it has the task of qualifying different radial designs of fuel cells. Specifically it is detailed how an inference system based based on Fuzzy Logic that has five enter variables and one exit variable was built, which corresponds to the objective function for the radial design of a fuel cell for a BWR. The use of Fuzzy with Mat lab offered the visualization capacity of the exit variable in function of one or two enter variables at the same time. This allowed to build, in appropriate way, the combination of the inference rules and the membership functions of those diffuse sets used for each one of the enter variables. The obtained objective function was used in an optimization process based on Taboo search. The new methodology was proven for the design of a cell used in a fuel assemble of the Laguna Verde reactor obtaining excellent results. (Author)

  3. Fuzzy Evidence in Identification, Forecasting and Diagnosis

    CERN Document Server

    Rotshtein, Alexander P

    2012-01-01

    The purpose of this book is to present a methodology for designing and tuning fuzzy expert systems in order to identify nonlinear objects; that is, to build input-output models using expert and experimental information. The results of these identifications are used for direct and inverse fuzzy evidence in forecasting and diagnosis problem solving. The book is organised as follows: Chapter 1 presents the basic knowledge about fuzzy sets, genetic algorithms and neural nets necessary for a clear understanding of the rest of this book. Chapter 2 analyzes direct fuzzy inference based on fuzzy if-then rules. Chapter 3 is devoted to the tuning of fuzzy rules for direct inference using genetic algorithms and neural nets. Chapter 4 presents models and algorithms for extracting fuzzy rules from experimental data. Chapter 5 describes a method for solving fuzzy logic equations necessary for the inverse fuzzy inference in diagnostic systems. Chapters 6 and 7 are devoted to inverse fuzzy inference based on fu...

  4. Quantitative modeling of gene networks of biological systems using fuzzy Petri nets and fuzzy sets

    Directory of Open Access Journals (Sweden)

    Raed I. Hamed

    2018-01-01

    Full Text Available Quantitative demonstrating of organic frameworks has turned into an essential computational methodology in the configuration of novel and investigation of existing natural frameworks. Be that as it may, active information that portrays the framework's elements should be known keeping in mind the end goal to get pertinent results with the routine displaying strategies. This information is frequently robust or even difficult to get. Here, we exhibit a model of quantitative fuzzy rational demonstrating approach that can adapt to obscure motor information and hence deliver applicable results despite the fact that dynamic information is fragmented or just dubiously characterized. Besides, the methodology can be utilized as a part of the blend with the current cutting edge quantitative demonstrating strategies just in specific parts of the framework, i.e., where the data are absent. The contextual analysis of the methodology suggested in this paper is performed on the model of nine-quality genes. We propose a kind of FPN model in light of fuzzy sets to manage the quantitative modeling of biological systems. The tests of our model appear that the model is practical and entirely powerful for information impersonation and thinking of fuzzy expert frameworks.

  5. Foundations Of Fuzzy Control

    DEFF Research Database (Denmark)

    Jantzen, Jan

    The objective of this textbook is to acquire an understanding of the behaviour of fuzzy logic controllers. Under certain conditions a fuzzy controller is equivalent to a proportional-integral-derivative (PID) controller. Using that equivalence as a link, the book applies analysis methods from...... linear and nonlinear control theory. In the linear domain, PID tuning methods and stability analyses are transferred to linear fuzzy controllers. The Nyquist plot shows the robustness of different settings of the fuzzy gain parameters. As a result, a fuzzy controller is guaranteed to perform as well...... as any PID controller. In the nonlinear domain, the stability of four standard control surfaces is analysed by means of describing functions and Nyquist plots. The self-organizing controller (SOC) is shown to be a model reference adaptive controller. There is a possibility that a nonlinear fuzzy PID...

  6. Improved estimation of electricity demand function by integration of fuzzy system and data mining approach

    International Nuclear Information System (INIS)

    Azadeh, A.; Saberi, M.; Ghaderi, S.F.; Gitiforouz, A.; Ebrahimipour, V.

    2008-01-01

    This study presents an integrated fuzzy system, data mining and time series framework to estimate and predict electricity demand for seasonal and monthly changes in electricity consumption especially in developing countries such as China and Iran with non-stationary data. Furthermore, it is difficult to model uncertain behavior of energy consumption with only conventional fuzzy system or time series and the integrated algorithm could be an ideal substitute for such cases. To construct fuzzy systems, a rule base is needed. Because a rule base is not available, for the case of demand function, look up table which is one of the extracting rule methods is used to extract the rule base. This system is defined as FLT. Also, decision tree method which is a data mining approach is similarly utilized to extract the rule base. This system is defined as FDM. Preferred time series model is selected from linear (ARMA) and nonlinear model. For this, after selecting preferred ARMA model, McLeod-Li test is applied to determine nonlinearity condition. When, nonlinearity condition is satisfied, preferred nonlinear model is selected and compare with preferred ARMA model and finally one of this is selected as time series model. At last, ANOVA is used for selecting preferred model from fuzzy models and time series model. Also, the impact of data preprocessing and postprocessing on the fuzzy system performance is considered by the algorithm. In addition, another unique feature of the proposed algorithm is utilization of autocorrelation function (ACF) to define input variables, whereas conventional methods which use trial and error method. Monthly electricity consumption of Iran from 1995 to 2005 is considered as the case of this study. The MAPE estimation of genetic algorithm (GA), artificial neural network (ANN) versus the proposed algorithm shows the appropriateness of the proposed algorithm

  7. A Fuzzy Logic Framework for Integrating Multiple Learned Models

    Energy Technology Data Exchange (ETDEWEB)

    Hartog, Bobi Kai Den [Univ. of Nebraska, Lincoln, NE (United States)

    1999-03-01

    The Artificial Intelligence field of Integrating Multiple Learned Models (IMLM) explores ways to combine results from sets of trained programs. Aroclor Interpretation is an ill-conditioned problem in which trained programs must operate in scenarios outside their training ranges because it is intractable to train them completely. Consequently, they fail in ways related to the scenarios. We developed a general-purpose IMLM solution, the Combiner, and applied it to Aroclor Interpretation. The Combiner's first step, Scenario Identification (M), learns rules from very sparse, synthetic training data consisting of results from a suite of trained programs called Methods. S1 produces fuzzy belief weights for each scenario by approximately matching the rules. The Combiner's second step, Aroclor Presence Detection (AP), classifies each of three Aroclors as present or absent in a sample. The third step, Aroclor Quantification (AQ), produces quantitative values for the concentration of each Aroclor in a sample. AP and AQ use automatically learned empirical biases for each of the Methods in each scenario. Through fuzzy logic, AP and AQ combine scenario weights, automatically learned biases for each of the Methods in each scenario, and Methods' results to determine results for a sample.

  8. An integrated fuzzy regression algorithm for energy consumption estimation with non-stationary data: A case study of Iran

    Energy Technology Data Exchange (ETDEWEB)

    Azadeh, A; Seraj, O [Department of Industrial Engineering and Research Institute of Energy Management and Planning, Center of Excellence for Intelligent-Based Experimental Mechanics, College of Engineering, University of Tehran, P.O. Box 11365-4563 (Iran); Saberi, M [Department of Industrial Engineering, University of Tafresh (Iran); Institute for Digital Ecosystems and Business Intelligence, Curtin University of Technology, Perth (Australia)

    2010-06-15

    This study presents an integrated fuzzy regression and time series framework to estimate and predict electricity demand for seasonal and monthly changes in electricity consumption especially in developing countries such as China and Iran with non-stationary data. Furthermore, it is difficult to model uncertain behavior of energy consumption with only conventional fuzzy regression (FR) or time series and the integrated algorithm could be an ideal substitute for such cases. At First, preferred Time series model is selected from linear or nonlinear models. For this, after selecting preferred Auto Regression Moving Average (ARMA) model, Mcleod-Li test is applied to determine nonlinearity condition. When, nonlinearity condition is satisfied, the preferred nonlinear model is selected and defined as preferred time series model. At last, the preferred model from fuzzy regression and time series model is selected by the Granger-Newbold. Also, the impact of data preprocessing on the fuzzy regression performance is considered. Monthly electricity consumption of Iran from March 1994 to January 2005 is considered as the case of this study. The superiority of the proposed algorithm is shown by comparing its results with other intelligent tools such as Genetic Algorithm (GA) and Artificial Neural Network (ANN). (author)

  9. Three dimensional fuzzy influence analysis of fitting algorithms on integrated chip topographic modeling

    International Nuclear Information System (INIS)

    Liang, Zhong Wei; Wang, Yi Jun; Ye, Bang Yan; Brauwer, Richard Kars

    2012-01-01

    In inspecting the detailed performance results of surface precision modeling in different external parameter conditions, the integrated chip surfaces should be evaluated and assessed during topographic spatial modeling processes. The application of surface fitting algorithms exerts a considerable influence on topographic mathematical features. The influence mechanisms caused by different surface fitting algorithms on the integrated chip surface facilitate the quantitative analysis of different external parameter conditions. By extracting the coordinate information from the selected physical control points and using a set of precise spatial coordinate measuring apparatus, several typical surface fitting algorithms are used for constructing micro topographic models with the obtained point cloud. In computing for the newly proposed mathematical features on surface models, we construct the fuzzy evaluating data sequence and present a new three dimensional fuzzy quantitative evaluating method. Through this method, the value variation tendencies of topographic features can be clearly quantified. The fuzzy influence discipline among different surface fitting algorithms, topography spatial features, and the external science parameter conditions can be analyzed quantitatively and in detail. In addition, quantitative analysis can provide final conclusions on the inherent influence mechanism and internal mathematical relation in the performance results of different surface fitting algorithms, topographic spatial features, and their scientific parameter conditions in the case of surface micro modeling. The performance inspection of surface precision modeling will be facilitated and optimized as a new research idea for micro-surface reconstruction that will be monitored in a modeling process

  10. Three dimensional fuzzy influence analysis of fitting algorithms on integrated chip topographic modeling

    Energy Technology Data Exchange (ETDEWEB)

    Liang, Zhong Wei; Wang, Yi Jun [Guangzhou Univ., Guangzhou (China); Ye, Bang Yan [South China Univ. of Technology, Guangzhou (China); Brauwer, Richard Kars [Indian Institute of Technology, Kanpur (India)

    2012-10-15

    In inspecting the detailed performance results of surface precision modeling in different external parameter conditions, the integrated chip surfaces should be evaluated and assessed during topographic spatial modeling processes. The application of surface fitting algorithms exerts a considerable influence on topographic mathematical features. The influence mechanisms caused by different surface fitting algorithms on the integrated chip surface facilitate the quantitative analysis of different external parameter conditions. By extracting the coordinate information from the selected physical control points and using a set of precise spatial coordinate measuring apparatus, several typical surface fitting algorithms are used for constructing micro topographic models with the obtained point cloud. In computing for the newly proposed mathematical features on surface models, we construct the fuzzy evaluating data sequence and present a new three dimensional fuzzy quantitative evaluating method. Through this method, the value variation tendencies of topographic features can be clearly quantified. The fuzzy influence discipline among different surface fitting algorithms, topography spatial features, and the external science parameter conditions can be analyzed quantitatively and in detail. In addition, quantitative analysis can provide final conclusions on the inherent influence mechanism and internal mathematical relation in the performance results of different surface fitting algorithms, topographic spatial features, and their scientific parameter conditions in the case of surface micro modeling. The performance inspection of surface precision modeling will be facilitated and optimized as a new research idea for micro-surface reconstruction that will be monitored in a modeling process.

  11. Markowitz portfolio optimization model employing fuzzy measure

    Science.gov (United States)

    Ramli, Suhailywati; Jaaman, Saiful Hafizah

    2017-04-01

    Markowitz in 1952 introduced the mean-variance methodology for the portfolio selection problems. His pioneering research has shaped the portfolio risk-return model and become one of the most important research fields in modern finance. This paper extends the classical Markowitz's mean-variance portfolio selection model applying the fuzzy measure to determine the risk and return. In this paper, we apply the original mean-variance model as a benchmark, fuzzy mean-variance model with fuzzy return and the model with return are modeled by specific types of fuzzy number for comparison. The model with fuzzy approach gives better performance as compared to the mean-variance approach. The numerical examples are included to illustrate these models by employing Malaysian share market data.

  12. An integrative fuzzy Kansei engineering and Kano model for logistics services

    Science.gov (United States)

    Hartono, M.; Chuan, T. K.; Prayogo, D. N.; Santoso, A.

    2017-11-01

    Nowadays, customer emotional needs (known as Kansei) in product and especially in services become a major concern. One of the emerging services is the logistics services. In obtaining a global competitive advantage, logistics services should understand and satisfy their customer affective impressions (Kansei). How to capture, model and analyze the customer emotions has been well structured by Kansei Engineering, equipped with Kano model to strengthen its methodology. However, its methodology lacks of the dynamics of customer perception. More specifically, there is a criticism of perceived scores on user preferences, in both perceived service quality and Kansei response, whether they represent an exact numerical value. Thus, this paper is proposed to discuss an approach of fuzzy Kansei in logistics service experiences. A case study in IT-based logistics services involving 100 subjects has been conducted. Its findings including the service gaps accompanied with prioritized improvement initiatives are discussed.

  13. Integrated fuzzy analytic hierarchy process and VIKOR method in the prioritization of pavement maintenance activities

    Directory of Open Access Journals (Sweden)

    Peyman Babashamsi

    2016-03-01

    Full Text Available Maintenance activities and pavement rehabilitation require the allocation of massive finances. Yet due to budget shortfalls, stakeholders and decision-makers must prioritize projects in maintenance and rehabilitation. This article addresses the prioritization of pavement maintenance alternatives by integrating the fuzzy analytic hierarchy process (AHP with the VIKOR method (which stands for ‘VlseKriterijumska Optimizacija I Kompromisno Resenje,’ meaning multi-criteria optimization and compromise solution for the process of multi-criteria decision analysis (MCDA by considering various pavement network indices. The indices selected include the pavement condition index (PCI, traffic congestion, pavement width, improvement and maintenance costs, and the time required to operate. In order to determine the weights of the indices, the fuzzy AHP is used. Subsequently, the alternatives’ priorities are ranked according to the indices weighted with the VIKOR model. The choice of these two independent methods was motivated by the fact that integrating fuzzy AHP with the VIKOR model can assist decision makers with solving MCDA problems. The case study was conducted on a pavement network within the same particular region in Tehran; three main streets were chosen that have an empirically higher maintenance demand. The most significant factors were evaluated and the project with the highest priority was selected for urgent maintenance. By comparing the index values of the alternative priorities, Delavaran Blvd. was revealed to have higher priority over the other streets in terms of maintenance and rehabilitation activities. Keywords: Maintenance and rehabilitation prioritization, Fuzzy analysis hierarchy process, VIKOR model, Pavement condition index, Multi-criteria decision analysis

  14. New Applications of m-Polar Fuzzy Matroids

    Directory of Open Access Journals (Sweden)

    Musavarah Sarwar

    2017-12-01

    Full Text Available Mathematical modelling is an important aspect in apprehending discrete and continuous physical systems. Multipolar uncertainty in data and information incorporates a significant role in various abstract and applied mathematical modelling and decision analysis. Graphical and algebraic models can be studied more precisely when multiple linguistic properties are dealt with, emphasizing the need for a multi-index, multi-object, multi-agent, multi-attribute and multi-polar mathematical approach. An m-polar fuzzy set is introduced to overcome the limitations entailed in single-valued and two-valued uncertainty. Our aim in this research study is to apply the powerful methodology of m-polar fuzzy sets to generalize the theory of matroids. We introduce the notion of m-polar fuzzy matroids and investigate certain properties of various types of m-polar fuzzy matroids. Moreover, we apply the notion of the m-polar fuzzy matroid to graph theory and linear algebra. We present m-polar fuzzy circuits, closures of m-polar fuzzy matroids and put special emphasis on m-polar fuzzy rank functions. Finally, we also describe certain applications of m-polar fuzzy matroids in decision support systems, ordering of machines and network analysis.

  15. Development of Fuzzy Logic and Soft Computing Methodologies

    Science.gov (United States)

    Zadeh, L. A.; Yager, R.

    1999-01-01

    Our earlier research on computing with words (CW) has led to a new direction in fuzzy logic which points to a major enlargement of the role of natural languages in information processing, decision analysis and control. This direction is based on the methodology of computing with words and embodies a new theory which is referred to as the computational theory of perceptions (CTP). An important feature of this theory is that it can be added to any existing theory - especially to probability theory, decision analysis, and control - and enhance the ability of the theory to deal with real-world problems in which the decision-relevant information is a mixture of measurements and perceptions. The new direction is centered on an old concept - the concept of a perception - a concept which plays a central role in human cognition. The ability to reason with perceptions perceptions of time, distance, force, direction, shape, intent, likelihood, truth and other attributes of physical and mental objects - underlies the remarkable human capability to perform a wide variety of physical and mental tasks without any measurements and any computations. Everyday examples of such tasks are parking a car, driving in city traffic, cooking a meal, playing golf and summarizing a story. Perceptions are intrinsically imprecise. Imprecision of perceptions reflects the finite ability of sensory organs and ultimately, the brain, to resolve detail and store information. More concretely, perceptions are both fuzzy and granular, or, for short, f-granular. Perceptions are f-granular in the sense that: (a) the boundaries of perceived classes are not sharply defined; and (b) the elements of classes are grouped into granules, with a granule being a clump of elements drawn together by indistinguishability, similarity. proximity or functionality. F-granularity of perceptions may be viewed as a human way of achieving data compression. In large measure, scientific progress has been, and continues to be

  16. A hybrid design methodology for structuring an Integrated Environmental Management System (IEMS) for shipping business.

    Science.gov (United States)

    Celik, Metin

    2009-03-01

    The International Safety Management (ISM) Code defines a broad framework for the safe management and operation of merchant ships, maintaining high standards of safety and environmental protection. On the other hand, ISO 14001:2004 provides a generic, worldwide environmental management standard that has been utilized by several industries. Both the ISM Code and ISO 14001:2004 have the practical goal of establishing a sustainable Integrated Environmental Management System (IEMS) for shipping businesses. This paper presents a hybrid design methodology that shows how requirements from both standards can be combined into a single execution scheme. Specifically, the Analytic Hierarchy Process (AHP) and Fuzzy Axiomatic Design (FAD) are used to structure an IEMS for ship management companies. This research provides decision aid to maritime executives in order to enhance the environmental performance in the shipping industry.

  17. A NEW APPROACH ON SHORTEST PATH IN FUZZY ENVIRONMENT

    OpenAIRE

    A. Nagoorgani; A. Mumtaj Begam

    2010-01-01

    This paper introduces a new type of fuzzy shortest path network problem using triangular fuzzy number. To find the smallest edge by the fuzzy distance using graded mean integration representation of generalized fuzzy number for every node. Thus the optimum shortest path for the given problem is obtained.

  18. EVALUATION OF THE GRAI INTEGRATED METHODOLOGY AND THE IMAGIM SUPPORTWARE

    Directory of Open Access Journals (Sweden)

    J.M.C. Reid

    2012-01-01

    Full Text Available This paper describes the GRAI Integrated Methodology and identifies the need for computer tools to support enterprise modelling,design and integration. The IMAGIM tool is then evaluated in terms of its ability to support the GRAI Integrated Methodology. The GRAI Integrated Methodology is an Enterprise Integration methodology developed to support the design of CIM systems . The GRAI Integrated Methodology consists of the GRAI model and a structured approach. The latest addition to the methodology is the IMAGIM software tool developed by the GRAI research group for the specific purpose of supporting the methodology.

  19. Design of supply chain in fuzzy environment

    Science.gov (United States)

    Rao, Kandukuri Narayana; Subbaiah, Kambagowni Venkata; Singh, Ganja Veera Pratap

    2013-05-01

    Nowadays, customer expectations are increasing and organizations are prone to operate in an uncertain environment. Under this uncertain environment, the ultimate success of the firm depends on its ability to integrate business processes among supply chain partners. Supply chain management emphasizes cross-functional links to improve the competitive strategy of organizations. Now, companies are moving from decoupled decision processes towards more integrated design and control of their components to achieve the strategic fit. In this paper, a new approach is developed to design a multi-echelon, multi-facility, and multi-product supply chain in fuzzy environment. In fuzzy environment, mixed integer programming problem is formulated through fuzzy goal programming in strategic level with supply chain cost and volume flexibility as fuzzy goals. These fuzzy goals are aggregated using minimum operator. In tactical level, continuous review policy for controlling raw material inventories in supplier echelon and controlling finished product inventories in plant as well as distribution center echelon is considered as fuzzy goals. A non-linear programming model is formulated through fuzzy goal programming using minimum operator in the tactical level. The proposed approach is illustrated with a numerical example.

  20. Model for qualitative evaluation of risk in ducts through the fuzzy logic in conformity with the methodology of IBR; Modelo para avaliacao qualitativa do risco em oleodutos atraves da logica fuzzy segundo a metodologia da IBR

    Energy Technology Data Exchange (ETDEWEB)

    Mishina, Koje Daniel Vasconcelos [Centro Federal de Educacao Tecnologica da Bahia (CEFET-BA), Salvador, BA (Brazil); Silva, Jose Felicio da; Silva, Joao Bosco de Aquino [Universidade Federal da Paraiba (UFPb), Joao Pessoa, PB (Brazil)

    2006-07-01

    This work considers a system for qualitative evaluation of the terrestrial risk in pipelines, based in the methodology of the Inspection Based on Risk and the Fuzzy Logic. For this one developed a matrix of risk associated with the oil transport and its derivatives, that define the type of tracking and the regularity of inspection with Pig Instrumented in function of the level of risk found in the stretch in study. This matrix of risk considers the probabilities and the consequences associates to the damage for corrosion. The evaluation of the considered system was based on the consistency of the found levels of risk, in relation to that it would be found in the practical one. The gotten results had demonstrated that the use of the methodology of the IBR and the Fuzzy Logic can be used jointly as one sufficiently efficient alternative technique in the evaluation of risk in corroded pipe-lines. (author)

  1. Fuzzy stability and synchronization of hyperchaos systems

    International Nuclear Information System (INIS)

    Wang Junwei; Xiong Xiaohua; Zhao Meichun; Zhang Yanbin

    2008-01-01

    This paper studies stability and synchronization of hyperchaos systems via a fuzzy-model-based control design methodology. First, we utilize a Takagi-Sugeno fuzzy model to represent a hyperchaos system. Second, we design fuzzy-model-based controllers for stability and synchronization of the system, based on so-called 'parallel distributed compensation (PDC)'. Third, we reduce a question of stabilizing and synchronizing hyperchaos systems to linear matrix inequalities (LMI) so that convex programming techniques can solve these LMIs efficiently. Finally, the generalized Lorenz hyperchaos system is employed to illustrate the effectiveness of our designing controller

  2. An integrated supply chain model for the perishable items with fuzzy production rate and fuzzy demand rate

    Directory of Open Access Journals (Sweden)

    Singh Chaman

    2011-01-01

    Full Text Available In the changing market scenario, supply chain management is getting phenomenal importance amongst researchers. Studies on supply chain management have emphasized the importance of a long-term strategic relationship between the manufacturer, distributor and retailer. In the present paper, a model has been developed by assuming that the demand rate and production rate as triangular fuzzy numbers and items deteriorate at a constant rate. The expressions for the average inventory cost are obtained both in crisp and fuzzy sense. The fuzzy model is defuzzified using the fuzzy extension principle, and its optimization with respect to the decision variable is also carried out. Finally, an example is given to illustrate the model and sensitivity analysis is performed to study the effect of parameters.

  3. Flood Hazard Mapping by Applying Fuzzy TOPSIS Method

    Science.gov (United States)

    Han, K. Y.; Lee, J. Y.; Keum, H.; Kim, B. J.; Kim, T. H.

    2017-12-01

    There are lots of technical methods to integrate various factors for flood hazard mapping. The purpose of this study is to suggest the methodology of integrated flood hazard mapping using MCDM(Multi Criteria Decision Making). MCDM problems involve a set of alternatives that are evaluated on the basis of conflicting and incommensurate criteria. In this study, to apply MCDM to assessing flood risk, maximum flood depth, maximum velocity, and maximum travel time are considered as criterion, and each applied elements are considered as alternatives. The scheme to find the efficient alternative closest to a ideal value is appropriate way to assess flood risk of a lot of element units(alternatives) based on various flood indices. Therefore, TOPSIS which is most commonly used MCDM scheme is adopted to create flood hazard map. The indices for flood hazard mapping(maximum flood depth, maximum velocity, and maximum travel time) have uncertainty concerning simulation results due to various values according to flood scenario and topographical condition. These kind of ambiguity of indices can cause uncertainty of flood hazard map. To consider ambiguity and uncertainty of criterion, fuzzy logic is introduced which is able to handle ambiguous expression. In this paper, we made Flood Hazard Map according to levee breach overflow using the Fuzzy TOPSIS Technique. We confirmed the areas where the highest grade of hazard was recorded through the drawn-up integrated flood hazard map, and then produced flood hazard map can be compared them with those indicated in the existing flood risk maps. Also, we expect that if we can apply the flood hazard map methodology suggested in this paper even to manufacturing the current flood risk maps, we will be able to make a new flood hazard map to even consider the priorities for hazard areas, including more varied and important information than ever before. Keywords : Flood hazard map; levee break analysis; 2D analysis; MCDM; Fuzzy TOPSIS

  4. Determination of the Main Influencing Factors on Road Fatalities Using an Integrated Neuro-Fuzzy Algorithm

    Directory of Open Access Journals (Sweden)

    Amir Masoud Rahimi

    Full Text Available Abstract This paper proposed an integrated algorithm of neuro-fuzzy techniques to examine the complex impact of socio-technical influencing factors on road fatalities. The proposed algorithm could handle complexity, non-linearity and fuzziness in the modeling environment due to its mechanism. The Neuro-fuzzy algorithm for determination of the potential influencing factors on road fatalities consisted of two phases. In the first phase, intelligent techniques are compared for their improved accuracy in predicting fatality rate with respect to some socio-technical influencing factors. Then in the second phase, sensitivity analysis is performed to calculate the pure effect on fatality rate of the potential influencing factors. The applicability and usefulness of the proposed algorithm is illustrated using the data in Iran provincial road transportation systems in the time period 2012-2014. Results show that road design improvement, number of trips, and number of passengers are the most influencing factors on provincial road fatality rate.

  5. Fuzzy associative memories for instrument fault detection

    International Nuclear Information System (INIS)

    Heger, A.S.

    1996-01-01

    A fuzzy logic instrument fault detection scheme is developed for systems having two or three redundant sensors. In the fuzzy logic approach the deviation between each signal pairing is computed and classified into three fuzzy sets. A rule base is created allowing the human perception of the situation to be represented mathematically. Fuzzy associative memories are then applied. Finally, a defuzzification scheme is used to find the centroid location, and hence the signal status. Real-time analyses are carried out to evaluate the instantaneous signal status as well as the long-term results for the sensor set. Instantaneous signal validation results are used to compute a best estimate for the measured state variable. The long-term sensor validation method uses a frequency fuzzy variable to determine the signal condition over a specific period. To corroborate the methodology synthetic data representing various anomalies are analyzed with both the fuzzy logic technique and the parity space approach. (Author)

  6. Fuzzy Multi-objective Linear Programming Approach

    Directory of Open Access Journals (Sweden)

    Amna Rehmat

    2007-07-01

    Full Text Available Traveling salesman problem (TSP is one of the challenging real-life problems, attracting researchers of many fields including Artificial Intelligence, Operations Research, and Algorithm Design and Analysis. The problem has been well studied till now under different headings and has been solved with different approaches including genetic algorithms and linear programming. Conventional linear programming is designed to deal with crisp parameters, but information about real life systems is often available in the form of vague descriptions. Fuzzy methods are designed to handle vague terms, and are most suited to finding optimal solutions to problems with vague parameters. Fuzzy multi-objective linear programming, an amalgamation of fuzzy logic and multi-objective linear programming, deals with flexible aspiration levels or goals and fuzzy constraints with acceptable deviations. In this paper, a methodology, for solving a TSP with imprecise parameters, is deployed using fuzzy multi-objective linear programming. An example of TSP with multiple objectives and vague parameters is discussed.

  7. Hybridizing fuzzy control and timed automata for modeling variable structure fuzzy systems

    NARCIS (Netherlands)

    Acampora, G.; Loia, V.; Vitiello, A.

    2010-01-01

    During the past several years, fuzzy control has emerged as one of the most suitable and efficient methods for designing and developing complex systems in environments characterized by high level of uncertainty and imprecision. Nowadays, this methodology is used to model systems in several

  8. Optimization of Urban Highway Bypass Horizontal Alignment: A Methodological Overview of Intelligent Spatial MCDA Approach Using Fuzzy AHP and GIS

    Directory of Open Access Journals (Sweden)

    Yashon O. Ouma

    2014-01-01

    Full Text Available Selection of urban bypass highway alternatives involves the consideration of competing and conflicting criteria and factors, which require multicriteria decision analysis. Analytic hierarchy process (AHP is one of the most commonly used multicriteria decision making (MCDM methods that can integrate personal preferences in performing spatial analyses on the physical and nonphysical parameters. In this paper, the traditional AHP is modified to fuzzy AHP for the determination of the optimal bypass route for Eldoret town in Kenya. The fuzzy AHP is proposed in order to take care of the vagueness type uncertainty encountered in alternative bypass location determination. In the implementation, both engineering and environmental factors comprising of physical and socioeconomic objectives were considered at different levels of decision hierarchy. The results showed that the physical objectives (elevation, slope, soils, geology, and drainage networks and socioeconomic objectives (land-use and road networks contributed the same weight of 0.5 towards the bypass location prioritization process. At the subcriteria evaluation level, land-use and existing road networks contributed the highest significance of 47.3% amongst the seven decision factors. Integrated with GIS-based least cost path (LCP analysis, the fuzzy AHP results produced the most desirable and optimal route alignment, as compared to the AHP only prioritization approach.

  9. Decomposition of fuzzy continuity and fuzzy ideal continuity via fuzzy idealization

    International Nuclear Information System (INIS)

    Zahran, A.M.; Abbas, S.E.; Abd El-baki, S.A.; Saber, Y.M.

    2009-01-01

    Recently, El-Naschie has shown that the notion of fuzzy topology may be relevant to quantum paretical physics in connection with string theory and E-infinity space time theory. In this paper, we study the concepts of r-fuzzy semi-I-open, r-fuzzy pre-I-open, r-fuzzy α-I-open and r-fuzzy β-I-open sets, which is properly placed between r-fuzzy openness and r-fuzzy α-I-openness (r-fuzzy pre-I-openness) sets regardless the fuzzy ideal topological space in Sostak sense. Moreover, we give a decomposition of fuzzy continuity, fuzzy ideal continuity and fuzzy ideal α-continuity, and obtain several characterization and some properties of these functions. Also, we investigate their relationship with other types of function.

  10. Assessment of land suitability for olive mill wastewater disposal site selection by integrating fuzzy logic, AHP, and WLC in a GIS.

    Science.gov (United States)

    Aydi, Abdelwaheb; Abichou, Tarek; Nasr, Imen Hamdi; Louati, Mourad; Zairi, Moncef

    2016-01-01

    This paper presents a geographic information system-based multi-criteria site selection tool of an olive mill wastewater (OMW) disposal site in Sidi Bouzid Region, Tunisia. The multi-criteria decision framework integrates ten constraints and six factors that relate to environmental and economic concerns, and builds a hierarchy model for OMW disposal site suitability. The methodology is used for preliminary assessment of the most suitable OMW disposal sites by combining fuzzy set theory and analytic hierarchy process (AHP). The fuzzy set theory is used to standardize factors using different fuzzy membership functions while the AHP is used to establish the relative importance of the criteria. The AHP makes pairwise comparisons of relative importance between hierarchy elements grouped by both environmental and economic decision criteria. The OMW disposal site suitability is achieved by applying a weighted linear combination that uses a comparison matrix to aggregate different importance scenarios associated with environmental and economic objectives. Three different scenarios generated by different weights applied to the two objectives. The scenario (a) assigns a weight of 0.75 to the environmental and 0.25 to the economic objective, scenario (b) has equal weights, and scenario (c) features weights of 0.25 and 0.75 for environmental and economic objectives, respectively. The results from this study assign the least suitable OMW disposal site of 2.5 % when environmental and economic objectives are rated equally, while a more suitable OMW disposal site of 1.0 % is generated when the economic objective is rated higher.

  11. Lyapunov Based-Distributed Fuzzy-Sliding Mode Control for Building Integrated-DC Microgrid with Plug-in Electric Vehicle

    DEFF Research Database (Denmark)

    Ghiasi, Mohammad Iman; Aliakbar Golkar, Masoud; Hajizadeh, Amin

    2017-01-01

    This paper presents a distributed control strategy based on Fuzzy-Sliding Mode Control (FSMC) for power control of an infrastructure integrated with a DC-Microgrid, which includes photovoltaic, fuel cell and energy storage systems with Plug-in Electric Vehicles (PEVs). In order to implement...... the proposed control strategy, first a general nonlinear modeling of a DC-Microgrid based on related DC-DC converters to each DC power sources is introduced. Secondly, a power management strategy based on fuzzy control for regulating the power flow between the hybrid DC sources, PEVs is proposed. Third...

  12. Expected value analysis for integrated supplier selection and inventory control of multi-product inventory system with fuzzy cost

    Science.gov (United States)

    Sutrisno, Widowati, Tjahjana, R. Heru

    2017-12-01

    The future cost in many industrial problem is obviously uncertain. Then a mathematical analysis for a problem with uncertain cost is needed. In this article, we deals with the fuzzy expected value analysis to solve an integrated supplier selection and supplier selection problem with uncertain cost where the costs uncertainty is approached by a fuzzy variable. We formulate the mathematical model of the problems fuzzy expected value based quadratic optimization with total cost objective function and solve it by using expected value based fuzzy programming. From the numerical examples result performed by the authors, the supplier selection problem was solved i.e. the optimal supplier was selected for each time period where the optimal product volume of all product that should be purchased from each supplier for each time period was determined and the product stock level was controlled as decided by the authors i.e. it was followed the given reference level.

  13. Expert system driven fuzzy control application to power reactors

    International Nuclear Information System (INIS)

    Tsoukalas, L.H.; Berkan, R.C.; Upadhyaya, B.R.; Uhrig, R.E.

    1990-01-01

    For the purpose of nonlinear control and uncertainty/imprecision handling, fuzzy controllers have recently reached acclaim and increasing commercial application. The fuzzy control algorithms often require a ''supervisory'' routine that provides necessary heuristics for interface, adaptation, mode selection and other implementation issues. Performance characteristics of an on-line fuzzy controller depend strictly on the ability of such supervisory routines to manipulate the fuzzy control algorithm and enhance its control capabilities. This paper describes an expert system driven fuzzy control design application to nuclear reactor control, for the automated start-up control of the Experimental Breeder Reactor-II. The methodology is verified through computer simulations using a valid nonlinear model. The necessary heuristic decisions are identified that are vitally important for the implemention of fuzzy control in the actual plant. An expert system structure incorporating the necessary supervisory routines is discussed. The discussion also includes the possibility of synthesizing the fuzzy, exact and combined reasoning to include both inexact concepts, uncertainty and fuzziness, within the same environment

  14. A Quality-Driven Methodology for Information Systems Integration

    Directory of Open Access Journals (Sweden)

    Iyad Zikra

    2017-10-01

    Full Text Available Information systems integration is an essential instrument for organizations to attain advantage in today’s growing and fast changing business and technology landscapes. Integration solutions generate added value by combining the functionality and services of heterogeneous and diverse systems. Existing integration environments tend to rely heavily on technical, platform-dependent skills. Consequently, the solutions that they enable are not optimally aligned with the envisioned business goals of the organization. Furthermore, the gap between the goals and the solutions complicates the task of evaluating the quality of integration solutions. To address these challenges, we propose a quality-driven, model-driven methodology for designing and developing integration solutions. The methodology spans organizational and systems design details, providing a holistic view of the integration solution and its underlying business goals. A multi-view meta-model provides the basis for the integration design. Quality factors that affect various aspects of the integration solution guide and inform the progress of the methodology. An example business case is presented to demonstrate the application of the methodology.

  15. Fuzzy vulnerability matrix

    International Nuclear Information System (INIS)

    Baron, Jorge H.; Rivera, S.S.

    2000-01-01

    The so-called vulnerability matrix is used in the evaluation part of the probabilistic safety assessment for a nuclear power plant, during the containment event trees calculations. This matrix is established from what is knows as Numerical Categories for Engineering Judgement. This matrix is usually established with numerical values obtained with traditional arithmetic using the set theory. The representation of this matrix with fuzzy numbers is much more adequate, due to the fact that the Numerical Categories for Engineering Judgement are better represented with linguistic variables, such as 'highly probable', 'probable', 'impossible', etc. In the present paper a methodology to obtain a Fuzzy Vulnerability Matrix is presented, starting from the recommendations on the Numerical Categories for Engineering Judgement. (author)

  16. Nursing and fuzzy logic: an integrative review Enfermería y lógica fuzzy: una revisión de integradora Enfermagem e lógica fuzzy: uma revisão integrativa

    Directory of Open Access Journals (Sweden)

    Rodrigo Jensen

    2011-02-01

    Full Text Available This study conducted an integrative review investigating how fuzzy logic has been used in research with the participation of nurses. The article search was carried out in the CINAHL, EMBASE, SCOPUS, PubMed and Medline databases, with no limitation on time of publication. Articles written in Portuguese, English and Spanish with themes related to nursing and fuzzy logic with the authorship or participation of nurses were included. The final sample included 21 articles from eight countries. For the purpose of analysis, the articles were distributed into categories: theory, method and model. In nursing, fuzzy logic has significantly contributed to the understanding of subjects related to: imprecision or the need of an expert; as a research method; and in the development of models or decision support systems and hard technologies. The use of fuzzy logic in nursing has shown great potential and represents a vast field for research.Este estudio tuvo como objetivo realizar una revisión integradora investigando como la lógica fuzzy ha sido utilizada en investigaciones con participación de enfermeros. La búsqueda de los artículos fue realizada en las bases de datos CINAHL, Embase, SCOPUS, Medline y PubMed, sin especificar un intervalo de años determinado. Fueron incluidos artículos en los idiomas: portugués, inglés y castellano; con una temática relacionada a la enfermería y a la lógica fuzzy; y con autoría o participación de enfermeros. La muestra final fue de 21 artículos, de ocho países. Para el análisis, los artículos fueron distribuidos en las categorías: teoría, método y modelo. En la enfermería, la lógica fuzzy ha contribuido significativamente para la comprensión de temas relativos a la imprecisión o a la necesidad del especialista, como método de investigación y en el desarrollo de modelos o sistemas de apoyo a la decisión y de tecnologías duras. El uso de la lógica fuzzy en la enfermería ha demostrado gran

  17. An approach to solve replacement problems under intuitionistic fuzzy nature

    Science.gov (United States)

    Balaganesan, M.; Ganesan, K.

    2018-04-01

    Due to impreciseness to solve the day to day problems the researchers use fuzzy sets in their discussions of the replacement problems. The aim of this paper is to solve the replacement theory problems with triangular intuitionistic fuzzy numbers. An effective methodology based on fuzziness index and location index is proposed to determine the optimal solution of the replacement problem. A numerical example is illustrated to validate the proposed method.

  18. Self tuning fuzzy PID type load and frequency controller

    International Nuclear Information System (INIS)

    Yesil, E.; Guezelkaya, M.; Eksin, I.

    2004-01-01

    In this paper, a self tuning fuzzy PID type controller is proposed for solving the load frequency control (LFC) problem. The fuzzy PID type controller is constructed as a set of control rules, and the control signal is directly deduced from the knowledge base and the fuzzy inference. Moreover, there exists a self tuning mechanism that adjusts the input scaling factor corresponding to the derivative coefficient and the output scaling factor corresponding to the integral coefficient of the PID type fuzzy logic controller in an on-line manner. The self tuning mechanism depends on the peak observer idea, and this idea is modified and adapted to the LFC problem. A two area interconnected system is assumed for demonstrations. The proposed self tuning fuzzy PID type controller has been compared with the fuzzy PID type controller without a self tuning mechanism and the conventional integral controller through some performance indices

  19. Intelligent control-III: fuzzy control system

    International Nuclear Information System (INIS)

    Nagrial, M.H.

    2004-01-01

    During the last decade or so, fuzzy logic control (FLC) has emerged as one of the most active and fruitful areas of research and development. The applications include industrial process control to medical diagnostic and financial markets. Many consumer products using this technology are available in the market place. FLC is best suited to complex ill-defined processes that can be controlled by a skilled human operator without much knowledge of their underlying dynamics. This lecture will cover the basic architecture and the design methodology of fuzzy logic controllers. FLC will be strongly based on the concepts of fuzzy set theory, introduced in first lecture. Some practical applications will also be discussed and presented. (author)

  20. Simulation comparison of proportional integral derivative and fuzzy logic in controlling AC-DC buck boost converter

    Science.gov (United States)

    Faisal, A.; Hasan, S.; Suherman

    2018-03-01

    AC-DC converter is widely used in the commercial industry even for daily purposes. The AC-DC converter is used to convert AC voltage into DC. In order to obtain the desired output voltage, the converter usually has a controllable regulator. This paper discusses buck boost regulator with a power MOSFET as switching component which is adjusted based on the duty cycle of pulse width modulation (PWM). The main problems of the buck boost converter at start up are the high overshoot, the long peak time and rise time. This paper compares the effectiveness of two control techniques: proportional integral derivative (PID) and fuzzy logic control in controlling the buck boost converter through simulations. The results show that the PID is more sensitive to voltage change than fuzzy logic. However, PID generates higher overshoot, long peak time and rise time. On the other hand, fuzzy logic generates no overshoot and shorter rise time.

  1. [Research on fuzzy proportional-integral-derivative control of master-slave minimally invasive operation robot driver].

    Science.gov (United States)

    Zhao, Ximei; Ren, Chengyi; Liu, Hao; Li, Haogyi

    2014-12-01

    Robotic catheter minimally invasive operation requires that the driver control system has the advantages of quick response, strong anti-jamming and real-time tracking of target trajectory. Since the catheter parameters of itself and movement environment and other factors continuously change, when the driver is controlled using traditional proportional-integral-derivative (PID), the controller gain becomes fixed once the PID parameters are set. It can not change with the change of the parameters of the object and environmental disturbance so that its change affects the position tracking accuracy, and may bring a large overshoot endangering patients' vessel. Therefore, this paper adopts fuzzy PID control method to adjust PID gain parameters in the tracking process in order to improve the system anti-interference ability, dynamic performance and tracking accuracy. The simulation results showed that the fuzzy PID control method had a fast tracking performance and a strong robustness. Compared with those of traditional PID control, the feasibility and practicability of fuzzy PID control are verified in a robotic catheter minimally invasive operation.

  2. Fuzzy Multi-Criteria Evaluation of Knowledge Management Tools

    Directory of Open Access Journals (Sweden)

    2011-04-01

    enhanced multi-criteria method, namely fuzzy VIKOR, that takes advantages of fuzzy logic and group decision making to deal with the vagueness and granularity in the linguistic assessments. The method aims to isolate compromise solutions, by providing a maximum group utility and a minimum of an individual regret. A case study is also given to demonstrate the potential of the methodology.

  3. A multi-objective fuzzy mathematical approach for sustainable reverse supply chain configuration

    Directory of Open Access Journals (Sweden)

    Jyoti D. Darbari

    2017-03-01

    Full Text Available Background: Designing and implementation of reverse logistics (RL network which meets the sustainability targets have been a matter of emerging concern for the electronics companies in India. Objectives: The present study developed a two-phase model for configuration of sustainable RL network design for an Indian manufacturing company to manage its end-of-life and endof-use electronic products. The notable feature of the model was the evaluation of facilities under financial, environmental and social considerations and integration of the facility selection decisions with the network design. Method: In the first phase, an integrated Analytical Hierarchical Process Complex Proportional Assessment methodology was used for the evaluation of the alternative locations in terms of their degree of utility, which in turn was based on the three dimensions of sustainability. In the second phase, the RL network was configured as a bi-objective programming problem, and fuzzy optimisation approach was utilised for obtaining a properly efficient solution to the problem. Results: The compromised solution attained by the proposed fuzzy model demonstrated that the cost differential for choosing recovery facilities with better environmental and social performance was not significant; therefore, Indian manufacturers must not compromise on the sustainability aspects for facility location decisions. Conclusion: The results reaffirmed that the bi-objective fuzzy decision-making model can serve as a decision tool for the Indian manufacturers in designing a sustainable RL network. The multi-objective optimisation model captured a reasonable trade-off between the fuzzy goals of minimising the cost of the RL network and maximising the sustainable performance of the facilities chosen.

  4. A Fuzzy Adaptive Tightly-Coupled Integration Method for Mobile Target Localization Using SINS/WSN

    Directory of Open Access Journals (Sweden)

    Wei Li

    2016-11-01

    Full Text Available In recent years, mobile target localization for enclosed environments has been a growing interest. In this paper, we have proposed a fuzzy adaptive tightly-coupled integration (FATCI method for positioning and tracking applications using strapdown inertial navigation system (SINS and wireless sensor network (WSN. The wireless signal outage and severe multipath propagation of WSN often influence the accuracy of measured distance and lead to difficulties with the WSN positioning. Note also that the SINS are known for their drifted error over time. Using as a base the well-known loosely-coupled integration method, we have built a tightly-coupled integrated positioning system for SINS/WSN based on the measured distances between anchor nodes and mobile node. The measured distance value of WSN is corrected with a least squares regression (LSR algorithm, with the aim of decreasing the systematic error for measured distance. Additionally, the statistical covariance of measured distance value is used to adjust the observation covariance matrix of a Kalman filter using a fuzzy inference system (FIS, based on the statistical characteristics. Then the tightly-coupled integration model can adaptively adjust the confidence level for measurement according to the different measured accuracies of distance measurements. Hence the FATCI system is achieved using SINS/WSN. This innovative approach is verified in real scenarios. Experimental results show that the proposed positioning system has better accuracy and stability compared with the loosely-coupled and traditional tightly-coupled integration model for WSN short-term failure or normal conditions.

  5. Simulation of operating rules and discretional decisions using a fuzzy rule-based system integrated into a water resources management model

    Science.gov (United States)

    Macian-Sorribes, Hector; Pulido-Velazquez, Manuel

    2013-04-01

    water stored in the reservoirs) and the month of the year as inputs; and the demand deliveries as outputs. The developed simulation management model integrates the fuzzy-ruled system of the operation of the two main reservoirs of the basin with the corresponding mass balance equations, the physical or boundary conditions and the water allocation rules among the competing demands. Historical information on inflow time series is used as inputs to the model simulation, being trained and validated using historical information on reservoir storage level and flow in several streams of the Mijares river. This methodology provides a more flexible and close to real policies approach. The model is easy to develop and to understand due to its rule-based structure, which mimics the human way of thinking. This can improve cooperation and negotiation between managers, decision-makers and stakeholders. The approach can be also applied to analyze the historical operation of the reservoir (what we have called a reservoir operation "audit").

  6. An intelligent sales forecasting system through integration of artificial neural networks and fuzzy neural networks with fuzzy weight elimination.

    Science.gov (United States)

    Kuo, R J; Wu, P; Wang, C P

    2002-09-01

    Sales forecasting plays a very prominent role in business strategy. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average (ARMA). However, sales forecasting is very complicated owing to influence by internal and external environments. Recently, artificial neural networks (ANNs) have also been applied in sales forecasting since their promising performances in the areas of control and pattern recognition. However, further improvement is still necessary since unique circumstances, e.g. promotion, cause a sudden change in the sales pattern. Thus, this study utilizes a proposed fuzzy neural network (FNN), which is able to eliminate the unimportant weights, for the sake of learning fuzzy IF-THEN rules obtained from the marketing experts with respect to promotion. The result from FNN is further integrated with the time series data through an ANN. Both the simulated and real-world problem results show that FNN with weight elimination can have lower training error compared with the regular FNN. Besides, real-world problem results also indicate that the proposed estimation system outperforms the conventional statistical method and single ANN in accuracy.

  7. The Study of Fuzzy Proportional Integral Controllers Based on Improved Particle Swarm Optimization for Permanent Magnet Direct Drive Wind Turbine Converters

    Directory of Open Access Journals (Sweden)

    Yancai Xiao

    2016-05-01

    Full Text Available In order to meet the requirements of high precision and fast response of permanent magnet direct drive (PMDD wind turbines, this paper proposes a fuzzy proportional integral (PI controller associated with a new control strategy for wind turbine converters. The purpose of the control strategy is to achieve the global optimization for the quantization factors, ke and kec, and scale factors, kup and kui, of the fuzzy PI controller by an improved particle swarm optimization (PSO method. Thus the advantages of the rapidity of the improved PSO and the robustness of the fuzzy controller can be fully applied in the control process. By conducting simulations for 2 MW PMDD wind turbines with Matlab/Simulink, the performance of the fuzzy PI controller based on the improved PSO is demonstrated to be obviously better than that of the PI controller or the fuzzy PI controller without using the improved PSO under the situation when the wind speed changes suddenly.

  8. Predictive Direct Torque Control Application-Specific Integrated Circuit of an Induction Motor Drive with a Fuzzy Controller

    Directory of Open Access Journals (Sweden)

    Guo-Ming Sung

    2017-06-01

    Full Text Available This paper proposes a modified predictive direct torque control (PDTC application-specific integrated circuit (ASIC of a motor drive with a fuzzy controller for eliminating sampling and calculating delay times in hysteresis controllers. These delay times degrade the control quality and increase both torque and flux ripples in a motor drive. The proposed fuzzy PDTC ASIC calculates the stator’s magnetic flux and torque by detecting the three-phase current, three-phase voltage, and rotor speed, and eliminates the ripples in the torque and flux by using a fuzzy controller and predictive scheme. The Verilog hardware description language was used to implement the hardware architecture, and the ASIC was fabricated by the Taiwan Semiconductor Manufacturing Company through a 0.18-μm 1P6M CMOS process that involved a cell-based design method. The measurements revealed that the proposed fuzzy PDTC ASIC of the three-phase induction motor yielded a test coverage of 96.03%, fault coverage of 95.06%, chip area of 1.81 × 1.81 mm2, and power consumption of 296 mW, at an operating frequency of 50 MHz and a supply voltage of 1.8 V.

  9. Self-learning fuzzy controllers based on temporal back propagation

    Science.gov (United States)

    Jang, Jyh-Shing R.

    1992-01-01

    This paper presents a generalized control strategy that enhances fuzzy controllers with self-learning capability for achieving prescribed control objectives in a near-optimal manner. This methodology, termed temporal back propagation, is model-insensitive in the sense that it can deal with plants that can be represented in a piecewise-differentiable format, such as difference equations, neural networks, GMDH structures, and fuzzy models. Regardless of the numbers of inputs and outputs of the plants under consideration, the proposed approach can either refine the fuzzy if-then rules if human experts, or automatically derive the fuzzy if-then rules obtained from human experts are not available. The inverted pendulum system is employed as a test-bed to demonstrate the effectiveness of the proposed control scheme and the robustness of the acquired fuzzy controller.

  10. Fuzzy Stochastic Optimization Theory, Models and Applications

    CERN Document Server

    Wang, Shuming

    2012-01-01

    Covering in detail both theoretical and practical perspectives, this book is a self-contained and systematic depiction of current fuzzy stochastic optimization that deploys the fuzzy random variable as a core mathematical tool to model the integrated fuzzy random uncertainty. It proceeds in an orderly fashion from the requisite theoretical aspects of the fuzzy random variable to fuzzy stochastic optimization models and their real-life case studies.   The volume reflects the fact that randomness and fuzziness (or vagueness) are two major sources of uncertainty in the real world, with significant implications in a number of settings. In industrial engineering, management and economics, the chances are high that decision makers will be confronted with information that is simultaneously probabilistically uncertain and fuzzily imprecise, and optimization in the form of a decision must be made in an environment that is doubly uncertain, characterized by a co-occurrence of randomness and fuzziness. This book begins...

  11. Robust and predictive fuzzy key performance indicators for condition-based treatment of squats in railway infrastructures

    NARCIS (Netherlands)

    Jamshidi, A.; Nunez Vicencio, Alfredo; Dollevoet, R.P.B.J.; Li, Z.

    2017-01-01

    This paper presents a condition-based treatment methodology for a type of rail surface defect called squat. The proposed methodology is based on a set of robust and predictive fuzzy key performance indicators. A fuzzy Takagi-Sugeno interval model is used to predict squat evolution for different

  12. SELECTION OF BUSINESS STRATEGIES FOR QUALITY IMPROVEMENT USING FUZZY ANALYTICAL HIERARCHY PROCESS

    Directory of Open Access Journals (Sweden)

    Prasun Das

    2010-12-01

    Full Text Available Fuzzy linguistic concepts are often used to enhance the traditional analytic hierarchy process (AHP in capturing the fuzziness and subjectiveness of decision makers' judgments. In this paper, fuzzy AHP methodology is adopted for selection of the strategies for business improvement in an Indian industry as a decision making problem. Due to simplicity and effectiveness, triangular fuzzy numbers are adopted as a reference to indicate the influence strength of each element in the hierarchy structure. The confidence level and the optimistic levels of multiple decision makers are captured by using ? -cut based fuzzy number methods. This fuzzy set theory based multi-attribute decision making method is found to be quite useful and effective in industrial environment.

  13. Integrating Fuzzy AHP and Fuzzy ARAS for evaluating financial performance

    OpenAIRE

    Abdolhamid Safaei Ghadikolaei; Saber Khalili Esbouei

    2014-01-01

    Multi Criteria Decision Making (MCDM) is an advanced field of Operation Research; recently MCDM methods are efficient and common tools for performance evaluation in many areas such as finance and economy. The aim of this study is to show one of applications of mathematics in real word. This study with considering value based measures and accounting based measures simultaneously, provided a hybrid approach of MCDM methods in fuzzy environment for financial performance evaluation of automotive ...

  14. Creating Clinical Fuzzy Automata with Fuzzy Arden Syntax.

    Science.gov (United States)

    de Bruin, Jeroen S; Steltzer, Heinz; Rappelsberger, Andrea; Adlassnig, Klaus-Peter

    2017-01-01

    Formal constructs for fuzzy sets and fuzzy logic are incorporated into Arden Syntax version 2.9 (Fuzzy Arden Syntax). With fuzzy sets, the relationships between measured or observed data and linguistic terms are expressed as degrees of compatibility that model the unsharpness of the boundaries of linguistic terms. Propositional uncertainty due to incomplete knowledge of relationships between clinical linguistic concepts is modeled with fuzzy logic. Fuzzy Arden Syntax also supports the construction of fuzzy state monitors. The latter are defined as monitors that employ fuzzy automata to observe gradual transitions between different stages of disease. As a use case, we re-implemented FuzzyARDS, a previously published clinical monitoring system for patients suffering from acute respiratory distress syndrome (ARDS). Using the re-implementation as an example, we show how key concepts of fuzzy automata, i.e., fuzzy states and parallel fuzzy state transitions, can be implemented in Fuzzy Arden Syntax. The results showed that fuzzy state monitors can be implemented in a straightforward manner.

  15. EVALUATION AND RANKING OF ARTIFICIAL HIP PROSTHESIS SUPPLIERS BY USING A FUZZY TOPSIS METHODOLOGY

    Directory of Open Access Journals (Sweden)

    Marija Zahar Djordjevic

    2014-06-01

    Full Text Available The aim of this study is to propose a fuzzy multi-criteria decision-making approach (MCDM to evaluate the artificial hip prosthesis suppliers with respect to numerous criteria, simultaneously, taking into account the type of each criteria and its relative importance. The fuzzy of the Technique for Order Preference by Similarity to Ideal Solution (FTOSISis applied in order to rank the artificial hip prosthesis suppliers. The rank is obtained using the process of fuzzy number comparison. Software solution based on suggested method is also presented. A real-life example with real data is presented to clarify the proposed method.

  16. A Combined Methodology of Adaptive Neuro-Fuzzy Inference System and Genetic Algorithm for Short-term Energy Forecasting

    Directory of Open Access Journals (Sweden)

    KAMPOUROPOULOS, K.

    2014-02-01

    Full Text Available This document presents an energy forecast methodology using Adaptive Neuro-Fuzzy Inference System (ANFIS and Genetic Algorithms (GA. The GA has been used for the selection of the training inputs of the ANFIS in order to minimize the training result error. The presented algorithm has been installed and it is being operating in an automotive manufacturing plant. It periodically communicates with the plant to obtain new information and update the database in order to improve its training results. Finally the obtained results of the algorithm are used in order to provide a short-term load forecasting for the different modeled consumption processes.

  17. Evaluating Loans Using a Combination of Data Envelopment and Neuro-Fuzzy Systems

    Directory of Open Access Journals (Sweden)

    Rashmi Malhotra

    2015-02-01

    Full Text Available A business organization's objective is to make better decisions at all levels of the firm to improve performance. Typically organizations are multi-faceted and complex systems that use uncertain information. Therefore, making quality decisions to improve organizational performance is a daunting task. Organizations use decision support systems that apply different business intelligence techniques such as statistical models, scoring models, neural networks, expert systems, neuro-fuzzy systems, case-based systems, or simply rules that have been developed through experience. Managers need a decision-making approach that is robust, competent, effective, efficient, and integrative to handle the multi-dimensional organizational entities. The decision maker deals with multiple players in an organization such as products, customers, competitors, location, geographic structure, scope, internal organization, and cultural dimension [46]. Sound decisions include two important concepts: efficiency (return on invested resources and effectiveness (reaching predetermined goals. However, quite frequently, the decision maker cannot simultaneously handle data from different sources. Hence, we recommend that managers analyze different aspects of data from multiple sources separately and integrate the results of the analysis. This study proposes the design of a multi-attribute-decision-support-system that combines the analytical power of two different tools: data envelopment analysis (DEA and fuzzy logic. DEA evaluates and measures the relative efficiency of decision making units that use multiple inputs and outputs to provide non-objective measures without making any specific assumptions about data. On the other hand fuzzy logic's main strength lies in handling imprecise data. This study proposes a modeling technique that jointly uses the two techniques to benefit from the two methodologies. A major advantage of the DEA approach is that it clearly identifies the

  18. Hybrid fuzzy logic control of laser surface heat treatments

    International Nuclear Information System (INIS)

    Perez, Jose Antonio; Ocana, Jose Luis; Molpeceres, Carlos

    2007-01-01

    This paper presents an advanced hybrid fuzzy logic control system for laser surface heat treatments, which allows to increase significantly the uniformity and final quality of the obtained product, reducing the rejection rate and increasing the productivity and efficiency of the treatment. Basically, the proposed hybrid control structure combines a fuzzy logic controller, with a pure integral action, both fully decoupled, improving the performances of the process with a reasonable design cost, since the system nonlinearities are fully compensated by the fuzzy component of the controller, while the integral action contributes to eliminate the steady-state error

  19. Evaluation of a Multi-Variable Self-Learning Fuzzy Logic Controller ...

    African Journals Online (AJOL)

    In spite of the usefulness of fuzzy control, its main drawback comes from lack of a systematic control design methodology. The most challenging aspect of the design of a fuzzy logic controller is the elicitation of the control rules for its rule base. In this paper, a scheme capable of elicitation of acceptable rules for multivariable ...

  20. use of fuzzy logic to investigate weather parameter impact

    African Journals Online (AJOL)

    user

    2016-07-03

    Jul 3, 2016 ... developed in the Simulink environment of a MATLAB software. The model ... smoothing, stochastic process, ARMA (autoregressive integrated moving .... 2.3 Building of Fuzzy Logic Simulation Model. The fuzzy model is ...

  1. Human factors and fuzzy set theory for safety analysis

    International Nuclear Information System (INIS)

    Nishiwaki, Y.

    1987-01-01

    Human reliability and performance is affected by many factors: medical, physiological and psychological, etc. The uncertainty involved in human factors may not necessarily be probabilistic, but fuzzy. Therefore, it is important to develop a theory by which both the non-probabilistic uncertainties, or fuzziness, of human factors and the probabilistic properties of machines can be treated consistently. In reality, randomness and fuzziness are sometimes mixed. From the mathematical point of view, probabilistic measures may be considered a special case of fuzzy measures. Therefore, fuzzy set theory seems to be an effective tool for analysing man-machine systems. The concept 'failure possibility' based on fuzzy sets is suggested as an approach to safety analysis and fault diagnosis of a large complex system. Fuzzy measures and fuzzy integrals are introduced and their possible applications are also discussed. (author)

  2. COMPARISON of FUZZY-BASED MODELS in LANDSLIDE HAZARD MAPPING

    Directory of Open Access Journals (Sweden)

    N. Mijani

    2017-09-01

    Full Text Available Landslide is one of the main geomorphic processes which effects on the development of prospect in mountainous areas and causes disastrous accidents. Landslide is an event which has different uncertain criteria such as altitude, slope, aspect, land use, vegetation density, precipitation, distance from the river and distance from the road network. This research aims to compare and evaluate different fuzzy-based models including Fuzzy Analytic Hierarchy Process (Fuzzy-AHP, Fuzzy Gamma and Fuzzy-OR. The main contribution of this paper reveals to the comprehensive criteria causing landslide hazard considering their uncertainties and comparison of different fuzzy-based models. The quantify of evaluation process are calculated by Density Ratio (DR and Quality Sum (QS. The proposed methodology implemented in Sari, one of the city of Iran which has faced multiple landslide accidents in recent years due to the particular environmental conditions. The achieved results of accuracy assessment based on the quantifier strated that Fuzzy-AHP model has higher accuracy compared to other two models in landslide hazard zonation. Accuracy of zoning obtained from Fuzzy-AHP model is respectively 0.92 and 0.45 based on method Precision (P and QS indicators. Based on obtained landslide hazard maps, Fuzzy-AHP, Fuzzy Gamma and Fuzzy-OR respectively cover 13, 26 and 35 percent of the study area with a very high risk level. Based on these findings, fuzzy-AHP model has been selected as the most appropriate method of zoning landslide in the city of Sari and the Fuzzy-gamma method with a minor difference is in the second order.

  3. Identifying desertification risk areas using fuzzy membership and ...

    Indian Academy of Sciences (India)

    An integrated model with fuzzy membership analysis, fuzzy rule- ... major sources of desertification in Kota are, namely Gully and Ravine erosion, inappropriate ... plant production, soil health and water quantity ..... fied for implementing preventive methods to check ...... Determination and management in soil physical proper-.

  4. The use of an integrated variable fuzzy sets in water resources management

    Science.gov (United States)

    Qiu, Qingtai; Liu, Jia; Li, Chuanzhe; Yu, Xinzhe; Wang, Yang

    2018-06-01

    Based on the evaluation of the present situation of water resources and the development of water conservancy projects and social economy, optimal allocation of regional water resources presents an increasing need in the water resources management. Meanwhile it is also the most effective way to promote the harmonic relationship between human and water. In view of the own limitations of the traditional evaluations of which always choose a single index model using in optimal allocation of regional water resources, on the basis of the theory of variable fuzzy sets (VFS) and system dynamics (SD), an integrated variable fuzzy sets model (IVFS) is proposed to address dynamically complex problems in regional water resources management in this paper. The model is applied to evaluate the level of the optimal allocation of regional water resources of Zoucheng in China. Results show that the level of allocation schemes of water resources ranging from 2.5 to 3.5, generally showing a trend of lower level. To achieve optimal regional management of water resources, this model conveys a certain degree of accessing water resources management, which prominently improve the authentic assessment of water resources management by using the eigenvector of level H.

  5. A Methodology for Integrating Maintainability Using Software Metrics

    OpenAIRE

    Lewis, John A.; Henry, Sallie M.

    1989-01-01

    Maintainability must be integrated into software early in the development process. But for practical use, the techniques used must be as unobtrusive to the existing software development process as possible. This paper defines a methodology for integrating maintainability into large-scale software and describes an experiment which implemented the methodology into a major commercial software development environment.

  6. A first course in fuzzy logic, fuzzy dynamical systems, and biomathematics theory and applications

    CERN Document Server

    de Barros, Laécio Carvalho; Lodwick, Weldon Alexander

    2017-01-01

    This book provides an essential introduction to the field of dynamical models. Starting from classical theories such as set theory and probability, it allows readers to draw near to the fuzzy case. On one hand, the book equips readers with a fundamental understanding of the theoretical underpinnings of fuzzy sets and fuzzy dynamical systems. On the other, it demonstrates how these theories are used to solve modeling problems in biomathematics, and presents existing derivatives and integrals applied to the context of fuzzy functions. Each of the major topics is accompanied by examples, worked-out exercises, and exercises to be completed. Moreover, many applications to real problems are presented. The book has been developed on the basis of the authors’ lectures to university students and is accordingly primarily intended as a textbook for both upper-level undergraduates and graduates in applied mathematics, statistics, and engineering. It also offers a valuable resource for practitioners such as mathematical...

  7. A neural-fuzzy approach to classify the ecological status in surface waters

    International Nuclear Information System (INIS)

    Ocampo-Duque, William; Schuhmacher, Marta; Domingo, Jose L.

    2007-01-01

    A methodology based on a hybrid approach that combines fuzzy inference systems and artificial neural networks has been used to classify ecological status in surface waters. This methodology has been proposed to deal efficiently with the non-linearity and highly subjective nature of variables involved in this serious problem. Ecological status has been assessed with biological, hydro-morphological, and physicochemical indicators. A data set collected from 378 sampling sites in the Ebro river basin has been used to train and validate the hybrid model. Up to 97.6% of sampling sites have been correctly classified with neural-fuzzy models. Such performance resulted very competitive when compared with other classification algorithms. With non-parametric classification-regression trees and probabilistic neural networks, the predictive capacities were 90.7% and 97.0%, respectively. The proposed methodology can support decision-makers in evaluation and classification of ecological status, as required by the EU Water Framework Directive. - Fuzzy inference systems can be used as environmental classifiers

  8. Utilization of accident databases and fuzzy sets to estimate frequency of HazMat transport accidents

    International Nuclear Information System (INIS)

    Qiao Yuanhua; Keren, Nir; Mannan, M. Sam

    2009-01-01

    Risk assessment and management of transportation of hazardous materials (HazMat) require the estimation of accident frequency. This paper presents a methodology to estimate hazardous materials transportation accident frequency by utilizing publicly available databases and expert knowledge. The estimation process addresses route-dependent and route-independent variables. Negative binomial regression is applied to an analysis of the Department of Public Safety (DPS) accident database to derive basic accident frequency as a function of route-dependent variables, while the effects of route-independent variables are modeled by fuzzy logic. The integrated methodology provides the basis for an overall transportation risk analysis, which can be used later to develop a decision support system.

  9. Adaptive fuzzy controller based MPPT for photovoltaic systems

    International Nuclear Information System (INIS)

    Guenounou, Ouahib; Dahhou, Boutaib; Chabour, Ferhat

    2014-01-01

    Highlights: • We propose a fuzzy controller with adaptive output scaling factor as a maximum power point tracker of photovoltaic system. • The proposed controller integrates two different rule bases defined on error and change of error. • Our controller can track the maximum power point with better performances when compared to its conventional counterpart. - Abstract: This paper presents an intelligent approach to optimize the performances of photovoltaic systems. The system consists of a PV panel, a DC–DC boost converter, a maximum power point tracker controller and a resistive load. The key idea of the proposed approach is the use of a fuzzy controller with an adaptive gain as a maximum power point tracker. The proposed controller integrates two different rule bases. The first is used to adjust the duty cycle of the boost converter as in the case of a conventional fuzzy controller while the second rule base is designed for an online adjusting of the controller’s gain. The performances of the adaptive fuzzy controller are compared with those obtained using a conventional fuzzy controllers with different gains and in each case, the proposed controller outperforms its conventional counterpart

  10. Speed Control Design of Permanent Magnet Synchronous Motor using TakagiSugeno Fuzzy Logic Control

    Directory of Open Access Journals (Sweden)

    Ahmad Asri Abd Samat

    2017-12-01

    Full Text Available This paper proposes a speed control design of Permanent Magnet Synchronous Motor (PMSM using Field Oriented Control (FOC. The focus is to design a speed control using Takagi — Sugeno Fuzzy Logic Control (T-S FLS. These systems will replace the conventional method which is proportional-integral (PI. The objective of this paper is to study the T—S Fuzzy Inference System (FIS speed regulator and acceleration observer for PMSM. The scope of study basically is to design and analyse the Takagi Sugeno FLC and the PMSM. This paper also will describe the methodology and process of modelling the PMSM including data analysis. The simulation work is implemented in Matlab-Simulink to verify the control method. The effectiveness of this proposed control method was confirmed through various range of speed and torque variation.

  11. Numerical Solution of Uncertain Beam Equations Using Double Parametric Form of Fuzzy Numbers

    Directory of Open Access Journals (Sweden)

    Smita Tapaswini

    2013-01-01

    Full Text Available Present paper proposes a new technique to solve uncertain beam equation using double parametric form of fuzzy numbers. Uncertainties appearing in the initial conditions are taken in terms of triangular fuzzy number. Using the single parametric form, the fuzzy beam equation is converted first to an interval-based fuzzy differential equation. Next, this differential equation is transformed to crisp form by applying double parametric form of fuzzy number. Finally, the same is solved by homotopy perturbation method (HPM to obtain the uncertain responses subject to unit step and impulse loads. Obtained results are depicted in terms of plots to show the efficiency and powerfulness of the methodology.

  12. Automated sleep stage detection with a classical and a neural learning algorithm--methodological aspects.

    Science.gov (United States)

    Schwaibold, M; Schöchlin, J; Bolz, A

    2002-01-01

    For classification tasks in biosignal processing, several strategies and algorithms can be used. Knowledge-based systems allow prior knowledge about the decision process to be integrated, both by the developer and by self-learning capabilities. For the classification stages in a sleep stage detection framework, three inference strategies were compared regarding their specific strengths: a classical signal processing approach, artificial neural networks and neuro-fuzzy systems. Methodological aspects were assessed to attain optimum performance and maximum transparency for the user. Due to their effective and robust learning behavior, artificial neural networks could be recommended for pattern recognition, while neuro-fuzzy systems performed best for the processing of contextual information.

  13. Implementation of Fuzzy Logic Based Temperature-Controlled Heat ...

    African Journals Online (AJOL)

    This research then compares the control performance of PID (Proportional Integral and Derivative) and Fuzzy logic controllers. Conclusions are made based on these control performances. The results show that the control performance for a Fuzzy controller is quite similar to PID controller but comparatively gives a better ...

  14. Fuzzy logic application for extruders replacement problem

    Directory of Open Access Journals (Sweden)

    Edison Conde Perez dos Santos

    2017-03-01

    Full Text Available In a scenario of uncertainty and imprecision, before taking the replacement analysis, a manager needs to consider the uncertain reality of a problem. In this scenario, the fuzzy logic makes an excellent option. Therefore, it is necessary to make a decision based on the fuzzy model. This study is based on the comparison of two methodologies used in the problem of asset replacement. The study, thus, was based on a comparison between two extruders for polypropylene yarn bibliopegy, comparing mainly the costs involved in maintaining the equipment.

  15. FUZZY LOGIC IN LEGAL EDUCATION

    Directory of Open Access Journals (Sweden)

    Z. Gonul BALKIR

    2011-04-01

    Full Text Available The necessity of examination of every case within its peculiar conditions in social sciences requires different approaches complying with the spirit and nature of social sciences. Multiple realities require different and various perceptual interpretations. In modern world and social sciences, interpretation of perception of valued and multi-valued have been started to be understood by the principles of fuzziness and fuzzy logic. Having the verbally expressible degrees of truthness such as true, very true, rather true, etc. fuzzy logic provides the opportunity for the interpretation of especially complex and rather vague set of information by flexibility or equivalence of the variables’ of fuzzy limitations. The methods and principles of fuzzy logic can be benefited in examination of the methodological problems of law, especially in the applications of filling the legal loopholes arising from the ambiguities and interpretation problems in order to understand the legal rules in a more comprehensible and applicable way and the efficiency of legal implications. On the other hand, fuzzy logic can be used as a technical legal method in legal education and especially in legal case studies and legal practice applications in order to provide the perception of law as a value and the more comprehensive and more quality perception and interpretation of value of justice, which is the core value of law. In the perception of what happened as it has happened in legal relationships and formations, the understanding of social reality and sociological legal rules with multi valued sense perspective and the their applications in accordance with the fuzzy logic’s methods could create more equivalent and just results. It can be useful for the young lawyers and law students as a facilitating legal method especially in the materialization of the perception and interpretation of multi valued and variables. Using methods and principles of fuzzy logic in legal

  16. Analysis of atomic force microscopy data for surface characterization using fuzzy logic

    International Nuclear Information System (INIS)

    Al-Mousa, Amjed; Niemann, Darrell L.; Niemann, Devin J.; Gunther, Norman G.; Rahman, Mahmud

    2011-01-01

    In this paper we present a methodology to characterize surface nanostructures of thin films. The methodology identifies and isolates nanostructures using Atomic Force Microscopy (AFM) data and extracts quantitative information, such as their size and shape. The fuzzy logic based methodology relies on a Fuzzy Inference Engine (FIE) to classify the data points as being top, bottom, uphill, or downhill. The resulting data sets are then further processed to extract quantitative information about the nanostructures. In the present work we introduce a mechanism which can consistently distinguish crowded surfaces from those with sparsely distributed structures and present an omni-directional search technique to improve the structural recognition accuracy. In order to demonstrate the effectiveness of our approach we present a case study which uses our approach to quantitatively identify particle sizes of two specimens each with a unique gold nanoparticle size distribution. - Research Highlights: → A Fuzzy logic analysis technique capable of characterizing AFM images of thin films. → The technique is applicable to different surfaces regardless of their densities. → Fuzzy logic technique does not require manual adjustment of the algorithm parameters. → The technique can quantitatively capture differences between surfaces. → This technique yields more realistic structure boundaries compared to other methods.

  17. On Intuitionistic Fuzzy Filters of Intuitionistic Fuzzy Coframes

    Directory of Open Access Journals (Sweden)

    Rajesh K. Thumbakara

    2013-01-01

    Full Text Available Frame theory is the study of topology based on its open set lattice, and it was studied extensively by various authors. In this paper, we study quotients of intuitionistic fuzzy filters of an intuitionistic fuzzy coframe. The quotients of intuitionistic fuzzy filters are shown to be filters of the given intuitionistic fuzzy coframe. It is shown that the collection of all intuitionistic fuzzy filters of a coframe and the collection of all intutionistic fuzzy quotient filters of an intuitionistic fuzzy filter are coframes.

  18. Why fuzzy controllers should be fuzzy

    International Nuclear Information System (INIS)

    Nowe, A.

    1996-01-01

    Fuzzy controllers are usually looked at as crisp valued mappings especially when artificial intelligence learning techniques are used to build up the controller. By doing so the semantics of a fuzzy conclusion being a fuzzy restriction on the viable control actions is non-existing. In this paper the authors criticise from an approximation point of view using a fuzzy controller to express a crisp mapping does not seem the right way to go. Secondly it is illustrated that interesting information is contained in a fuzzy conclusion when indeed this conclusion is considered as a fuzzy restriction. This information turns out to be very valuable when viability problems are concerned, i.e. problems where the objective is to keep a system within predefined boundaries

  19. A feasibility investigation for modeling and optimization of temperature in bone drilling using fuzzy logic and Taguchi optimization methodology.

    Science.gov (United States)

    Pandey, Rupesh Kumar; Panda, Sudhansu Sekhar

    2014-11-01

    Drilling of bone is a common procedure in orthopedic surgery to produce hole for screw insertion to fixate the fracture devices and implants. The increase in temperature during such a procedure increases the chances of thermal invasion of bone which can cause thermal osteonecrosis resulting in the increase of healing time or reduction in the stability and strength of the fixation. Therefore, drilling of bone with minimum temperature is a major challenge for orthopedic fracture treatment. This investigation discusses the use of fuzzy logic and Taguchi methodology for predicting and minimizing the temperature produced during bone drilling. The drilling experiments have been conducted on bovine bone using Taguchi's L25 experimental design. A fuzzy model is developed for predicting the temperature during orthopedic drilling as a function of the drilling process parameters (point angle, helix angle, feed rate and cutting speed). Optimum bone drilling process parameters for minimizing the temperature are determined using Taguchi method. The effect of individual cutting parameters on the temperature produced is evaluated using analysis of variance. The fuzzy model using triangular and trapezoidal membership predicts the temperature within a maximum error of ±7%. Taguchi analysis of the obtained results determined the optimal drilling conditions for minimizing the temperature as A3B5C1.The developed system will simplify the tedious task of modeling and determination of the optimal process parameters to minimize the bone drilling temperature. It will reduce the risk of thermal osteonecrosis and can be very effective for the online condition monitoring of the process. © IMechE 2014.

  20. A fuzzy expert system based on relations

    International Nuclear Information System (INIS)

    Hall, L.O.; Kandel, A.

    1986-01-01

    The Fuzzy Expert System (FESS) is an expert system which makes use of the theory of fuzzy relations to perform inference. Relations are very general and can be used for any application, which only requires different types of relations be implemented and used. The incorporation of fuzzy reasoning techniques enables the expert system to deal with imprecision in a well-founded manner. The knowledge is represented in relational frames. FESS may operate in either a forward chaining or backward chaining manner. It uses primarily implication and factual relations. A unique methodology for combination of evidence has been developed. It makes uses of a blackboard for communication between the various knowledge sources which may operate in parallel. The expert system has been designed in such a manner that it may be used for diverse applications

  1. A fuzzy chance-constrained programming model with type 1 and type 2 fuzzy sets for solid waste management under uncertainty

    Science.gov (United States)

    Ma, Xiaolin; Ma, Chi; Wan, Zhifang; Wang, Kewei

    2017-06-01

    Effective management of municipal solid waste (MSW) is critical for urban planning and development. This study aims to develop an integrated type 1 and type 2 fuzzy sets chance-constrained programming (ITFCCP) model for tackling regional MSW management problem under a fuzzy environment, where waste generation amounts are supposed to be type 2 fuzzy variables and treated capacities of facilities are assumed to be type 1 fuzzy variables. The evaluation and expression of uncertainty overcome the drawbacks in describing fuzzy possibility distributions as oversimplified forms. The fuzzy constraints are converted to their crisp equivalents through chance-constrained programming under the same or different confidence levels. Regional waste management of the City of Dalian, China, was used as a case study for demonstration. The solutions under various confidence levels reflect the trade-off between system economy and reliability. It is concluded that the ITFCCP model is capable of helping decision makers to generate reasonable waste-allocation alternatives under uncertainties.

  2. Genetic algorithms and fuzzy multiobjective optimization

    CERN Document Server

    Sakawa, Masatoshi

    2002-01-01

    Since the introduction of genetic algorithms in the 1970s, an enormous number of articles together with several significant monographs and books have been published on this methodology. As a result, genetic algorithms have made a major contribution to optimization, adaptation, and learning in a wide variety of unexpected fields. Over the years, many excellent books in genetic algorithm optimization have been published; however, they focus mainly on single-objective discrete or other hard optimization problems under certainty. There appears to be no book that is designed to present genetic algorithms for solving not only single-objective but also fuzzy and multiobjective optimization problems in a unified way. Genetic Algorithms And Fuzzy Multiobjective Optimization introduces the latest advances in the field of genetic algorithm optimization for 0-1 programming, integer programming, nonconvex programming, and job-shop scheduling problems under multiobjectiveness and fuzziness. In addition, the book treats a w...

  3. Modulation transfer function estimation of optical lens system by adaptive neuro-fuzzy methodology

    Science.gov (United States)

    Petković, Dalibor; Shamshirband, Shahaboddin; Pavlović, Nenad T.; Anuar, Nor Badrul; Kiah, Miss Laiha Mat

    2014-07-01

    The quantitative assessment of image quality is an important consideration in any type of imaging system. The modulation transfer function (MTF) is a graphical description of the sharpness and contrast of an imaging system or of its individual components. The MTF is also known and spatial frequency response. The MTF curve has different meanings according to the corresponding frequency. The MTF of an optical system specifies the contrast transmitted by the system as a function of image size, and is determined by the inherent optical properties of the system. In this study, the adaptive neuro-fuzzy (ANFIS) estimator is designed and adapted to estimate MTF value of the actual optical system. Neural network in ANFIS adjusts parameters of membership function in the fuzzy logic of the fuzzy inference system. The back propagation learning algorithm is used for training this network. This intelligent estimator is implemented using Matlab/Simulink and the performances are investigated. The simulation results presented in this paper show the effectiveness of the developed method.

  4. Design of a new adaptive fuzzy controller and its application to vibration control of a vehicle seat installed with an MR damper

    International Nuclear Information System (INIS)

    Phu, Do Xuan; Shin, Do Kyun; Choi, Seung-Bok

    2015-01-01

    This paper presents a new adaptive fuzzy controller featuring a combination of two different control methodologies: H infinity control technique and sliding mode control. It is known that both controllers are powerful in terms of high performance and robust stability. However, both control methods require an accurate dynamic model to design a state variable based controller in order to maintain their advantages. Thus, in this work a fuzzy control method which does not require an accurate dynamic model is adopted and two control methodologies are integrated to maintain the advantages even in an uncertain environment of the dynamic system. After a brief explanation of the interval type 2 fuzzy logic, a new adaptive fuzzy controller associated with the H infinity control and sliding mode control is formulated on the basis of Lyapunov stability theory. Subsequently, the formulated controller is applied to vibration control of a vehicle seat equipped with magnetorheological fluid damper (MR damper in short). An experimental setup for realization of the proposed controller is established and vibration control performances such as acceleration at the driver’s seat are evaluated. In addition, in order to demonstrate the effectiveness of the proposed controller, a comparative work with two existing controllers is undertaken. It is shown through simulation and experiment that the proposed controller can provide much better vibration control performance than the two existing controllers. (paper)

  5. Regression to fuzziness method for estimation of remaining useful life in power plant components

    Science.gov (United States)

    Alamaniotis, Miltiadis; Grelle, Austin; Tsoukalas, Lefteri H.

    2014-10-01

    Mitigation of severe accidents in power plants requires the reliable operation of all systems and the on-time replacement of mechanical components. Therefore, the continuous surveillance of power systems is a crucial concern for the overall safety, cost control, and on-time maintenance of a power plant. In this paper a methodology called regression to fuzziness is presented that estimates the remaining useful life (RUL) of power plant components. The RUL is defined as the difference between the time that a measurement was taken and the estimated failure time of that component. The methodology aims to compensate for a potential lack of historical data by modeling an expert's operational experience and expertise applied to the system. It initially identifies critical degradation parameters and their associated value range. Once completed, the operator's experience is modeled through fuzzy sets which span the entire parameter range. This model is then synergistically used with linear regression and a component's failure point to estimate the RUL. The proposed methodology is tested on estimating the RUL of a turbine (the basic electrical generating component of a power plant) in three different cases. Results demonstrate the benefits of the methodology for components for which operational data is not readily available and emphasize the significance of the selection of fuzzy sets and the effect of knowledge representation on the predicted output. To verify the effectiveness of the methodology, it was benchmarked against the data-based simple linear regression model used for predictions which was shown to perform equal or worse than the presented methodology. Furthermore, methodology comparison highlighted the improvement in estimation offered by the adoption of appropriate of fuzzy sets for parameter representation.

  6. Stability Analysis of a Type of Takagi-Sugeno PI Fuzzy Control Systems Using Circle Criterion

    Directory of Open Access Journals (Sweden)

    Kairui Cao

    2011-04-01

    Full Text Available A type of Takagi-Sugeno (T-S Proportional-Integral (PI fuzzy controllers is studied. The T-S PI fuzzy controller is formed by a T-S Proportional-Derivative (PD fuzzy controller connected with an integrator. In this particular structure, the T-S PD fuzzy controller is a weighted sum of some linear PD sub-controllers. The mathematical properties of our T-S PI fuzzy controller are also investigated. Based on these properties, the global asymptotic stability of the fuzzy control systems, in which the T-S PI fuzzy controllers are employed, are analyzed by using the well-known circle criterion. A sufficient condition with an elegant graphical interpretation in the frequency domain is further derived to guarantee the global asymptotic stability of the above fuzzy control systems. Finally, two numerical examples are provided to demonstrate how to deploy this method in analyzing the T-S PI fuzzy control systems in the frequency domain with the aid of some simple graphs.

  7. FSILP: fuzzy-stochastic-interval linear programming for supporting municipal solid waste management.

    Science.gov (United States)

    Li, Pu; Chen, Bing

    2011-04-01

    Although many studies on municipal solid waste management (MSW management) were conducted under uncertain conditions of fuzzy, stochastic, and interval coexistence, the solution to the conventional linear programming problems of integrating fuzzy method with the other two was inefficient. In this study, a fuzzy-stochastic-interval linear programming (FSILP) method is developed by integrating Nguyen's method with conventional linear programming for supporting municipal solid waste management. The Nguyen's method was used to convert the fuzzy and fuzzy-stochastic linear programming problems into the conventional linear programs, by measuring the attainment values of fuzzy numbers and/or fuzzy random variables, as well as superiority and inferiority between triangular fuzzy numbers/triangular fuzzy-stochastic variables. The developed method can effectively tackle uncertainties described in terms of probability density functions, fuzzy membership functions, and discrete intervals. Moreover, the method can also improve upon the conventional interval fuzzy programming and two-stage stochastic programming approaches, with advantageous capabilities that are easily achieved with fewer constraints and significantly reduces consumption time. The developed model was applied to a case study of municipal solid waste management system in a city. The results indicated that reasonable solutions had been generated. The solution can help quantify the relationship between the change of system cost and the uncertainties, which could support further analysis of tradeoffs between the waste management cost and the system failure risk. Copyright © 2010 Elsevier Ltd. All rights reserved.

  8. Reducing the Complexity of Genetic Fuzzy Classifiers in Highly-Dimensional Classification Problems

    Directory of Open Access Journals (Sweden)

    DimitrisG. Stavrakoudis

    2012-04-01

    Full Text Available This paper introduces the Fast Iterative Rule-based Linguistic Classifier (FaIRLiC, a Genetic Fuzzy Rule-Based Classification System (GFRBCS which targets at reducing the structural complexity of the resulting rule base, as well as its learning algorithm's computational requirements, especially when dealing with high-dimensional feature spaces. The proposed methodology follows the principles of the iterative rule learning (IRL approach, whereby a rule extraction algorithm (REA is invoked in an iterative fashion, producing one fuzzy rule at a time. The REA is performed in two successive steps: the first one selects the relevant features of the currently extracted rule, whereas the second one decides the antecedent part of the fuzzy rule, using the previously selected subset of features. The performance of the classifier is finally optimized through a genetic tuning post-processing stage. Comparative results in a hyperspectral remote sensing classification as well as in 12 real-world classification datasets indicate the effectiveness of the proposed methodology in generating high-performing and compact fuzzy rule-based classifiers, even for very high-dimensional feature spaces.

  9. Sanitizing sensitive association rules using fuzzy correlation scheme

    International Nuclear Information System (INIS)

    Hameed, S.; Shahzad, F.; Asghar, S.

    2013-01-01

    Data mining is used to extract useful information hidden in the data. Sometimes this extraction of information leads to revealing sensitive information. Privacy preservation in Data Mining is a process of sanitizing sensitive information. This research focuses on sanitizing sensitive rules discovered in quantitative data. The proposed scheme, Privacy Preserving in Fuzzy Association Rules (PPFAR) is based on fuzzy correlation analysis. In this work, fuzzy set concept is integrated with fuzzy correlation analysis and Apriori algorithm to mark interesting fuzzy association rules. The identified rules are called sensitive. For sanitization, we use modification technique where we substitute maximum value of fuzzy items with zero, which occurs most frequently. Experiments demonstrate that PPFAR method hides sensitive rules with minimum modifications. The technique also maintains the modified data's quality. The PPFAR scheme has applications in various domains e.g. temperature control, medical analysis, travel time prediction, genetic behavior prediction etc. We have validated the results on medical dataset. (author)

  10. METHODOLOGY FRAMEWORK FOR PROCESS INTEGRATION AND SERVICE MANAGEMENT

    Directory of Open Access Journals (Sweden)

    Darko Galinec

    2007-06-01

    Full Text Available History of information systems development was driven by business system's functions automation and mergers and acquisitions - business subjects integration into a whole. Modern business requires business processes integration through their dynamics and thus enterprise application integration (EAI as well. In this connection it is necessary to find ways and means of application integration and interaction in a consistent and reliable way. The real-time enterprise (RTE monitors, captures and analyzes root causes and overt events that are critical to its success the instant those events occur [6]. EAI is determined by business needs and business requirements. It must be based on business process repository and models, business integration methodology (BIM and information flow as well. Decisions concerning technology must be in function of successful application integration. In this paper EAI methodological framework and technological concepts for its achievements are introduced.

  11. Edge detection methods based on generalized type-2 fuzzy logic

    CERN Document Server

    Gonzalez, Claudia I; Castro, Juan R; Castillo, Oscar

    2017-01-01

    In this book four new methods are proposed. In the first method the generalized type-2 fuzzy logic is combined with the morphological gra-dient technique. The second method combines the general type-2 fuzzy systems (GT2 FSs) and the Sobel operator; in the third approach the me-thodology based on Sobel operator and GT2 FSs is improved to be applied on color images. In the fourth approach, we proposed a novel edge detec-tion method where, a digital image is converted a generalized type-2 fuzzy image. In this book it is also included a comparative study of type-1, inter-val type-2 and generalized type-2 fuzzy systems as tools to enhance edge detection in digital images when used in conjunction with the morphologi-cal gradient and the Sobel operator. The proposed generalized type-2 fuzzy edge detection methods were tested with benchmark images and synthetic images, in a grayscale and color format. Another contribution in this book is that the generalized type-2 fuzzy edge detector method is applied in the preproc...

  12. Rule-bases construction through self-learning for a table-based Sugeno-Takagi fuzzy logic control system

    Directory of Open Access Journals (Sweden)

    C. Boldisor

    2009-12-01

    Full Text Available A self-learning based methodology for building the rule-base of a fuzzy logic controller (FLC is presented and verified, aiming to engage intelligent characteristics to a fuzzy logic control systems. The methodology is a simplified version of those presented in today literature. Some aspects are intentionally ignored since it rarely appears in control system engineering and a SISO process is considered here. The fuzzy inference system obtained is a table-based Sugeno-Takagi type. System’s desired performance is defined by a reference model and rules are extracted from recorded data, after the correct control actions are learned. The presented algorithm is tested in constructing the rule-base of a fuzzy controller for a DC drive application. System’s performances and method’s viability are analyzed.

  13. Hybrid Type II fuzzy system & data mining approach for surface finish

    Directory of Open Access Journals (Sweden)

    Tzu-Liang (Bill Tseng

    2015-07-01

    Full Text Available In this study, a new methodology in predicting a system output has been investigated by applying a data mining technique and a hybrid type II fuzzy system in CNC turning operations. The purpose was to generate a supplemental control function under the dynamic machining environment, where unforeseeable changes may occur frequently. Two different types of membership functions were developed for the fuzzy logic systems and also by combining the two types, a hybrid system was generated. Genetic algorithm was used for fuzzy adaptation in the control system. Fuzzy rules are automatically modified in the process of genetic algorithm training. The computational results showed that the hybrid system with a genetic adaptation generated a far better accuracy. The hybrid fuzzy system with genetic algorithm training demonstrated more effective prediction capability and a strong potential for the implementation into existing control functions.

  14. Stability-integrated Fuzzy C means segmentation for spatial ...

    Indian Academy of Sciences (India)

    V ROYNA DAISY

    2018-03-16

    Mar 16, 2018 ... clusters and including spatial information to basic Fuzzy C Means clustering are done in .... modify the objective function with Kernel distance function .... spatial information, thus making it sensitive to noise and outliers.

  15. A new approach to self-organizing fuzzy polynomial neural networks guided by genetic optimization

    International Nuclear Information System (INIS)

    Oh, Sung-Kwun; Pedrycz, Witold

    2005-01-01

    In this study, we introduce a new topology of Fuzzy Polynomial Neural Networks (FPNN) that is based on a genetically optimized multilayer perceptron with fuzzy polynomial neurons (FPNs) and discuss its comprehensive design methodology. The underlying methodology involves mechanisms of genetic optimization, especially genetic algorithms (GAs). Let us recall that the design of the 'conventional' FPNNs uses an extended Group Method of Data Handling (GMDH) and exploits a fixed fuzzy inference type located at each FPN of the FPNN as well as considers a fixed number of input nodes at FPNs (or nodes) located in each layer. The proposed FPNN gives rise to a structurally optimized structure and comes with a substantial level of flexibility in comparison to the one we encounter in conventional FPNNs. The structural optimization is realized via GAs whereas in the case of the parametric optimization we proceed with a standard least square method based learning. Through the consecutive process of such structural and parametric optimization, an optimized and flexible fuzzy neural network is generated in a dynamic fashion. The performance of the proposed gFPNN is quantified through experimentation that exploits standard data already being used in fuzzy modeling. The results reveal superiority of the proposed networks over the existing fuzzy and neural models

  16. Fuzzy logic and image processing techniques for the interpretation of seismic data

    International Nuclear Information System (INIS)

    Orozco-del-Castillo, M G; Ortiz-Alemán, C; Rodríguez-Castellanos, A; Urrutia-Fucugauchi, J

    2011-01-01

    Since interpretation of seismic data is usually a tedious and repetitive task, the ability to do so automatically or semi-automatically has become an important objective of recent research. We believe that the vagueness and uncertainty in the interpretation process makes fuzzy logic an appropriate tool to deal with seismic data. In this work we developed a semi-automated fuzzy inference system to detect the internal architecture of a mass transport complex (MTC) in seismic images. We propose that the observed characteristics of a MTC can be expressed as fuzzy if-then rules consisting of linguistic values associated with fuzzy membership functions. The constructions of the fuzzy inference system and various image processing techniques are presented. We conclude that this is a well-suited problem for fuzzy logic since the application of the proposed methodology yields a semi-automatically interpreted MTC which closely resembles the MTC from expert manual interpretation

  17. Countable Fuzzy Topological Space and Countable Fuzzy Topological Vector Space

    Directory of Open Access Journals (Sweden)

    Apu Kumar Saha

    2015-06-01

    Full Text Available This paper deals with countable fuzzy topological spaces, a generalization of the notion of fuzzy topological spaces. A collection of fuzzy sets F on a universe X forms a countable fuzzy topology if in the definition of a fuzzy topology, the condition of arbitrary supremum is relaxed to countable supremum. In this generalized fuzzy structure, the continuity of fuzzy functions and some other related properties are studied. Also the class of countable fuzzy topological vector spaces as a generalization of the class of fuzzy topological vector spaces has been introduced and investigated.

  18. A fuzzy model for achieving lean attributes for competitive advantages development using AHP-QFD-PROMETHEE

    Science.gov (United States)

    Roghanian, E.; Alipour, Mohammad

    2014-06-01

    Lean production has become an integral part of the manufacturing landscape as its link with superior performance and its ability to provide competitive advantage is well accepted among academics and practitioners. Lean production helps producers in overcoming the challenges organizations face through using powerful tools and enablers. However, most companies are faced with restricted resources such as financial and human resources, time, etc., in using these enablers, and are not capable of implementing all these techniques. Therefore, identifying and selecting the most appropriate and efficient tool can be a significant challenge for many companies. Hence, this literature seeks to combine competitive advantages, lean attributes, and lean enablers to determine the most appropriate enablers for improvement of lean attributes. Quality function deployment in fuzzy environment and house of quality matrix are implemented. Throughout the methodology, fuzzy logic is the basis for translating linguistic judgments required for the relationships and correlation matrix to numerical values. Moreover, for final ranking of lean enablers, a multi-criteria decision-making method (PROMETHEE) is adopted. Finally, a case study in automotive industry is presented to illustrate the implementation of the proposed methodology.

  19. A Lexicographic Method for Matrix Games with Payoffs of Triangular Intuitionistic Fuzzy Numbers

    Directory of Open Access Journals (Sweden)

    Jiang-Xia Nan

    2010-09-01

    Full Text Available The intuitionistic fuzzy set (IF-set has not been applied to matrix game problems yet since it was introduced by K.T.Atanassov. The aim of this paper is to develop a methodology for solving matrix games with payoffs of triangular intuitionistic fuzzy numbers (TIFNs. Firstly the concept of TIFNs and their arithmetic operations and cut sets are introduced as well as the ranking order relations. Secondly the concept of solutions for matrix games with payoffs of TIFNs is defined. A lexicographic methodology is developed to determine the solutions of matrix games with payoffs of TIFNs for both Players through solving a pair of bi-objective linear programming models derived from two new auxiliary intuitionistic fuzzy programming models. The proposed method is illustrated with a numerical example.

  20. Optimality Conditions for Fuzzy Number Quadratic Programming with Fuzzy Coefficients

    Directory of Open Access Journals (Sweden)

    Xue-Gang Zhou

    2014-01-01

    Full Text Available The purpose of the present paper is to investigate optimality conditions and duality theory in fuzzy number quadratic programming (FNQP in which the objective function is fuzzy quadratic function with fuzzy number coefficients and the constraint set is fuzzy linear functions with fuzzy number coefficients. Firstly, the equivalent quadratic programming of FNQP is presented by utilizing a linear ranking function and the dual of fuzzy number quadratic programming primal problems is introduced. Secondly, we present optimality conditions for fuzzy number quadratic programming. We then prove several duality results for fuzzy number quadratic programming problems with fuzzy coefficients.

  1. Automating Software Development Process using Fuzzy Logic

    NARCIS (Netherlands)

    Marcelloni, Francesco; Aksit, Mehmet; Damiani, Ernesto; Jain, Lakhmi C.; Madravio, Mauro

    2004-01-01

    In this chapter, we aim to highlight how fuzzy logic can be a valid expressive tool to manage the software development process. We characterize a software development method in terms of two major components: artifact types and methodological rules. Classes, attributes, operations, and inheritance

  2. Fuzzy modeling and control of the calcination process in a kiln

    International Nuclear Information System (INIS)

    Ramirez, M.; Haber, R.

    1999-01-01

    Calcination kilns are strongly nonlinear, multivariable processes, that only can be modeled with great uncertainty. In order to get a quality product and ensure the process efficiency, the controller must keep a prescribed temperature profile optimizing the fuel consumption. In this paper, a design methodology of a multivariable fuzzy controller for a nickel calcination kiln is presented. The controller structure is a classical one, and uses the Mamdani fuzzy inference system. In simulation results the fuzzy controller exhibits a great robustness in presence of several types of disturbances, and a better performance than the PID in same conditions is observed. (author)

  3. Solving fully fuzzy transportation problem using pentagonal fuzzy numbers

    Science.gov (United States)

    Maheswari, P. Uma; Ganesan, K.

    2018-04-01

    In this paper, we propose a simple approach for the solution of fuzzy transportation problem under fuzzy environment in which the transportation costs, supplies at sources and demands at destinations are represented by pentagonal fuzzy numbers. The fuzzy transportation problem is solved without converting to its equivalent crisp form using a robust ranking technique and a new fuzzy arithmetic on pentagonal fuzzy numbers. To illustrate the proposed approach a numerical example is provided.

  4. Optimization of Neuro-Fuzzy System Using Genetic Algorithm for Chromosome Classification

    Directory of Open Access Journals (Sweden)

    M. Sarosa

    2013-09-01

    Full Text Available Neuro-fuzzy system has been shown to provide a good performance on chromosome classification but does not offer a simple method to obtain the accurate parameter values required to yield the best recognition rate. This paper presents a neuro-fuzzy system where its parameters can be automatically adjusted using genetic algorithms. The approach combines the advantages of fuzzy logic theory, neural networks, and genetic algorithms. The structure consists of a four layer feed-forward neural network that uses a GBell membership function as the output function. The proposed methodology has been applied and tested on banded chromosome classification from the Copenhagen Chromosome Database. Simulation result showed that the proposed neuro-fuzzy system optimized by genetic algorithms offers advantages in setting the parameter values, improves the recognition rate significantly and decreases the training/testing time which makes genetic neuro-fuzzy system suitable for chromosome classification.

  5. Fuzzy process control and knowledge engineering in petrochemical and robotic manufacturing

    Energy Technology Data Exchange (ETDEWEB)

    Aliev, R. (Azerbaijan Industrial Univ., Dept. of Automatic Control Systems, Baku (Russia)); Aliev, F. (Azerbaijan Polytechnique Institute, Dept. of Automation and Computer Science, Baku (Russia)); Babaev, M. (Azerbaijan Industrial Univ., Laboratory of Intelligent Control Systems, Baku (Russia))

    1991-01-01

    This book presents the methodology, the functionality and the pragmatics of implementing and applying AI (Artificial Intelligence) techniques enhanced by the new mathematical discipline of fuzzy sets. Emphasis is put on the design and modelling of fuzzy controllers and intelligent control equipment for the oil processing and chemical industries, as well as on robotics and CAM (Computer-Aided Manufacturing), including the development of appropriate algorithms and computer programs. The content is strongly application-oriented in order to explain the main features of the theory of fuzzy systems using different real examples from concrete engineering projects. It excels over the present literature available on this subject by its descriptions new classes of industrial systems to be controlled with fuzzy logic, as well as by its descriptive introduction to intelligent control systems and fuzzy controllers developed and successfully implemented by the authors in working industrial plants. (orig.).

  6. Adaptive fuzzy control for a simulation of hydraulic analogy of a nuclear reactor

    International Nuclear Information System (INIS)

    Ruan, D.; Li, X.; Eynde, G. van den

    2000-01-01

    In the framework of the on-going R and D project on fuzzy control applications to the Belgian Reactor 1 (BR1) at the Belgian Nuclear Research Centre (SCK-CEN), we have constructed a real fuzzy-logic-control demo model. The demo model is suitable for us to test and compare some new algorithms of fuzzy control and intelligent systems, which is advantageous because it is always difficult and time consuming, due to safety aspects, to do all experiments in a real nuclear environment. In this chapter, we first report briefly on the construction of the demo model, and then introduce the results of a fuzzy control, a proportional-integral-derivative (PID) control and an advanced fuzzy control, in which the advanced fuzzy control is a fuzzy control with an adaptive function that can self-regulate the fuzzy control rules. Afterwards, we present a comparative study of those three methods. The results have shown that fuzzy control has more advantages in terms of flexibility, robustness, and easily updated facilities with respect to the PID control of the demo model, but that PID control has much higher regulation resolution due to its integration terms. The adaptive fuzzy control can dynamically adjust the rule base, therefore it is more robust and suitable to those very uncertain occasions. (orig.)

  7. Interval-valued intuitionistic fuzzy multi-criteria model for design concept selection

    Directory of Open Access Journals (Sweden)

    Daniel Osezua Aikhuele

    2017-09-01

    Full Text Available This paper presents a new approach for design concept selection by using an integrated Fuzzy Analytical Hierarchy Process (FAHP and an Interval-valued intuitionistic fuzzy modified TOP-SIS (IVIF-modified TOPSIS model. The integrated model which uses the improved score func-tion and a weighted normalized Euclidean distance method for the calculation of the separation measures of alternatives from the positive and negative intuitionistic ideal solutions provides a new approach for the computation of intuitionistic fuzzy ideal solutions. The results of the two approaches are integrated using a reflection defuzzification integration formula. To ensure the feasibility and the rationality of the integrated model, the method is successfully applied for eval-uating and selecting some design related problems including a real-life case study for the selec-tion of the best concept design for a new printed-circuit-board (PCB and for a hypothetical ex-ample. The model which provides a novel alternative, has been compared with similar computa-tional methods in the literature.

  8. Intelligent tuning of vibration mitigation process for single link manipulator using fuzzy logic

    Directory of Open Access Journals (Sweden)

    Ahmed A. Ali

    2017-08-01

    Full Text Available In this work, active vibration mitigation for smart single link manipulator is presented. Two piezoelectric transducers were utilized to act as actuator and sensor respectively. Classical Proportional (P controller was tested numerically and experimentally. The comparison between measured results showed good agreement. The proposed work includes the introducing of fuzzy logic for tuning controller's gain within finite element method. Classical Proportional-Integral (PI, Fuzzy-P and Fuzzy-PI controllers were totally integrated as a series of [IF-Then] states and solved numerically by using Finite Element (FE solver (ANSYS. Proposed method will pave the way on solving the tuning process totally within single FE solver with high efficiency. Proposed method satisfied mitigation in the overall free response with about 52% and 74% of the manipulator settling time when Fuzzy-P and Fuzzy-PI controllers were activated respectively. This contribution can be utilized for many other applications related to fuzzy topics.

  9. reactor power control using fuzzy logic

    International Nuclear Information System (INIS)

    Ahmed, A.E.E.

    2001-01-01

    power stabilization is a critical issue in nuclear reactors. convention pd- controller is currently used in egypt second testing research reactor (ETRR-2). two fuzzy controllers are proposed to control the reactor power of ETRR-2 reactor. the design of the first one is based on a set of linguistic rules that were adopted from the human operators experience. after off-line fuzzy computations, the controller is a lookup table, and thus, real time controller is achieved. comparing this f lc response with the pd-controller response, which already exists in the system, through studying the expected transients during the normal operation of ETRR-2 reactor, the simulation results show that, fl s has the better response, the second controller is adaptive fuzzy controller, which is proposed to deal with system non-linearity . The simulation results show that the proposed adaptive fuzzy controller gives a better integral square error (i se) index than the existing conventional od controller

  10. Application of fuzzy inference system to increase efficiency of management decision-making in agricultural enterprises

    OpenAIRE

    Balanovskаya, Tetiana Ivanovna; Boretska, Zoreslava Petrovna

    2014-01-01

    Application of fuzzy inference system to increase efficiency of management decision- making in agricultural enterprises. Theoretical and methodological issues, practical recommendations on improvement of management decision-making in agricultural enterprises to increase their competitiveness have been intensified and developed in the article. A simulation example of a quality management system for agricultural products on the basis of the theory of fuzzy sets and fuzzy logic has been proposed...

  11. Diamond Fuzzy Number

    Directory of Open Access Journals (Sweden)

    T. Pathinathan

    2015-01-01

    Full Text Available In this paper we define diamond fuzzy number with the help of triangular fuzzy number. We include basic arithmetic operations like addition, subtraction of diamond fuzzy numbers with examples. We define diamond fuzzy matrix with some matrix properties. We have defined Nested diamond fuzzy number and Linked diamond fuzzy number. We have further classified Right Linked Diamond Fuzzy number and Left Linked Diamond Fuzzy number. Finally we have verified the arithmetic operations for the above mentioned types of Diamond Fuzzy Numbers.

  12. Fuzzy logic approach for energetic and economic evaluation of hydroelectric projects

    International Nuclear Information System (INIS)

    Iliev, Atanas M.

    2003-01-01

    A mathematical model for energetic and economic evaluation of hydroelectric projects is developed. The main advantage of the proposed methodology is that the model considers uncertainty and vagueness which appears during the decision making process. Due to modeling of variables that are non statistical in their character, fuzzy logic approach is fully incorporated in the model. The first step in energetic evaluation of the hydro power projects is determination of the characteristic of the efficiency of the units to be installed in hydro power plants. For this purpose the model which uses the best characteristics of Artificial Network Fuzzy Inference System (ANFIS) is applied. The method is tested on real systems: HPP Tikves- the power plant in operation and HPP Kozjak - the power plant in construction. The results obtained from practical implementation show that the proposed approach gives superior results than classical polynomial approximation. The model for determining the consumption characteristic of hydro power plant is developed by Sugeno Fuzzy Logic System with polynomials in the consequent part of the rules. Model takes into account the variable gross head of HPP, as well as, the number of units which will be in operation for given output. Modeling of the gross head and power output are performed by expert's design membership functions. This model is practically applied on HPP Tikves for determination of the consumption characteristic for several gross head. The plausible yearly production of electricity from hydro power project, which is important for estimation of the benefit from the project, is calculated by mixed fuzzy-statistical model. hi this approach fuzzy set of the inflow is constructed according to the statistical parameters. The calculation of the production of electricity is realized for a several hydrological conditions which are described by linguistic variables. Finally, Mamdani Fuzzy Inference System with fuzzy number in consequent part

  13. Reliable Decentralized Control of Fuzzy Discrete-Event Systems and a Test Algorithm.

    Science.gov (United States)

    Liu, Fuchun; Dziong, Zbigniew

    2013-02-01

    A framework for decentralized control of fuzzy discrete-event systems (FDESs) has been recently presented to guarantee the achievement of a given specification under the joint control of all local fuzzy supervisors. As a continuation, this paper addresses the reliable decentralized control of FDESs in face of possible failures of some local fuzzy supervisors. Roughly speaking, for an FDES equipped with n local fuzzy supervisors, a decentralized supervisor is called k-reliable (1 ≤ k ≤ n) provided that the control performance will not be degraded even when n - k local fuzzy supervisors fail. A necessary and sufficient condition for the existence of k-reliable decentralized supervisors of FDESs is proposed by introducing the notions of M̃uc-controllability and k-reliable coobservability of fuzzy language. In particular, a polynomial-time algorithm to test the k-reliable coobservability is developed by a constructive methodology, which indicates that the existence of k-reliable decentralized supervisors of FDESs can be checked with a polynomial complexity.

  14. Fuzzy-like multiple objective multistage decision making

    CERN Document Server

    Xu, Jiuping

    2014-01-01

    Decision has inspired reflection of many thinkers since the ancient times. With the rapid development of science and society, appropriate dynamic decision making has been playing an increasingly important role in many areas of human activity including engineering, management, economy and others. In most real-world problems, decision makers usually have to make decisions sequentially at different points in time and space, at different levels for a component or a system, while facing multiple and conflicting objectives and a hybrid uncertain environment where fuzziness and randomness co-exist in a decision making process. This leads to the development of fuzzy-like multiple objective multistage decision making. This book provides a thorough understanding of the concepts of dynamic optimization from a modern perspective and presents the state-of-the-art methodology for modeling, analyzing and solving the most typical multiple objective multistage decision making practical application problems under fuzzy-like un...

  15. DESCRIBING FUNCTION METHOD FOR PI-FUZZY CONTROLLED SYSTEMS STABILITY ANALYSIS

    Directory of Open Access Journals (Sweden)

    Stefan PREITL

    2004-12-01

    Full Text Available The paper proposes a global stability analysis method dedicated to fuzzy control systems containing Mamdani PI-fuzzy controllers with output integration to control SISO linear / linearized plants. The method is expressed in terms of relatively simple steps, and it is based on: the generalization of the describing function method for the considered fuzzy control systems to the MIMO case, the approximation of the describing functions by applying the least squares method. The method is applied to the stability analysis of a class of PI-fuzzy controlled servo-systems, and validated by considering a case study.

  16. Groundwater vulnerability and risk mapping using GIS, modeling and a fuzzy logic tool.

    Science.gov (United States)

    Nobre, R C M; Rotunno Filho, O C; Mansur, W J; Nobre, M M M; Cosenza, C A N

    2007-12-07

    A groundwater vulnerability and risk mapping assessment, based on a source-pathway-receptor approach, is presented for an urban coastal aquifer in northeastern Brazil. A modified version of the DRASTIC methodology was used to map the intrinsic and specific groundwater vulnerability of a 292 km(2) study area. A fuzzy hierarchy methodology was adopted to evaluate the potential contaminant source index, including diffuse and point sources. Numerical modeling was performed for delineation of well capture zones, using MODFLOW and MODPATH. The integration of these elements provided the mechanism to assess groundwater pollution risks and identify areas that must be prioritized in terms of groundwater monitoring and restriction on use. A groundwater quality index based on nitrate and chloride concentrations was calculated, which had a positive correlation with the specific vulnerability index.

  17. Study on scenario evaluation methodology for decommissioning nuclear facilities using fuzzy logic

    International Nuclear Information System (INIS)

    Matsuhashi, Kazuya; Yanagihara, Satoshi

    2015-01-01

    Since there are many scenarios of the process from start to completion of a decommissioning project, it is important to study scenarios of decommissioning by evaluating such properties as safety, cost, and technology. An optimum scenario with the highest feasibility in accordance with the facility and environmental conditions should be selected on the basis of the results of the study. For analyzing a scenario of decommissioning, we prepared structured work packages by using the work breakdown structures (WBS) method together with qualitative evaluation of the technologies being applied to work packages located at the bottom (the third level) of the WBS. A calculation model was constructed to evaluate the feasibility of a scenario where fuzzy logic is applied to derive a score of technology performance and TOPSIS is applied for getting a feasibility grade of the scenario from technical performance scoring. As a case study, the model was applied to the debris removal scenario of Fukushima Daiichi Nuclear Power Plant to confirm its applicability. Two scenarios, underwater and in-air debris removal cases, were characterized by extracting the work packages with the lowest feasibility and by obtaining total average scores of the scenarios. It is confirmed that the methodology developed is useful for the scenario evaluation of decommissioning nuclear facilities. (author)

  18. Fuzzy model investic do High-tech projektů

    Directory of Open Access Journals (Sweden)

    Alžběta Kubíčková

    2013-10-01

    Full Text Available Purpose of the article: Relations among parameters of High-tech projects are very complex, vague, partially inconsistent and multidimensional. Optimal decisions to invest into High-tech companies require top field experts and knowledgeable investors. Therefore the conventional methods of investments analysis are not relevant. Therefore fuzzy logic is introduced. Methodology/methods: A fuzzy knowledge base is a flexible framework for acquisition of vague inconsistent knowledge items which are typical for knowledge economics and consequently for High-tech projects. The pooling of the records and / or observations represents a trade-off between minimal modification of the original data and elimination of inconsistencies among available sets of data. Scientific aim: The paper presents a detailed description of fuzzy model of investment decision making into High-tech firm’s projects. A set of conditional statements was used to formalize the effects of selected variables on investment feasibility of High-tech projects. The main aim is to quantify feasibilities of High-tech projects risk investors make good /not bad decisions. Findings: A set of 50 observations of High-tech companies was transformed into a set of 50 conditional statements using 14 variables. The result is the fuzzy model, which can be used to answer investors’ queries. Two queries are answered and presented in details as an example and as a nucleus of a fuzzy dialogue investor – computer. Conclusions: The main problem is the sparseness of the fuzzy model. Many fuzzy similarities are relatively low and the decision process is therefore often problematic. A much more complex set of variables must be applied to specify the fuzzy model to increase reliability of predictions and decisions.

  19. Fuzzy power control algorithm for a pressurized water reactor

    International Nuclear Information System (INIS)

    Hah, Y.J.; Lee, B.W.

    1994-01-01

    A fuzzy power control algorithm is presented for automatic reactor power control in a pressurized water reactor (PWR). Automatic power shape control is complicated by the use of control rods with a conventional proportional-integral-differential controller because it is highly coupled with reactivity compensation. Thus, manual shape controls are usually employed even for the limited capability needed for load-following operations including frequency control. In an attempt to achieve automatic power shape control without any design modifications to the core, a fuzzy power control algorithm is proposed. For the fuzzy control, the rule base is formulated based on a multiple-input multiple-output system. The minimum operation rule and the center of area method are implemented for the development of the fuzzy algorithm. The fuzzy power control algorithm has been applied to Yonggwang Nuclear Unit 3. The simulation results show that the fuzzy control can be adapted as a practical control strategy for automatic reactor power control of PWRs during the load-following operations

  20. Project INTEGRATE - a common methodological approach to understand integrated health care in Europe

    Directory of Open Access Journals (Sweden)

    Lucinda Cash-Gibson

    2014-12-01

    Full Text Available Background: The use of case studies in health services research has proven to be an excellent methodology for gaining in-depth understanding of the organisation and delivery of health care. This is particularly relevant when looking at the complexity of integrated healthcare programmes, where multifaceted interactions occur at the different levels of care and often without a clear link between the interventions (new and/or existing and their impact on outcomes (in terms of patients health, both patient and professional satisfaction and cost-effectiveness. Still, integrated care is seen as a core strategy in the sustainability of health and care provision in most societies in Europe and beyond. More specifically, at present, there is neither clear evidence on transferable factors of integrated care success nor a method for determining how to establish these specific success factors. The drawback of case methodology in this case, however, is that the in-depth results or lessons generated are usually highly context-specific and thus brings the challenge of transferability of findings to other settings, as different health care systems and different indications are often not comparable. Project INTEGRATE, a European Commission-funded project, has been designed to overcome these problems; it looks into four chronic conditions in different European settings, under a common methodology framework (taking a mixed-methods approach to try to overcome the issue of context specificity and limited transferability. The common methodological framework described in this paper seeks to bring together the different case study findings in a way that key lessons may be derived and transferred between countries, contexts and patient-groups, where integrated care is delivered in order to provide insight into generalisability and build on existing evidence in this field.Methodology: To compare the different integrated care experiences, a mixed-methods approach has

  1. Fuzzy forecasting based on fuzzy-trend logical relationship groups.

    Science.gov (United States)

    Chen, Shyi-Ming; Wang, Nai-Yi

    2010-10-01

    In this paper, we present a new method to predict the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) based on fuzzy-trend logical relationship groups (FTLRGs). The proposed method divides fuzzy logical relationships into FTLRGs based on the trend of adjacent fuzzy sets appearing in the antecedents of fuzzy logical relationships. First, we apply an automatic clustering algorithm to cluster the historical data into intervals of different lengths. Then, we define fuzzy sets based on these intervals of different lengths. Then, the historical data are fuzzified into fuzzy sets to derive fuzzy logical relationships. Then, we divide the fuzzy logical relationships into FTLRGs for forecasting the TAIEX. Moreover, we also apply the proposed method to forecast the enrollments and the inventory demand, respectively. The experimental results show that the proposed method gets higher average forecasting accuracy rates than the existing methods.

  2. Fuzzy controller for an uncertain dynamical system

    DEFF Research Database (Denmark)

    Kulczycki, P.; Wisniewski, Rafal

    2002-01-01

    The present paper deals with the time-optimal control for mechanical systems with uncertain load. A fuzzy approach is used in the design of suboptimal feedback controllers, robust with respect to the load. Statistical kernel estimators are used for the specification of crucial parameters. The met......The present paper deals with the time-optimal control for mechanical systems with uncertain load. A fuzzy approach is used in the design of suboptimal feedback controllers, robust with respect to the load. Statistical kernel estimators are used for the specification of crucial parameters....... The methodology proposed in this work may be easily adopted to other modeling uncertainties of mechanical systems, e.g. motion resistance....

  3. Efficient fuzzy Bayesian inference algorithms for incorporating expert knowledge in parameter estimation

    Science.gov (United States)

    Rajabi, Mohammad Mahdi; Ataie-Ashtiani, Behzad

    2016-05-01

    Bayesian inference has traditionally been conceived as the proper framework for the formal incorporation of expert knowledge in parameter estimation of groundwater models. However, conventional Bayesian inference is incapable of taking into account the imprecision essentially embedded in expert provided information. In order to solve this problem, a number of extensions to conventional Bayesian inference have been introduced in recent years. One of these extensions is 'fuzzy Bayesian inference' which is the result of integrating fuzzy techniques into Bayesian statistics. Fuzzy Bayesian inference has a number of desirable features which makes it an attractive approach for incorporating expert knowledge in the parameter estimation process of groundwater models: (1) it is well adapted to the nature of expert provided information, (2) it allows to distinguishably model both uncertainty and imprecision, and (3) it presents a framework for fusing expert provided information regarding the various inputs of the Bayesian inference algorithm. However an important obstacle in employing fuzzy Bayesian inference in groundwater numerical modeling applications is the computational burden, as the required number of numerical model simulations often becomes extremely exhaustive and often computationally infeasible. In this paper, a novel approach of accelerating the fuzzy Bayesian inference algorithm is proposed which is based on using approximate posterior distributions derived from surrogate modeling, as a screening tool in the computations. The proposed approach is first applied to a synthetic test case of seawater intrusion (SWI) in a coastal aquifer. It is shown that for this synthetic test case, the proposed approach decreases the number of required numerical simulations by an order of magnitude. Then the proposed approach is applied to a real-world test case involving three-dimensional numerical modeling of SWI in Kish Island, located in the Persian Gulf. An expert

  4. Intuitionistic Trapezoidal Fuzzy Group Decision-Making Based on Prospect Choquet Integral Operator and Grey Projection Pursuit Dynamic Cluster

    Directory of Open Access Journals (Sweden)

    Jiahang Yuan

    2017-01-01

    Full Text Available In consideration of the interaction among attributes and the influence of decision makers’ risk attitude, this paper proposes an intuitionistic trapezoidal fuzzy aggregation operator based on Choquet integral and prospect theory. With respect to a multiattribute group decision-making problem, the prospect value functions of intuitionistic trapezoidal fuzzy numbers are aggregated by the proposed operator; then a grey relation-projection pursuit dynamic cluster method is developed to obtain the ranking of alternatives; the firefly algorithm is used to optimize the objective function of projection for obtaining the best projection direction of grey correlation projection values, and the grey correlation projection values are evaluated, which are applied to classify, rank, and prefer the alternatives. Finally, an illustrative example is taken in the present study to make the proposed method comprehensible.

  5. Development of a fuzzy logic method to build objective functions in optimization problems: application to BWR fuel lattice design

    International Nuclear Information System (INIS)

    Martin-del-Campo, C.; Francois, J.L.; Barragan, A.M.; Palomera, M.A.

    2005-01-01

    In this paper we develop a methodology based on the use of the Fuzzy Logic technique to build multi-objective functions to be used in optimization processes applied to in-core nuclear fuel management. As an example, we selected the problem of determining optimal radial fuel enrichment and gadolinia distributions in a typical 'Boiling Water Reactor (BWR)' fuel lattice. The methodology is based on the use of the mathematical capability of Fuzzy Logic to model nonlinear functions of arbitrary complexity. The utility of Fuzzy Logic is to map an input space into an output space, and the primary mechanism for doing this is a list of if-then statements called rules. The rules refer to variables and adjectives that describe those variables and, the Fuzzy Logic technique interprets the values in the input vectors and, based on the set of rules assigns values to the output vector. The methodology was developed for the radial optimization of a BWR lattice where the optimization algorithm employed is Tabu Search. The global objective is to find the optimal distribution of enrichments and burnable poison concentrations in a 10*10 BWR lattice. In order to do that, a fuzzy control inference system was developed using the Fuzzy Logic Toolbox of Matlab and it has been linked to the Tabu Search optimization process. Results show that Tabu Search combined with Fuzzy Logic performs very well, obtaining lattices with optimal fuel utilization. (authors)

  6. A fuzzy levelised energy cost method for renewable energy technology assessment

    International Nuclear Information System (INIS)

    Wright, Daniel G.; Dey, Prasanta K.; Brammer, John G.

    2013-01-01

    Renewable energy project development is highly complex and success is by no means guaranteed. Decisions are often made with approximate or uncertain information yet the current methods employed by decision-makers do not necessarily accommodate this. Levelised energy costs (LEC) are one such commonly applied measure utilised within the energy industry to assess the viability of potential projects and inform policy. The research proposes a method for achieving this by enhancing the traditional discounting LEC measure with fuzzy set theory. Furthermore, the research develops the fuzzy LEC (F-LEC) methodology to incorporate the cost of financing a project from debt and equity sources. Applied to an example bioenergy project, the research demonstrates the benefit of incorporating fuzziness for project viability, optimal capital structure and key variable sensitivity analysis decision-making. The proposed method contributes by incorporating uncertain and approximate information to the widely utilised LEC measure and by being applicable to a wide range of energy project viability decisions. -- Highlights: •Proposes a fuzzy levelised energy cost (F-LEC) methodology to support energy project development. •Incorporates the terms and cost of project finance into the F-LEC method. •Applies the F-LEC method to an example bioenergy project development case

  7. Applying fuzzy integral for evaluating intensity of knowledge work in jobs

    Directory of Open Access Journals (Sweden)

    Jalil Heidary Dahooie

    2013-10-01

    Full Text Available In this article, a framework is proposed to define and identify knowledge work intensity in jobs, quantitatively. For determining the Knowledge Work Intensity Score (KWIS of a job, it is supposed that the job comprises some tasks and KWIS of the job is determined based on knowledge intensity of these tasks. Functional Job Analysis (FJA method is applied to determine tasks of jobs and then Task’s Knowledge Intensity Score (TKIS is computed by using Fuzzy integral method. Besides, importance weight and time weight of tasks are determined by utilizing appropriate methods. Finally, KWIS is calculated by a formula composed of tasks’ TKISs and the weights. For evaluating applicability of the framework, it is applied to calculate KWISs of two jobs (Deputy of Finance and service, Laboratory technician.

  8. Integrating Geographical Information Systems, Fuzzy Logic and Analytical Hierarchy Process in Modelling Optimum Sites for Locating Water Reservoirs. A Case Study of the Debub District in Eritrea

    Directory of Open Access Journals (Sweden)

    Rodney G. Tsiko

    2011-03-01

    Full Text Available The aim of this study was to model water reservoir site selection for a real world application in the administrative district of Debub, Eritrea. This is a region were scarcity of water is a fundamental problem. Erratic rainfall, drought and unfavourable hydro-geological characteristics exacerbates the region’s water supply. Consequently, the population of Debub is facing severe water shortages and building reservoirs has been promoted as a possible solution to meet the future demand of water supply. This was the most powerful motivation to identify candidate sites for locating water reservoirs. A number of conflicting qualitative and quantitative criteria exist for evaluating alternative sites. Decisions regarding criteria are often accompanied by ambiguities and vagueness. This makes fuzzy logic a more natural approach to this kind of Multi-criteria Decision Analysis (MCDA problems. This paper proposes a combined two-stage MCDA methodology. The first stage involved utilizing the most simplistic type of data aggregation techniques known as Boolean Intersection or logical AND to identify areas restricted by environmental and hydrological constraints and therefore excluded from further study. The second stage involved integrating fuzzy logic with the Analytic Hierarchy Process (AHP to identify optimum and back-up candidate water reservoir sites in the area designated for further study.

  9. Integration of infrared thermography into various maintenance methodologies

    Science.gov (United States)

    Morgan, William T.

    1993-04-01

    Maintenance methodologies are in developmental stages throughout the world as global competitiveness drives all industries to improve operational efficiencies. Rapid progress in technical advancements has added an additional strain on maintenance organizations to progressively change. Accompanying needs for advanced training and documentation is the demand for utilization of various analytical instruments and quantitative methods. Infrared thermography is one of the primary elements of engineered approaches to maintenance. Current maintenance methodologies can be divided into six categories; Routine ('Breakdown'), Preventive, Predictive, Proactive, Reliability-Based, and Total Productive (TPM) maintenance. Each of these methodologies have distinctive approaches to achieving improved operational efficiencies. Popular though is that infrared thermography is a Predictive maintenance tool. While this is true, it is also true that it can be effectively integrated into each of the maintenance methodologies for achieving desired results. The six maintenance strategies will be defined. Infrared applications integrated into each will be composed in tabular form.

  10. A fuzzy multi-criteria decision-making model for CCHP systems driven by different energy sources

    International Nuclear Information System (INIS)

    Jing Youyin; Bai He; Wang Jiangjiang

    2012-01-01

    Because of its energy-saving and pollutant emission reduction potentials, combined cooling, heating and power (CCHP) system has been widely used in different kinds of buildings to solve building-related energetic problems and environmental issues. As various kinds of clean energy and renewable energy have been focused and applied to CCHP systems, it is urgent to find a practical decision making methodology for CCHP systems driven by different energy sources. In this paper, an evaluation model which integrates fuzzy theory with multi-criteria decision making process is proposed to assess the comprehensive benefits of CCHP systems from technology, economic, society and environment criterions. Grey relation analysis and combination weighting method are also employed to compare the integrated performances of CCHP systems driven by natural gas, fuel cell, biomass energy and combined gas-steam cycle respectively with a separation production system. Finally, a baseline residential building in Beijing, China is selected as a case to obtain the optimal CCHP system alternative. The results indicate that gas–steam combined cycle CCHP system is the optimum scheme among the five options. - Graphical abstract: A fuzzy multi-criteria decision-making model combined with combination weighting method and grey system theory is presented in this paper, which can be used to evaluate CCHP systems driven by different energy sources from technology, economic, environment and society criteria. Highlights: ► The integrated benefits of CCHP systems driven by different energy sources are evaluated. ► A fuzzy multi-criteria model combined with combination weighting method is proposed. ► Environment evaluation criteria play an important role in the decision-making process. ► CCHP system driven by gas–steam combined cycle is the optimal alternative.

  11. A pertinent approach to solve nonlinear fuzzy integro-differential equations.

    Science.gov (United States)

    Narayanamoorthy, S; Sathiyapriya, S P

    2016-01-01

    Fuzzy integro-differential equations is one of the important parts of fuzzy analysis theory that holds theoretical as well as applicable values in analytical dynamics and so an appropriate computational algorithm to solve them is in essence. In this article, we use parametric forms of fuzzy numbers and suggest an applicable approach for solving nonlinear fuzzy integro-differential equations using homotopy perturbation method. A clear and detailed description of the proposed method is provided. Our main objective is to illustrate that the construction of appropriate convex homotopy in a proper way leads to highly accurate solutions with less computational work. The efficiency of the approximation technique is expressed via stability and convergence analysis so as to guarantee the efficiency and performance of the methodology. Numerical examples are demonstrated to verify the convergence and it reveals the validity of the presented numerical technique. Numerical results are tabulated and examined by comparing the obtained approximate solutions with the known exact solutions. Graphical representations of the exact and acquired approximate fuzzy solutions clarify the accuracy of the approach.

  12. Uncovering transcriptional interactions via an adaptive fuzzy logic approach

    Directory of Open Access Journals (Sweden)

    Chen Chung-Ming

    2009-12-01

    Full Text Available Abstract Background To date, only a limited number of transcriptional regulatory interactions have been uncovered. In a pilot study integrating sequence data with microarray data, a position weight matrix (PWM performed poorly in inferring transcriptional interactions (TIs, which represent physical interactions between transcription factors (TF and upstream sequences of target genes. Inferring a TI means that the promoter sequence of a target is inferred to match the consensus sequence motifs of a potential TF, and their interaction type such as AT or RT is also predicted. Thus, a robust PWM (rPWM was developed to search for consensus sequence motifs. In addition to rPWM, one feature extracted from ChIP-chip data was incorporated to identify potential TIs under specific conditions. An interaction type classifier was assembled to predict activation/repression of potential TIs using microarray data. This approach, combining an adaptive (learning fuzzy inference system and an interaction type classifier to predict transcriptional regulatory networks, was named AdaFuzzy. Results AdaFuzzy was applied to predict TIs using real genomics data from Saccharomyces cerevisiae. Following one of the latest advances in predicting TIs, constrained probabilistic sparse matrix factorization (cPSMF, and using 19 transcription factors (TFs, we compared AdaFuzzy to four well-known approaches using over-representation analysis and gene set enrichment analysis. AdaFuzzy outperformed these four algorithms. Furthermore, AdaFuzzy was shown to perform comparably to 'ChIP-experimental method' in inferring TIs identified by two sets of large scale ChIP-chip data, respectively. AdaFuzzy was also able to classify all predicted TIs into one or more of the four promoter architectures. The results coincided with known promoter architectures in yeast and provided insights into transcriptional regulatory mechanisms. Conclusion AdaFuzzy successfully integrates multiple types of

  13. Generalized coherent state approach to star products and applications to the fuzzy sphere

    International Nuclear Information System (INIS)

    Alexanian, G.; Pinzul, A.; Stern, A.

    2001-01-01

    We construct a star product associated with an arbitrary two-dimensional Poisson structure using generalized coherent states on the complex plane. From our approach one easily recovers the star product for the fuzzy torus, and also one for the fuzzy sphere. For the latter we need to define the 'fuzzy' stereographic projection to the plane and the fuzzy sphere integration measure, which in the commutative limit reduce to the usual formulae for the sphere

  14. On the Fuzzy Convergence

    Directory of Open Access Journals (Sweden)

    Abdul Hameed Q. A. Al-Tai

    2011-01-01

    Full Text Available The aim of this paper is to introduce and study the fuzzy neighborhood, the limit fuzzy number, the convergent fuzzy sequence, the bounded fuzzy sequence, and the Cauchy fuzzy sequence on the base which is adopted by Abdul Hameed (every real number r is replaced by a fuzzy number r¯ (either triangular fuzzy number or singleton fuzzy set (fuzzy point. And then, we will consider that some results respect effect of the upper sequence on the convergent fuzzy sequence, the bounded fuzzy sequence, and the Cauchy fuzzy sequence.

  15. Credit Scoring by Fuzzy Support Vector Machines with a Novel Membership Function

    Directory of Open Access Journals (Sweden)

    Jian Shi

    2016-11-01

    Full Text Available Due to the recent financial crisis and European debt crisis, credit risk evaluation has become an increasingly important issue for financial institutions. Reliable credit scoring models are crucial for commercial banks to evaluate the financial performance of clients and have been widely studied in the fields of statistics and machine learning. In this paper a novel fuzzy support vector machine (SVM credit scoring model is proposed for credit risk analysis, in which fuzzy membership is adopted to indicate different contribution of each input point to the learning of SVM classification hyperplane. Considering the methodological consistency, support vector data description (SVDD is introduced to construct the fuzzy membership function and to reduce the effect of outliers and noises. The SVDD-based fuzzy SVM model is tested against the traditional fuzzy SVM on two real-world datasets and the research results confirm the effectiveness of the presented method.

  16. AN INTEGRATED METHODOLOGY FOR CUSTOMER RELATIONSHIP MANAGEMENT CUSTOMIZATION

    Directory of Open Access Journals (Sweden)

    Ricardo Colomo Palacios

    2008-02-01

    Full Text Available The importance and presence of technological solutions in organizations supporting CRM are a vital business fact from the late nineties. Presently, the manufacturers figure in the market has dramatically decreased because of continuous takeovers and merges, but it has on the other hand gained momentum because of the sudden open-source and on-demand solutions appearance. In this scope, a unified methodology centered on CRM solutions is of paramount importance since it has traditionally been linked to either system integration or overall solution design. Based on the two de-facto complementary standards for the implementation and development of Information Systems, namely the ESA and Dyché CRM systems implementation methodology, in this paper, we provide a CRM business solutions customization methodology which pertains independently to the integration and tool maker perspective.

  17. Safety analysis and synthesis using fuzzy sets and evidential reasoning

    International Nuclear Information System (INIS)

    Wang, J.; Yang, J.B.; Sen, P.

    1995-01-01

    This paper presents a new methodology for safety analysis and synthesis of a complex engineering system with a structure that is capable of being decomposed into a hierarchy of levels. In this methodology, fuzzy set theory is used to describe each failure event and an evidential reasoning approach is then employed to synthesise the information thus produced to assess the safety of the whole system. Three basic parameters--failure likelihood, consequence severity and failure consequence probability, are used to analyse a failure event. These three parameters are described by linguistic variables which are characterised by a membership function to the defined categories. As safety can also be clearly described by linguistic variables referred to as the safety expressions, the obtained fuzzy safety score can be mapped back to the safety expressions which are characterised by membership functions over the same categories. This mapping results in the identification of the safety of each failure event in terms of the degree to which the fuzzy safety score belongs to each of the safety expressions. Such degrees represent the uncertainty in safety evaluations and can be synthesised using an evidential reasoning approach so that the safety of the whole system can be evaluated in terms of these safety expressions. Finally, a practical engineering example is presented to demonstrate the proposed safety analysis and synthesis methodology

  18. Fuzzy logic system for BBT based fertility prediction | Yazed | Journal ...

    African Journals Online (AJOL)

    ... been obtained with the accuracy of 95 % and 80 respectively. Besides, this prediction system using fuzzy logic could improve the current practice in the FAM technique by integrating it with an Internet of Things (IoT) technology for automatic BBT charting and monitoring. Keywords: family planning; fertility; BBT; fuzzy logic.

  19. Stability Analysis of Interconnected Fuzzy Systems Using the Fuzzy Lyapunov Method

    Directory of Open Access Journals (Sweden)

    Ken Yeh

    2010-01-01

    Full Text Available The fuzzy Lyapunov method is investigated for use with a class of interconnected fuzzy systems. The interconnected fuzzy systems consist of J interconnected fuzzy subsystems, and the stability analysis is based on Lyapunov functions. Based on traditional Lyapunov stability theory, we further propose a fuzzy Lyapunov method for the stability analysis of interconnected fuzzy systems. The fuzzy Lyapunov function is defined in fuzzy blending quadratic Lyapunov functions. Some stability conditions are derived through the use of fuzzy Lyapunov functions to ensure that the interconnected fuzzy systems are asymptotically stable. Common solutions can be obtained by solving a set of linear matrix inequalities (LMIs that are numerically feasible. Finally, simulations are performed in order to verify the effectiveness of the proposed stability conditions in this paper.

  20. Stochastic Optimal Estimation with Fuzzy Random Variables and Fuzzy Kalman Filtering

    Institute of Scientific and Technical Information of China (English)

    FENG Yu-hu

    2005-01-01

    By constructing a mean-square performance index in the case of fuzzy random variable, the optimal estimation theorem for unknown fuzzy state using the fuzzy observation data are given. The state and output of linear discrete-time dynamic fuzzy system with Gaussian noise are Gaussian fuzzy random variable sequences. An approach to fuzzy Kalman filtering is discussed. Fuzzy Kalman filtering contains two parts: a real-valued non-random recurrence equation and the standard Kalman filtering.

  1. A fuzzy approach to a multiple criteria and Geographical Information System for decision support on suitable locations for biogas plants

    DEFF Research Database (Denmark)

    Franco, Camilo; Bojesen, Mikkel; Hougaard, Jens Leth

    2015-01-01

    The purpose of this paper is to model the multi-criteria decision problem of identifying the most suitable facility locations for biogas plants under an integrated decision support methodology. Here the Geographical Information System (GIS) is used for measuring the attributes of the alternatives...... according to a given set of criteria. Measurements are taken in interval form, expressing the natural imprecision of common data, and the Fuzzy Weighted Overlap Dominance (FWOD) procedure is applied for aggregating and exploiting this kind of data, obtaining suitability degrees for every alternative...... suitable sites for building biogas plants. We show that the FWOD relevance-ranking procedure can also be successfully applied over the outcomes of different decision makers, in case a unique social solution is required to exist. The proposed methodology can be used under an integrated decision support...

  2. Performance evaluation of enterprise architecture using fuzzy sequence diagram

    Directory of Open Access Journals (Sweden)

    Mohammad Atasheneh

    2014-01-01

    Full Text Available Developing an Enterprise Architecture is a complex task and to control the complexity of the regulatory framework we need to measure the relative performance of one system against other available systems. On the other hand, enterprise architecture cannot be organized without the use of a logical structure. The framework provides a logical structure for classifying architectural output. Among the common architectural framework, the C4ISR framework and methodology of the product is one of the most popular techniques. In this paper, given the existing uncertainties in system development and information systems, a new version of UML called Fuzzy-UML is proposed for enterprise architecture development based on fuzzy Petri nets. In addition, the performance of the system is also evaluated based on Fuzzy sequence diagram.

  3. Modeling and control of an unstable system using probabilistic fuzzy inference system

    Directory of Open Access Journals (Sweden)

    Sozhamadevi N.

    2015-09-01

    Full Text Available A new type Fuzzy Inference System is proposed, a Probabilistic Fuzzy Inference system which model and minimizes the effects of statistical uncertainties. The blend of two different concepts, degree of truth and probability of truth in a unique framework leads to this new concept. This combination is carried out both in Fuzzy sets and Fuzzy rules, which gives rise to Probabilistic Fuzzy Sets and Probabilistic Fuzzy Rules. Introducing these probabilistic elements, a distinctive probabilistic fuzzy inference system is developed and this involves fuzzification, inference and output processing. This integrated approach accounts for all of the uncertainty like rule uncertainties and measurement uncertainties present in the systems and has led to the design which performs optimally after training. In this paper a Probabilistic Fuzzy Inference System is applied for modeling and control of a highly nonlinear, unstable system and also proved its effectiveness.

  4. Fuzzy interaction modelling for participants in innovation development: approaches and examples

    Directory of Open Access Journals (Sweden)

    CHERNOV Vladimir

    2018-01-01

    Full Text Available The article considers the interaction problems of the participants in innovative development at the regional level. Mathematical approaches and formulations for mode lling, such as the interaction on the basis of game approaches and the theory of fuzzy sets, have been proposed. In particular, the interaction model of innovative participants in the region, considered as a fuzzy coalition game, is presented. Its theoretical justification and an example of practical calculations are given. Further, the methodology of interaction modelling is considered , taking into account the motives of the participants in innovative development when forming fuzzy coalitions. An example of the corresponding calculations is also given. Also, the interaction model of "state-regions" in the interpretation of the fuzzy hierarchical game is proposed and described. The features of its solution are described and an example of calculations is presented.

  5. A new approach to analyze strategy map using an integrated BSC and FUZZY DEMATEL

    Directory of Open Access Journals (Sweden)

    Seyed Abdollah Heydariyeh

    2012-01-01

    Full Text Available Today, with ever-increasing competition in global economic conditions, the necessity of effective implementation of strategy map has become an inevitable and necessary. The strategy map represents a general and structured framework for strategic objectives and plays an important role in forming competitive advantages for organizations. It is important to find important factors influencing strategy map and prioritize them based on suitable factors. In this paper, we propose an integration of BSC and Fuzzy DEMATEL technique to rank different items influencing strategy of a production plan. The proposed technique is implemented for real-world case study of glass production.

  6. RISIKO RANTAI PASOK AGROINDUSTRI SALAK MENGGUNAKAN FUZZY FMEA

    Directory of Open Access Journals (Sweden)

    Ina Amanatur Risqiyah

    2017-03-01

    Full Text Available This research aims to identify and evaluate the risks of the supply chain management of salacca at the SME of Ambudi Makmur using fuzzy logic. In this research, identification of the supply chain risk was performed on each subject of supply chain using survey method. Furthermore, the results of supply chain risk in Ambudi Makmur were evaluated using FMEA’s fuzzy logic, a methodology using fuzzy logic to identify the problems or causes of failures that have occurred by consideration of criteria of Severity (S, Occurrence (O, and Detection (D. The identification results show that there are eight risk factors at the farm level, 11 risk factors, at the agribusiness industry level of SME of Ambudi Makmur, 4 risk factors at distributor level and 3 risk factors at the retailer level. The largest risk factor is in agribusiness industry, and the most dominant is on “make”. Based on the Fuzzy Risk Priority Number (FRPN, the first rank of risks of salacca supply chain is delay. Thus, this risk is the first priority that must be solved by Ambudi Makmur. Keywords: Fuzzy FMEA, risk supply chain, supply chainABSTRAKPenelitian ini bertujuan mengidentifikasi dan mengevalusi risiko rantai pasok salak di UKM Ambudi Makmur Bangkalan menggunakan logika fuzzy. Pada penelitian ini identifikasi risiko rantai pasok dilakukan pada tiap pelaku rantai pasok menggunakan metode survei. Selanjutnya, hasil identifikasi risiko rantai pasok pada UKM Ambudi Makmur dievaluasi menggunakan logika fuzzy FMEA.  Fuzzy FMEA merupakan metodologi yang memakai logika fuzzy dalam mengidentifikasi permasalahan atau penyebab kegagalan yang terjadi melalui pertimbangan kriteria severity (S, occurence (O, dan detection (D. Hasil identifikasi menunjukkan bahwa pada tingkat petani terdapat delapan faktor risiko, pada tingkat usaha agroindustri, yaitu UKM Ambudi Makmur terdapat 11 faktor risiko, pada tingkat distributor terdapat empat faktor risiko, pada tingkat retailer terdapat tiga

  7. A Comparative Approach for Ranking Contaminated Sites Based on the Risk Assessment Paradigm Using Fuzzy PROMETHEE

    Science.gov (United States)

    Zhang, Kejiang; Kluck, Cheryl; Achari, Gopal

    2009-11-01

    A ranking system for contaminated sites based on comparative risk methodology using fuzzy Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) was developed in this article. It combines the concepts of fuzzy sets to represent uncertain site information with the PROMETHEE, a subgroup of Multi-Criteria Decision Making (MCDM) methods. Criteria are identified based on a combination of the attributes (toxicity, exposure, and receptors) associated with the potential human health and ecological risks posed by contaminated sites, chemical properties, site geology and hydrogeology and contaminant transport phenomena. Original site data are directly used avoiding the subjective assignment of scores to site attributes. When the input data are numeric and crisp the PROMETHEE method can be used. The Fuzzy PROMETHEE method is preferred when substantial uncertainties and subjectivities exist in site information. The PROMETHEE and fuzzy PROMETHEE methods are both used in this research to compare the sites. The case study shows that this methodology provides reasonable results.

  8. Hydro-environmental management of groundwater resources: A fuzzy-based multi-objective compromise approach

    Science.gov (United States)

    Alizadeh, Mohammad Reza; Nikoo, Mohammad Reza; Rakhshandehroo, Gholam Reza

    2017-08-01

    Sustainable management of water resources necessitates close attention to social, economic and environmental aspects such as water quality and quantity concerns and potential conflicts. This study presents a new fuzzy-based multi-objective compromise methodology to determine the socio-optimal and sustainable policies for hydro-environmental management of groundwater resources, which simultaneously considers the conflicts and negotiation of involved stakeholders, uncertainties in decision makers' preferences, existing uncertainties in the groundwater parameters and groundwater quality and quantity issues. The fuzzy multi-objective simulation-optimization model is developed based on qualitative and quantitative groundwater simulation model (MODFLOW and MT3D), multi-objective optimization model (NSGA-II), Monte Carlo analysis and Fuzzy Transformation Method (FTM). Best compromise solutions (best management policies) on trade-off curves are determined using four different Fuzzy Social Choice (FSC) methods. Finally, a unanimity fallback bargaining method is utilized to suggest the most preferred FSC method. Kavar-Maharloo aquifer system in Fars, Iran, as a typical multi-stakeholder multi-objective real-world problem is considered to verify the proposed methodology. Results showed an effective performance of the framework for determining the most sustainable allocation policy in groundwater resource management.

  9. Model Integrating Fuzzy Argument with Neural Network Enhancing the Performance of Active Queue Management

    Directory of Open Access Journals (Sweden)

    Nguyen Kim Quoc

    2015-08-01

    Full Text Available The bottleneck control by active queue management mechanisms at network nodes is essential. In recent years, some researchers have used fuzzy argument to improve the active queue management mechanisms to enhance the network performance. However, the projects using the fuzzy controller depend heavily on professionals and their parameters cannot be updated according to changes in the network, so the effectiveness of this mechanism is not high. Therefore, we propose a model combining the fuzzy controller with neural network (FNN to overcome the limitations above. Results of the training of the neural networks will find the optimal parameters for the adaptive fuzzy controller well to changes of the network. This improves the operational efficiency of the active queue management mechanisms at network nodes.

  10. Estimation of Fuzzy Measures Using Covariance Matrices in Gaussian Mixtures

    Directory of Open Access Journals (Sweden)

    Nishchal K. Verma

    2012-01-01

    Full Text Available This paper presents a novel computational approach for estimating fuzzy measures directly from Gaussian mixtures model (GMM. The mixture components of GMM provide the membership functions for the input-output fuzzy sets. By treating consequent part as a function of fuzzy measures, we derived its coefficients from the covariance matrices found directly from GMM and the defuzzified output constructed from both the premise and consequent parts of the nonadditive fuzzy rules that takes the form of Choquet integral. The computational burden involved with the solution of λ-measure is minimized using Q-measure. The fuzzy model whose fuzzy measures were computed using covariance matrices found in GMM has been successfully applied on two benchmark problems and one real-time electric load data of Indian utility. The performance of the resulting model for many experimental studies including the above-mentioned application is found to be better and comparable to recent available fuzzy models. The main contribution of this paper is the estimation of fuzzy measures efficiently and directly from covariance matrices found in GMM, avoiding the computational burden greatly while learning them iteratively and solving polynomial equations of order of the number of input-output variables.

  11. Fuzzy sets as extension of probabilistic models for evaluating human reliability

    International Nuclear Information System (INIS)

    Przybylski, F.

    1996-11-01

    On the base of a survey of established quantification methodologies for evaluating human reliability, a new computerized methodology was developed in which a differential consideration of user uncertainties is made. In this quantification method FURTHER (FUzzy Sets Related To Human Error Rate Prediction), user uncertainties are quantified separately from model and data uncertainties. As tools fuzzy sets are applied which, however, stay hidden to the method's user. The user in the quantification process only chooses an action pattern, performance shaping factors and natural language expressions. The acknowledged method HEART (Human Error Assessment and Reduction Technique) serves as foundation of the fuzzy set approach FURTHER. By means of this method, the selection of a basic task in connection with its basic error probability, the decision how correct the basic task's selection is, the selection of a peformance shaping factor, and the decision how correct the selection and how important the performance shaping factor is, were identified as aspects of fuzzification. This fuzzification is made on the base of data collection and information from literature as well as of the estimation by competent persons. To verify the ammount of additional information to be received by the usage of fuzzy sets, a benchmark session was accomplished. In this benchmark twelve actions were assessed by five test-persons. In case of the same degree of detail in the action modelling process, the bandwidths of the interpersonal evaluations decrease in FURTHER in comparison with HEART. The uncertainties of the single results could not be reduced up to now. The benchmark sessions conducted so far showed plausible results. A further testing of the fuzzy set approach by using better confirmed fuzzy sets can only be achieved in future practical application. Adequate procedures, however, are provided. (orig.) [de

  12. A DIFFERENT WEB-BASED GEOCODING SERVICE USING FUZZY TECHNIQUES

    Directory of Open Access Journals (Sweden)

    P. Pahlavani

    2015-12-01

    Full Text Available Geocoding – the process of finding position based on descriptive data such as address or postal code - is considered as one of the most commonly used spatial analyses. Many online map providers such as Google Maps, Bing Maps and Yahoo Maps present geocoding as one of their basic capabilities. Despite the diversity of geocoding services, users usually face some limitations when they use available online geocoding services. In existing geocoding services, proximity and nearness concept is not modelled appropriately as well as these services search address only by address matching based on descriptive data. In addition there are also some limitations in display searching results. Resolving these limitations can enhance efficiency of the existing geocoding services. This paper proposes the idea of integrating fuzzy technique with geocoding process to resolve these limitations. In order to implement the proposed method, a web-based system is designed. In proposed method, nearness to places is defined by fuzzy membership functions and multiple fuzzy distance maps are created. Then these fuzzy distance maps are integrated using fuzzy overlay technique for obtain the results. Proposed methods provides different capabilities for users such as ability to search multi-part addresses, searching places based on their location, non-point representation of results as well as displaying search results based on their priority.

  13. Environmental impact assessment for energy pathways: an integrated methodology

    International Nuclear Information System (INIS)

    Sommereux-Blanc, Isabelle

    2010-01-01

    This document presents the synthesis of my research work contributing to the development of an integrated methodology of environmental impact assessment for energy pathways. In the context of world globalization, environmental impact assessments issues are highly linked with the following questioning: Which environmental impacts? for which demand? at which location? at which temporal scale? My work is built upon the definition of a conceptual framework able to handle these issues and upon its progressive implementation. The integration of the spatial and temporal issues within the methodology are key elements. Fundamental cornerstones of this framework are presented along the DPSIR concept (Driving forces, Pressures, State, Impacts, Responses). They cover a comprehensive analysis of the limits and the relevance of life cycle analysis and the development of a geo-spatialized environmental performance approach for an electrical production pathway. Perspectives linked with the development of this integrated methodology are detailed for energy pathways. (author)

  14. Indoor signal attenuation assessment via fuzzy logic

    Directory of Open Access Journals (Sweden)

    Alexandre de Assis Mota

    2011-09-01

    Full Text Available This work focuses on the analysis of signal´s attenuation in indoor environments using a fuzzy logic approach based on the Shadowing Signal Propagation Model (SSPM. The SSPM allows the characterization of the attenuation caused by the environment through the ? parameter present in this model. In addition to this, the Fuzzy Logic provides a form of approximate reasoning that allows the treatment of problems with incomplete, vague and imprecise information. Also, it offers a simple way to obtain a possible solution for a problem using the heuristic knowledge about a particular situation. The results show that the methodology produced satisfactory results, close to the ones yielded by experimental methods.

  15. Complex Fuzzy Set-Valued Complex Fuzzy Measures and Their Properties

    Science.gov (United States)

    Ma, Shengquan; Li, Shenggang

    2014-01-01

    Let F*(K) be the set of all fuzzy complex numbers. In this paper some classical and measure-theoretical notions are extended to the case of complex fuzzy sets. They are fuzzy complex number-valued distance on F*(K), fuzzy complex number-valued measure on F*(K), and some related notions, such as null-additivity, pseudo-null-additivity, null-subtraction, pseudo-null-subtraction, autocontionuous from above, autocontionuous from below, and autocontinuity of the defined fuzzy complex number-valued measures. Properties of fuzzy complex number-valued measures are studied in detail. PMID:25093202

  16. On logical, algebraic, and probabilistic aspects of fuzzy set theory

    CERN Document Server

    Mesiar, Radko

    2016-01-01

    The book is a collection of contributions by leading experts, developed around traditional themes discussed at the annual Linz Seminars on Fuzzy Set Theory. The different chapters have been written by former PhD students, colleagues, co-authors and friends of Peter Klement, a leading researcher and the organizer of the Linz Seminars on Fuzzy Set Theory. The book also includes advanced findings on topics inspired by Klement’s research activities, concerning copulas, measures and integrals, as well as aggregation problems. Some of the chapters reflect personal views and controversial aspects of traditional topics, while others deal with deep mathematical theories, such as the algebraic and logical foundations of fuzzy set theory and fuzzy logic. Originally thought as an homage to Peter Klement, the book also represents an advanced reference guide to the mathematical theories related to fuzzy logic and fuzzy set theory with the potential to stimulate important discussions on new research directions in the fiel...

  17. Integrating System Dynamic and Fuzzy Logic for Economic Assessment of BOT Projects

    Directory of Open Access Journals (Sweden)

    Farnad Nasirzadeh

    2016-03-01

    Full Text Available The selection of the most appropriate project for the investment is one of the most important decisions that should be made by the private investors. This problem is of vital importance in BOT projects, where the total investment as well as the investor's profit should be recovered by the project's income. There are several approaches proposed by the researchers to determine the best economical project in comparison to other projects. The previous researches, however, faced with some major defects. As an example, the effects of various factors affecting the project evaluation process as well as the existing risks and uncertainties are not taken into account. In this research, economic assessment of BOT projects is performed by integrating system dynamic simulation approach and fuzzy logic. For this purpose, first the project's NPV is modeled considering all the influencing factors qualitatively. The relationships that exist between different factors are then determined and the quantitative model is built. Using the developed model, the value of NPV is simulated considering the effects of all the influencing factors and the existing uncertainties. Finally, the value of project's NPV is determined as a triangular fuzzy number. Finally, the best alternative project is selected by comparing the simulated values of NPV. To evaluate the capabilities and performance of the proposed model, the project economical evaluation is performed for two highway projects and the best project is selected.

  18. Hierarchical type-2 fuzzy aggregation of fuzzy controllers

    CERN Document Server

    Cervantes, Leticia

    2016-01-01

    This book focuses on the fields of fuzzy logic, granular computing and also considering the control area. These areas can work together to solve various control problems, the idea is that this combination of areas would enable even more complex problem solving and better results. In this book we test the proposed method using two benchmark problems: the total flight control and the problem of water level control for a 3 tank system. When fuzzy logic is used it make it easy to performed the simulations, these fuzzy systems help to model the behavior of a real systems, using the fuzzy systems fuzzy rules are generated and with this can generate the behavior of any variable depending on the inputs and linguistic value. For this reason this work considers the proposed architecture using fuzzy systems and with this improve the behavior of the complex control problems.

  19. Design and optimization of fuzzy-PID controller for the nuclear reactor power control

    International Nuclear Information System (INIS)

    Liu Cheng; Peng Jinfeng; Zhao Fuyu; Li Chong

    2009-01-01

    This paper introduces a fuzzy proportional-integral-derivative (fuzzy-PID) control strategy, and applies it to the nuclear reactor power control system. At the fuzzy-PID control strategy, the fuzzy logic controller (FLC) is exploited to extend the finite sets of PID gains to the possible combinations of PID gains in stable region and the genetic algorithm to improve the 'extending' precision through quadratic optimization for the membership function (MF) of the FLC. Thus the FLC tunes the gains of PID controller to adapt the model changing with the power. The fuzzy-PID has been designed and simulated to control the reactor power. The simulation results show the favorable performance of the fuzzy-PID controller.

  20. Fuzzy Stabilization for Nonlinear Discrete Ship Steering Stochastic Systems Subject to State Variance and Passivity Constraints

    Directory of Open Access Journals (Sweden)

    Wen-Jer Chang

    2014-01-01

    Full Text Available For nonlinear discrete-time stochastic systems, a fuzzy controller design methodology is developed in this paper subject to state variance constraint and passivity constraint. According to fuzzy model based control technique, the nonlinear discrete-time stochastic systems considered in this paper are represented by the discrete-time Takagi-Sugeno fuzzy models with multiplicative noise. Employing Lyapunov stability theory, upper bound covariance control theory, and passivity theory, some sufficient conditions are derived to find parallel distributed compensation based fuzzy controllers. In order to solve these sufficient conditions, an iterative linear matrix inequality algorithm is applied based on the linear matrix inequality technique. Finally, the fuzzy stabilization problem for nonlinear discrete ship steering stochastic systems is investigated in the numerical example to illustrate the feasibility and validity of proposed fuzzy controller design method.

  1. Fuzzy portfolio model with fuzzy-input return rates and fuzzy-output proportions

    Science.gov (United States)

    Tsaur, Ruey-Chyn

    2015-02-01

    In the finance market, a short-term investment strategy is usually applied in portfolio selection in order to reduce investment risk; however, the economy is uncertain and the investment period is short. Further, an investor has incomplete information for selecting a portfolio with crisp proportions for each chosen security. In this paper we present a new method of constructing fuzzy portfolio model for the parameters of fuzzy-input return rates and fuzzy-output proportions, based on possibilistic mean-standard deviation models. Furthermore, we consider both excess or shortage of investment in different economic periods by using fuzzy constraint for the sum of the fuzzy proportions, and we also refer to risks of securities investment and vagueness of incomplete information during the period of depression economics for the portfolio selection. Finally, we present a numerical example of a portfolio selection problem to illustrate the proposed model and a sensitivity analysis is realised based on the results.

  2. Combining fuzzy mathematics with fuzzy logic to solve business management problems

    Science.gov (United States)

    Vrba, Joseph A.

    1993-12-01

    Fuzzy logic technology has been applied to control problems with great success. Because of this, many observers fell that fuzzy logic is applicable only in the control arena. However, business management problems almost never deal with crisp values. Fuzzy systems technology--a combination of fuzzy logic, fuzzy mathematics and a graphical user interface--is a natural fit for developing software to assist in typical business activities such as planning, modeling and estimating. This presentation discusses how fuzzy logic systems can be extended through the application of fuzzy mathematics and the use of a graphical user interface to make the information contained in fuzzy numbers accessible to business managers. As demonstrated through examples from actual deployed systems, this fuzzy systems technology has been employed successfully to provide solutions to the complex real-world problems found in the business environment.

  3. Fuzzy Languages

    Science.gov (United States)

    Rahonis, George

    The theory of fuzzy recognizable languages over bounded distributive lattices is presented as a paradigm of recognizable formal power series. Due to the idempotency properties of bounded distributive lattices, the equality of fuzzy recognizable languages is decidable, the determinization of multi-valued automata is effective, and a pumping lemma exists. Fuzzy recognizable languages over finite and infinite words are expressively equivalent to sentences of the multi-valued monadic second-order logic. Fuzzy recognizability over bounded ℓ-monoids and residuated lattices is briefly reported. The chapter concludes with two applications of fuzzy recognizable languages to real world problems in medicine.

  4. Robust position control of induction motor using fuzzy logic control

    International Nuclear Information System (INIS)

    Kim, Sei Chan; Kim, Duk Hun; Yang, Seung Ho; Won, Chung Yuen

    1993-01-01

    In recent years, fuzzy logic or fuzzy set theory has reveived attention of a number of researchers in the area of power electronics and motion control. The paper describes a vector-controlled induction motor position servo drive where fuzzy control is used to get robustness against parameter variation and load torque disturbance effects. Both coarse and fine control with the help of look-up rule tables are used to improve transient response and system settling time. The performance characteristics are then compared with those of proportional-integral(PI) control. The simulation results clearly indicate the superiority of fuzzy control with larger number of rules. The fuzzy controller was implemented with a 16-bit microprocessor and tested in laboratory on a 3-hp IGBT inverter induction motor drive system. The test results verify the simulation performance. (Author)

  5. Multimodality Tumor Delineation and Predictive Modelling via Fuzzy-Fusion Deformable Models and Biological Potential Functions

    Science.gov (United States)

    Wasserman, Richard Marc

    The radiation therapy treatment planning (RTTP) process may be subdivided into three planning stages: gross tumor delineation, clinical target delineation, and modality dependent target definition. The research presented will focus on the first two planning tasks. A gross tumor target delineation methodology is proposed which focuses on the integration of MRI, CT, and PET imaging data towards the generation of a mathematically optimal tumor boundary. The solution to this problem is formulated within a framework integrating concepts from the fields of deformable modelling, region growing, fuzzy logic, and data fusion. The resulting fuzzy fusion algorithm can integrate both edge and region information from multiple medical modalities to delineate optimal regions of pathological tissue content. The subclinical boundaries of an infiltrating neoplasm cannot be determined explicitly via traditional imaging methods and are often defined to extend a fixed distance from the gross tumor boundary. In order to improve the clinical target definition process an estimation technique is proposed via which tumor growth may be modelled and subclinical growth predicted. An in vivo, macroscopic primary brain tumor growth model is presented, which may be fit to each patient undergoing treatment, allowing for the prediction of future growth and consequently the ability to estimate subclinical local invasion. Additionally, the patient specific in vivo tumor model will be of significant utility in multiple diagnostic clinical applications.

  6. A methodology for assessing the effect of countermeasures against a nuclear accident using fuzzy set theory

    International Nuclear Information System (INIS)

    Han, M.H.; Hwang, W.T.; Kim, E.H.; Suh, K.S.; Choi, Y.G.

    2000-01-01

    A methodology for assessing the effectiveness of countermeasures against a nuclear accident has been designed by means of the concept of fuzzy set theory. In most of the existing countermeasure models in actions under radiological emergencies, the large variety of possible features is simplified by a number of rough assumptions. During this simplification procedure, a lot of information is lost which results in much uncertainty concerning the output of the countermeasure model. Furthermore, different assumptions should be used for different sites to consider the site specific conditions. In this study, the diversity of each variable related to protective action has been modelled by the linguistic variable. The effectiveness of sheltering and evacuation has been estimated using the proposed method. The potential advantage of the proposed method is in reducing the loss of information by incorporating the opinions of experts and by introducing the linguistic variables which represent the site specific conditions. (author)

  7. Rough-fuzzy pattern recognition applications in bioinformatics and medical imaging

    CERN Document Server

    Maji, Pradipta

    2012-01-01

    Learn how to apply rough-fuzzy computing techniques to solve problems in bioinformatics and medical image processing Emphasizing applications in bioinformatics and medical image processing, this text offers a clear framework that enables readers to take advantage of the latest rough-fuzzy computing techniques to build working pattern recognition models. The authors explain step by step how to integrate rough sets with fuzzy sets in order to best manage the uncertainties in mining large data sets. Chapters are logically organized according to the major phases of pattern recognition systems dev

  8. Reliability evaluation methodologies for ensuring container integrity of stored transuranic (TRU) waste

    International Nuclear Information System (INIS)

    Smith, K.L.

    1995-06-01

    This report provides methodologies for providing defensible estimates of expected transuranic waste storage container lifetimes at the Radioactive Waste Management Complex. These methodologies can be used to estimate transuranic waste container reliability (for integrity and degradation) and as an analytical tool to optimize waste container integrity. Container packaging and storage configurations, which directly affect waste container integrity, are also addressed. The methodologies presented provide a means for demonstrating Resource Conservation and Recovery Act waste storage requirements

  9. Relational Demonic Fuzzy Refinement

    Directory of Open Access Journals (Sweden)

    Fairouz Tchier

    2014-01-01

    Full Text Available We use relational algebra to define a refinement fuzzy order called demonic fuzzy refinement and also the associated fuzzy operators which are fuzzy demonic join (⊔fuz, fuzzy demonic meet (⊓fuz, and fuzzy demonic composition (□fuz. Our definitions and properties are illustrated by some examples using mathematica software (fuzzy logic.

  10. Assessing IT Projects Success with Extended Fuzzy Cognitive Maps & Neutrosophic Cognitive Maps in comparison to Fuzzy Cognitive Maps

    Directory of Open Access Journals (Sweden)

    Kanika Bhutani

    2016-08-01

    Full Text Available IT projects hold a huge importance to economic growth. Today, half of the capital investments are in IT technology. IT systems and projects are extensive and time consuming; thus implying that its failure is not affordable, so proper feasibility study of assessing project success factors is required. A current methodology like Fuzzy Cognitive Maps has been experimented for identifying and evaluating the success factors in IT projects, but this technique has certain limitations. This paper discusses two new approaches to evaluate IT project success: Extended Fuzzy Cognitive Maps (E-FCM & Neutrosophic Cognitive Maps (NCM.The limitations of FCM like non consideration for non-linear, conditional, time delay weights and indeterminate relations are targeted using E-FCM and NCM in this paper.

  11. Multi-stage fuzzy PID power system automatic generation controller in deregulated environments

    International Nuclear Information System (INIS)

    Shayeghi, H.; Shayanfar, H.A.; Jalili, A.

    2006-01-01

    In this paper, a multi-stage fuzzy proportional integral derivative (PID) type controller is proposed to solve the automatic generation control (AGC) problem in a deregulated power system that operates under deregulation based on the bilateral policy scheme. In each control area, the effects of the possible contracts are treated as a set of new input signals in a modified traditional dynamical model. The multi-stage controller uses the fuzzy switch to blend a proportional derivative (PD) fuzzy logic controller with an integral fuzzy logic input. The proposed controller operates on fuzzy values passing the consequence of a prior stage on to the next stage as fact. The salient advantage of this strategy is its high insensitivity to large load changes and disturbances in the presence of plant parameter variations and system nonlinearities. This newly developed strategy leads to a flexible controller with simple structure that is easy to implement, and therefore, it can be useful for the real world power systems. The proposed method is tested on a three area power system with different contracted scenarios under various operating conditions. The results of the proposed controller are compared with those of the classical fuzzy PID type controller and classical PID controller through some performance indices to illustrate its robust performance

  12. Fuzzy logic controller for crude oil levels at Escravos Tank Farm ...

    African Journals Online (AJOL)

    Fuzzy logic controller (FLC) for crude oil flow rates and tank levels was designed for monitoring flow and tank level management at Escravos Tank Farm in Nigeria. The fuzzy control system incorporated essence of expert knowledge required to handle the tasks. Proportional Integral Derivative (PID) control of crude flow ...

  13. Fuzzy logic

    CERN Document Server

    Smets, P

    1995-01-01

    We start by describing the nature of imperfect data, and giving an overview of the various models that have been proposed. Fuzzy sets theory is shown to be an extension of classical set theory, and as such has a proeminent role or modelling imperfect data. The mathematic of fuzzy sets theory is detailled, in particular the role of the triangular norms. The use of fuzzy sets theory in fuzzy logic and possibility theory,the nature of the generalized modus ponens and of the implication operator for approximate reasoning are analysed. The use of fuzzy logic is detailled for application oriented towards process control and database problems.

  14. Exploiting maximum energy from variable speed wind power generation systems by using an adaptive Takagi-Sugeno-Kang fuzzy model

    International Nuclear Information System (INIS)

    Galdi, V.; Piccolo, A.; Siano, P.

    2009-01-01

    Nowadays, incentives and financing options for developing renewable energy facilities and the new development in variable speed wind technology make wind energy a competitive source if compared with conventional generation ones. In order to improve the effectiveness of variable speed wind systems, adaptive control systems able to cope with time variances of the system under control are necessary. On these basis, a data driven designing methodology for TSK fuzzy models design is presented in this paper. The methodology, on the basis of given input-output numerical data, generates the 'best' TSK fuzzy model able to estimate with high accuracy the maximum extractable power from a variable speed wind turbine. The design methodology is based on fuzzy clustering methods for partitioning the input-output space combined with genetic algorithms (GA), and recursive least-squares (LS) optimization methods for model parameter adaptation

  15. Fuzzy Logic Controller Design for Intelligent Robots

    Directory of Open Access Journals (Sweden)

    Ching-Han Chen

    2017-01-01

    Full Text Available This paper presents a fuzzy logic controller by which a robot can imitate biological behaviors such as avoiding obstacles or following walls. The proposed structure is implemented by integrating multiple ultrasonic sensors into a robot to collect data from a real-world environment. The decisions that govern the robot’s behavior and autopilot navigation are driven by a field programmable gate array- (FPGA- based fuzzy logic controller. The validity of the proposed controller was demonstrated by simulating three real-world scenarios to test the bionic behavior of a custom-built robot. The results revealed satisfactorily intelligent performance of the proposed fuzzy logic controller. The controller enabled the robot to demonstrate intelligent behaviors in complex environments. Furthermore, the robot’s bionic functions satisfied its design objectives.

  16. Fuzzy Neuroidal Nets and Recurrent Fuzzy Computations

    Czech Academy of Sciences Publication Activity Database

    Wiedermann, Jiří

    2001-01-01

    Roč. 11, č. 6 (2001), s. 675-686 ISSN 1210-0552. [SOFSEM 2001 Workshop on Soft Computing. Piešťany, 29.11.2001-30.11.2001] R&D Projects: GA ČR GA201/00/1489; GA AV ČR KSK1019101 Institutional research plan: AV0Z1030915 Keywords : fuzzy computing * fuzzy neural nets * fuzzy Turing machines * non-uniform computational complexity Subject RIV: BA - General Mathematics

  17. Evaluation of Combined Heat and Power (CHP Systems Using Fuzzy Shannon Entropy and Fuzzy TOPSIS

    Directory of Open Access Journals (Sweden)

    Fausto Cavallaro

    2016-06-01

    Full Text Available Combined heat and power (CHP or cogeneration can play a strategic role in addressing environmental issues and climate change. CHP systems require less fuel than separate heat and power systems in order to produce the same amount of energy saving primary energy, improving the security of the supply. Because less fuel is combusted, greenhouse gas emissions and other air pollutants are reduced. If we are to consider the CHP system as “sustainable”, we must include in its assessment not only energetic performance but also environmental and economic aspects, presenting a multicriteria issue. The purpose of the paper is to apply a fuzzy multicriteria methodology to the assessment of five CHP commercial technologies. Specifically, the combination of the fuzzy Shannon’s entropy and the fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS approach will be tested for this purpose. Shannon’s entropy concept, using interval data such as the α-cut, is a particularly suitable technique for assigning weights to criteria—it does not require a decision-making (DM to assign a weight to the criteria. To rank the proposed alternatives, a fuzzy TOPSIS method has been applied. It is based on the principle that the chosen alternative should be as close as possible to the positive ideal solution and be as far as possible from the negative ideal solution. The proposed approach provides a useful technical–scientific decision-making tool that can effectively support, in a consistent and transparent way, the assessment of various CHP technologies from a sustainable point of view.

  18. Cascade fuzzy control for gas engine driven heat pump

    International Nuclear Information System (INIS)

    Li Shuze; Zhang Wugao; Zhang Rongrong; Lv Dexu; Huang Zhen

    2005-01-01

    In addition to absorption chillers, today's gas cooling technology includes gas engine driven heat pump systems (GEHP) in a range of capacities and temperature capacities suitable for most commercial air conditioning and refrigeration applications. Much is expected from GEHPs as a product that would help satisfy the air conditioning system demand from medium and small sized buildings, restrict electric power demand peaks in summer and save energy in general. This article describes a kind of control strategy for a GEHP, a cascade fuzzy control. GEHPs have large and varying time constants and their dynamic modeling cannot be easily achieved. A cascade control strategy is effective for systems that have large time constants and disturbances, and a fuzzy control strategy is fit for a system that lacks an accurate model. This cascade fuzzy control structure brings together the best merits of fuzzy control and cascade control structures. The performance of the cascade fuzzy control is compared to that of a cascade PI (proportional and integral) control strategy, and it is shown by example that the cascade fuzzy control strategy gives a better performance, reduced reaction time and smaller overshoot temperature

  19. A 3D Hybrid Integration Methodology for Terabit Transceivers

    DEFF Research Database (Denmark)

    Dong, Yunfeng; Johansen, Tom Keinicke; Zhurbenko, Vitaliy

    2015-01-01

    integration are described. An equivalent circuit model of the via-throughs connecting the RF circuitry to the modulator is proposed and its lumped element parameters are extracted. Wire bonding transitions between the driving and RF circuitry were designed and simulated. An optimized 3D interposer design......This paper presents a three-dimensional (3D) hybrid integration methodology for terabit transceivers. The simulation methodology for multi-conductor structures are explained. The effect of ground vias on the RF circuitry and the preferred interposer substrate material for large bandwidth 3D hybrid...

  20. A novel prosodic-information synthesizer based on recurrent fuzzy neural network for the Chinese TTS system.

    Science.gov (United States)

    Lin, Chin-Teng; Wu, Rui-Cheng; Chang, Jyh-Yeong; Liang, Sheng-Fu

    2004-02-01

    In this paper, a new technique for the Chinese text-to-speech (TTS) system is proposed. Our major effort focuses on the prosodic information generation. New methodologies for constructing fuzzy rules in a prosodic model simulating human's pronouncing rules are developed. The proposed Recurrent Fuzzy Neural Network (RFNN) is a multilayer recurrent neural network (RNN) which integrates a Self-cOnstructing Neural Fuzzy Inference Network (SONFIN) into a recurrent connectionist structure. The RFNN can be functionally divided into two parts. The first part adopts the SONFIN as a prosodic model to explore the relationship between high-level linguistic features and prosodic information based on fuzzy inference rules. As compared to conventional neural networks, the SONFIN can always construct itself with an economic network size in high learning speed. The second part employs a five-layer network to generate all prosodic parameters by directly using the prosodic fuzzy rules inferred from the first part as well as other important features of syllables. The TTS system combined with the proposed method can behave not only sandhi rules but also the other prosodic phenomena existing in the traditional TTS systems. Moreover, the proposed scheme can even find out some new rules about prosodic phrase structure. The performance of the proposed RFNN-based prosodic model is verified by imbedding it into a Chinese TTS system with a Chinese monosyllable database based on the time-domain pitch synchronous overlap add (TD-PSOLA) method. Our experimental results show that the proposed RFNN can generate proper prosodic parameters including pitch means, pitch shapes, maximum energy levels, syllable duration, and pause duration. Some synthetic sounds are online available for demonstration.

  1. Fuzzy linear programming based optimal fuel scheduling incorporating blending/transloading facilities

    Energy Technology Data Exchange (ETDEWEB)

    Djukanovic, M.; Babic, B.; Milosevic, B. [Electrical Engineering Inst. Nikola Tesla, Belgrade (Yugoslavia); Sobajic, D.J. [EPRI, Palo Alto, CA (United States). Power System Control; Pao, Y.H. [Case Western Reserve Univ., Cleveland, OH (United States)]|[AI WARE, Inc., Cleveland, OH (United States)

    1996-05-01

    In this paper the blending/transloading facilities are modeled using an interactive fuzzy linear programming (FLP), in order to allow the decision-maker to solve the problem of uncertainty of input information within the fuel scheduling optimization. An interactive decision-making process is formulated in which decision-maker can learn to recognize good solutions by considering all possibilities of fuzziness. The application of the fuzzy formulation is accompanied by a careful examination of the definition of fuzziness, appropriateness of the membership function and interpretation of results. The proposed concept provides a decision support system with integration-oriented features, whereby the decision-maker can learn to recognize the relative importance of factors in the specific domain of optimal fuel scheduling (OFS) problem. The formulation of a fuzzy linear programming problem to obtain a reasonable nonfuzzy solution under consideration of the ambiguity of parameters, represented by fuzzy numbers, is introduced. An additional advantage of the FLP formulation is its ability to deal with multi-objective problems.

  2. Inventory Model for Deteriorating Items Involving Fuzzy with Shortages and Exponential Demand

    Directory of Open Access Journals (Sweden)

    Sharmila Vijai Stanly

    2015-11-01

    Full Text Available This paper considers the fuzzy inventory model for deteriorating items for power demand under fully backlogged conditions. We define various factors which are affecting the inventory cost by using the shortage costs. An intention of this paper is to study the inventory modelling through fuzzy environment. Inventory parameters, such as holding cost, shortage cost, purchasing cost and deterioration cost are assumed to be the trapezoidal fuzzy numbers. In addition, an efficient algorithm is developed to determine the optimal policy, and the computational effort and time are small for the proposed algorithm. It is simple to implement, and our approach is illustrated through some numerical examples to demonstrate the application and the performance of the proposed methodology.

  3. Dual mode linguistic hedge fuzzy logic controller for an isolated wind-diesel hybrid power system with superconducting magnetic energy storage unit

    International Nuclear Information System (INIS)

    Thameem Ansari, M.Md.; Velusami, S.

    2010-01-01

    A design of dual mode linguistic hedge fuzzy logic controller for an isolated wind-diesel hybrid power system with superconducting magnetic energy storage unit is proposed in this paper. The design methodology of dual mode linguistic hedge fuzzy logic controller is a hybrid model based on the concepts of linguistic hedges and hybrid genetic algorithm-simulated annealing algorithms. The linguistic hedge operators are used to adjust the shape of the system membership functions dynamically and can speed up the control result to fit the system demand. The hybrid genetic algorithm-simulated annealing algorithm is adopted to search the optimal linguistic hedge combination in the linguistic hedge module. Dual mode concept is also incorporated in the proposed controller because it can improve the system performance. The system with the proposed controller was simulated and the frequency deviation resulting from a step load disturbance is presented. The comparison of the proportional plus integral controller, fuzzy logic controller and the proposed dual mode linguistic hedge fuzzy logic controller shows that, with the application of the proposed controller, the system performance is improved significantly. The proposed controller is also found to be less sensitive to the changes in the parameters of the system and also robust under different operating modes of the hybrid power system.

  4. A fuzzy-ontology-oriented case-based reasoning framework for semantic diabetes diagnosis.

    Science.gov (United States)

    El-Sappagh, Shaker; Elmogy, Mohammed; Riad, A M

    2015-11-01

    Case-based reasoning (CBR) is a problem-solving paradigm that uses past knowledge to interpret or solve new problems. It is suitable for experience-based and theory-less problems. Building a semantically intelligent CBR that mimic the expert thinking can solve many problems especially medical ones. Knowledge-intensive CBR using formal ontologies is an evolvement of this paradigm. Ontologies can be used for case representation and storage, and it can be used as a background knowledge. Using standard medical ontologies, such as SNOMED CT, enhances the interoperability and integration with the health care systems. Moreover, utilizing vague or imprecise knowledge further improves the CBR semantic effectiveness. This paper proposes a fuzzy ontology-based CBR framework. It proposes a fuzzy case-base OWL2 ontology, and a fuzzy semantic retrieval algorithm that handles many feature types. This framework is implemented and tested on the diabetes diagnosis problem. The fuzzy ontology is populated with 60 real diabetic cases. The effectiveness of the proposed approach is illustrated with a set of experiments and case studies. The resulting system can answer complex medical queries related to semantic understanding of medical concepts and handling of vague terms. The resulting fuzzy case-base ontology has 63 concepts, 54 (fuzzy) object properties, 138 (fuzzy) datatype properties, 105 fuzzy datatypes, and 2640 instances. The system achieves an accuracy of 97.67%. We compare our framework with existing CBR systems and a set of five machine-learning classifiers; our system outperforms all of these systems. Building an integrated CBR system can improve its performance. Representing CBR knowledge using the fuzzy ontology and building a case retrieval algorithm that treats different features differently improves the accuracy of the resulting systems. Copyright © 2015 Elsevier B.V. All rights reserved.

  5. The Construction of a Vague Fuzzy Measure Through L1 Parameter Optimization

    Science.gov (United States)

    2012-08-26

    Programming v. 1.21, http://cvxr.com/cvx, (2011) 11 [3] E.J. Candes, J. Romberg and T. Tao. Robust Uncertainty Principles: Exact Signal Reconstruction From...Annales de I’institut Fourer, 5 (1954), pp. 131-295 [9] D. Diakoulaki, C. Antunes and A. Martins. MCDA in Energy Planning, Int. Series in Operations...formance and Tests , Fuzzy Sets and Systems, Vol. 65, Issues 2-3 (1994), pp.255-271 [15] M. Grabisch. Fuzzy Integral in Multicriteria Decision Making, Fuzzy

  6. Neuro-fuzzy system modeling based on automatic fuzzy clustering

    Institute of Scientific and Technical Information of China (English)

    Yuangang TANG; Fuchun SUN; Zengqi SUN

    2005-01-01

    A neuro-fuzzy system model based on automatic fuzzy clustering is proposed.A hybrid model identification algorithm is also developed to decide the model structure and model parameters.The algorithm mainly includes three parts:1) Automatic fuzzy C-means (AFCM),which is applied to generate fuzzy rules automatically,and then fix on the size of the neuro-fuzzy network,by which the complexity of system design is reducesd greatly at the price of the fitting capability;2) Recursive least square estimation (RLSE).It is used to update the parameters of Takagi-Sugeno model,which is employed to describe the behavior of the system;3) Gradient descent algorithm is also proposed for the fuzzy values according to the back propagation algorithm of neural network.Finally,modeling the dynamical equation of the two-link manipulator with the proposed approach is illustrated to validate the feasibility of the method.

  7. Combinational Reasoning of Quantitative Fuzzy Topological Relations for Simple Fuzzy Regions

    Science.gov (United States)

    Liu, Bo; Li, Dajun; Xia, Yuanping; Ruan, Jian; Xu, Lili; Wu, Huanyi

    2015-01-01

    In recent years, formalization and reasoning of topological relations have become a hot topic as a means to generate knowledge about the relations between spatial objects at the conceptual and geometrical levels. These mechanisms have been widely used in spatial data query, spatial data mining, evaluation of equivalence and similarity in a spatial scene, as well as for consistency assessment of the topological relations of multi-resolution spatial databases. The concept of computational fuzzy topological space is applied to simple fuzzy regions to efficiently and more accurately solve fuzzy topological relations. Thus, extending the existing research and improving upon the previous work, this paper presents a new method to describe fuzzy topological relations between simple spatial regions in Geographic Information Sciences (GIS) and Artificial Intelligence (AI). Firstly, we propose a new definition for simple fuzzy line segments and simple fuzzy regions based on the computational fuzzy topology. And then, based on the new definitions, we also propose a new combinational reasoning method to compute the topological relations between simple fuzzy regions, moreover, this study has discovered that there are (1) 23 different topological relations between a simple crisp region and a simple fuzzy region; (2) 152 different topological relations between two simple fuzzy regions. In the end, we have discussed some examples to demonstrate the validity of the new method, through comparisons with existing fuzzy models, we showed that the proposed method can compute more than the existing models, as it is more expressive than the existing fuzzy models. PMID:25775452

  8. An Integrated DEMATEL-QFD Model for Medical Supplier Selection

    OpenAIRE

    Mehtap Dursun; Zeynep Şener

    2014-01-01

    Supplier selection is considered as one of the most critical issues encountered by operations and purchasing managers to sharpen the company’s competitive advantage. In this paper, a novel fuzzy multi-criteria group decision making approach integrating quality function deployment (QFD) and decision making trial and evaluation laboratory (DEMATEL) method is proposed for supplier selection. The proposed methodology enables to consider the impacts of inner dependence among supplier assessment cr...

  9. The use of fuzzy real option valuation method to rank Giga ...

    African Journals Online (AJOL)

    The use of fuzzy real option valuation method to rank Giga Investment Projects on Iran's natural gas reserves. ... Journal of Fundamental and Applied Sciences ... methodology – discounted cash flow analysis – in valuation of Giga investments.

  10. The Fuzzy MCDM Algorithms for the M&A Due Diligence

    Directory of Open Access Journals (Sweden)

    Chung-Tsen Tsao

    2008-04-01

    Full Text Available An M&A due diligence is the process in which one of the parties to the transaction undertakes to investigate the other in order to judge whether to go forward with the transaction on the terms proposed. It encompasses the missions in three phases: searching and preliminary screening potential candidates, evaluating the candidates and deciding the target, and assisting the after-transaction integration. This work suggests using a Fuzzy Multiple Criteria Decision Making approach (Fuzzy MCDM and develops detailed algorithms to carry out the second-phase task. The approach of MCDM is able to facilitate the analysis and integration of information from different aspects and criteria. The theory of Fuzzy Sets can include qualitative information in addition to quantitative information. In the developed algorithms the evaluators' subjective judgments are expressed in linguistic terms which can better reflect human intuitive thought than the quantitative scores. These linguistic judgments are transformed into fuzzy numbers and made subsequent synthesis with quantitative financial figures. The order of candidates can be ranked after a defuzzification. Then the acquiring firm can work out a more specific study, including pricing and costing, on the priority candidates so as to decide the target.

  11. FUZZY RINGS AND ITS PROPERTIES

    Directory of Open Access Journals (Sweden)

    Karyati Karyati

    2017-01-01

      One of algebraic structure that involves a binary operation is a group that is defined  an un empty set (classical with an associative binary operation, it has identity elements and each element has an inverse. In the structure of the group known as the term subgroup, normal subgroup, subgroup and factor group homomorphism and its properties. Classical algebraic structure is developed to algebraic structure fuzzy by the researchers as an example semi group fuzzy and fuzzy group after fuzzy sets is introduced by L. A. Zadeh at 1965. It is inspired of writing about semi group fuzzy and group of fuzzy, a research on the algebraic structure of the ring is held with reviewing ring fuzzy, ideal ring fuzzy, homomorphism ring fuzzy and quotient ring fuzzy with its properties. The results of this study are obtained fuzzy properties of the ring, ring ideal properties fuzzy, properties of fuzzy ring homomorphism and properties of fuzzy quotient ring by utilizing a subset of a subset level  and strong level  as well as image and pre-image homomorphism fuzzy ring.   Keywords: fuzzy ring, subset level, homomorphism fuzzy ring, fuzzy quotient ring

  12. On fuzzy quasi continuity and an application of fuzzy set theory

    CERN Document Server

    Mahmoud, R A

    2003-01-01

    Where as classical topology has been developed closely connected with classical analysis describing topological phenomena in analysis, fuzzy topology with its important application in quantum gravity indicated by Witten and Elnaschie, has only been introduced as an analogue of the classical topology. The development of fuzzy topology without close relations to analytical problems did not give the possibility of testing successfully the applicability of the new notions and results. Till now this situation did not change, essentially. Although, many types of fuzzy sets and fuzzy functions having the quasi-property in both of weak and strong than openness and continuity, respectively, have been studied in detail. Many properties on fuzzy topological spaces such as compactness are discussed via fuzzy notion. While others are far from being completely devoted in its foundation. So, this paper is devoted to present a new class of fuzzy quasi-continuous functions via fuzzy compactness has been defined. Some characte...

  13. A fuzzy MCDM framework based on fuzzy measure and fuzzy integral for agile supplier evaluation

    Science.gov (United States)

    Dursun, Mehtap

    2017-06-01

    Supply chains need to be agile in order to response quickly to the changes in today's competitive environment. The success of an agile supply chain depends on the firm's ability to select the most appropriate suppliers. This study proposes a multi-criteria decision making technique for conducting an analysis based on multi-level hierarchical structure and fuzzy logic for the evaluation of agile suppliers. The ideal and anti-ideal solutions are taken into consideration simultaneously in the developed approach. The proposed decision approach enables the decision-makers to use linguistic terms, and thus, reduce their cognitive burden in the evaluation process. Furthermore, a hierarchy of evaluation criteria and their related sub-criteria is employed in the presented approach in order to conduct a more effective analysis.

  14. Fuzzy Versions of Epistemic and Deontic Logic

    Science.gov (United States)

    Gounder, Ramasamy S.; Esterline, Albert C.

    1998-01-01

    Epistemic and deontic logics are modal logics, respectively, of knowledge and of the normative concepts of obligation, permission, and prohibition. Epistemic logic is useful in formalizing systems of communicating processes and knowledge and belief in AI (Artificial Intelligence). Deontic logic is useful in computer science wherever we must distinguish between actual and ideal behavior, as in fault tolerance and database integrity constraints. We here discuss fuzzy versions of these logics. In the crisp versions, various axioms correspond to various properties of the structures used in defining the semantics of the logics. Thus, any axiomatic theory will be characterized not only by its axioms but also by the set of properties holding of the corresponding semantic structures. Fuzzy logic does not proceed with axiomatic systems, but fuzzy versions of the semantic properties exist and can be shown to correspond to some of the axioms for the crisp systems in special ways that support dependency networks among assertions in a modal domain. This in turn allows one to implement truth maintenance systems. For the technical development of epistemic logic, and for that of deontic logic. To our knowledge, we are the first to address fuzzy epistemic and fuzzy deontic logic explicitly and to consider the different systems and semantic properties available. We give the syntax and semantics of epistemic logic and discuss the correspondence between axioms of epistemic logic and properties of semantic structures. The same topics are covered for deontic logic. Fuzzy epistemic and fuzzy deontic logic discusses the relationship between axioms and semantic properties for these logics. Our results can be exploited in truth maintenance systems.

  15. Application of fuzzy logic control system for reactor feed-water control

    International Nuclear Information System (INIS)

    Iijima, T.; Nakajima, Y.

    1994-01-01

    The successful actual application of a fuzzy logic control system to the a nuclear Fugen nuclear power reactor is described. Fugen is a heavy-water moderated, light-water cooled reactor. The introduction of fuzzy logic control system has enabled operators to control the steam drum water level more effectively in comparison to a conventional proportional-integral (PI) control system

  16. Improvement of Fuzzy Image Contrast Enhancement Using Simulated Ergodic Fuzzy Markov Chains

    Directory of Open Access Journals (Sweden)

    Behrouz Fathi-Vajargah

    2014-01-01

    Full Text Available This paper presents a novel fuzzy enhancement technique using simulated ergodic fuzzy Markov chains for low contrast brain magnetic resonance imaging (MRI. The fuzzy image contrast enhancement is proposed by weighted fuzzy expected value. The membership values are then modified to enhance the image using ergodic fuzzy Markov chains. The qualitative performance of the proposed method is compared to another method in which ergodic fuzzy Markov chains are not considered. The proposed method produces better quality image.

  17. On macroeconomic characteristics of pharmaceutical generics and the potential for manufacturing and consumption under fuzzy conditions.

    Science.gov (United States)

    Gascón, Fernando; de la Fuente, David; Puente, Javier; Lozano, Jesús

    2007-11-01

    The aim of this paper is to develop a methodology that is useful for analyzing, from a macroeconomic perspective, the aggregate demand and the aggregate supply features of the market of pharmaceutical generics. In order to determine the potential consumption and the potential production of pharmaceutical generics in different countries, two fuzzy decision support systems are proposed. Two fuzzy decision support systems, both based on the Mamdani model, were applied in this paper. These systems, generated by Matlab Toolbox 'Fuzzy' (v. 2.0), are able to determine the potential of a country for the manufacturing or the consumption of pharmaceutical generics. The systems make use of three macroeconomic input variables. In an empirical application of our proposed methodology, the potential towards consumption and manufacturing in Holland, Sweden, Italy and Spain has been estimated from national indicators. Cross-country comparisons are made and graphical surfaces are analyzed in order to interpret the results. The main contribution of this work is the development of a methodology that is useful for analyzing aggregate demand and aggregate supply characteristics of pharmaceutical generics. The methodology is valid for carrying out a systematic analysis of the potential generics have at a macrolevel in different countries. The main advantages of the use of fuzzy decision support systems in the context of pharmaceutical generics are the flexibility in the construction of the system, the speed in interpreting the results offered by the inference and surface maps and the ease with which a sensitivity analysis of the potential behavior of a given country may be performed.

  18. Using a fuzzy comprehensive evaluation method to determine product usability: A proposed theoretical framework.

    Science.gov (United States)

    Zhou, Ronggang; Chan, Alan H S

    2017-01-01

    In order to compare existing usability data to ideal goals or to that for other products, usability practitioners have tried to develop a framework for deriving an integrated metric. However, most current usability methods with this aim rely heavily on human judgment about the various attributes of a product, but often fail to take into account of the inherent uncertainties in these judgments in the evaluation process. This paper presents a universal method of usability evaluation by combining the analytic hierarchical process (AHP) and the fuzzy evaluation method. By integrating multiple sources of uncertain information during product usability evaluation, the method proposed here aims to derive an index that is structured hierarchically in terms of the three usability components of effectiveness, efficiency, and user satisfaction of a product. With consideration of the theoretical basis of fuzzy evaluation, a two-layer comprehensive evaluation index was first constructed. After the membership functions were determined by an expert panel, the evaluation appraisals were computed by using the fuzzy comprehensive evaluation technique model to characterize fuzzy human judgments. Then with the use of AHP, the weights of usability components were elicited from these experts. Compared to traditional usability evaluation methods, the major strength of the fuzzy method is that it captures the fuzziness and uncertainties in human judgments and provides an integrated framework that combines the vague judgments from multiple stages of a product evaluation process.

  19. Fuzzy control. Fundamentals, stability and design of fuzzy controllers

    Energy Technology Data Exchange (ETDEWEB)

    Michels, K. [Fichtner GmbH und Co. KG, Stuttgart (Germany); Klawonn, F. [Fachhochschule Braunschweig/Wolfenbuettel (Germany). Fachbereich Informatik; Kruse, R. [Magdeburg Univ. (Germany). Fakultaet Informatik, Abt. Wiss.- und Sprachverarbeitung; Nuernberger, A. (eds.) [California Univ., Berkeley, CA (United States). Computer Science Division

    2006-07-01

    The book provides a critical discussion of fuzzy controllers from the perspective of classical control theory. Special emphases are placed on topics that are of importance for industrial applications, like (self-) tuning of fuzzy controllers, optimisation and stability analysis. The book is written as a textbook for graduate students as well as a comprehensive reference book about fuzzy control for researchers and application engineers. Starting with a detailed introduction to fuzzy systems and control theory the reader is guided to up-to-date research results. (orig.)

  20. Genetic Learning of Fuzzy Parameters in Predictive and Decision Support Modelling

    Directory of Open Access Journals (Sweden)

    Nebot

    2012-04-01

    Full Text Available In this research a genetic fuzzy system (GFS is proposed that performs discretization parameter learning in the context of the Fuzzy Inductive Reasoning (FIR methodology and the Linguistic Rule FIR (LR-FIR algorithm. The main goal of the GFS is to take advantage of the potentialities of GAs to learn the fuzzification parameters of the FIR and LR-FIR approaches in order to obtain reliable and useful predictive (FIR models and decision support (LR-FIR models. The GFS is evaluated in an e-learning context.

  1. Networks as integrated in research methodologies in PER

    DEFF Research Database (Denmark)

    Bruun, Jesper

    2016-01-01

    of using networks to create insightful maps of learning discussions. To conclude, I argue that conceptual blending is a powerful framework for constructing "mixed methods" methodologies that may integrate diverse theories and other methodologies with network methodologies.......In recent years a number of researchers within the PER community have started using network analysis as a new methodology to extend our understanding of teaching and learning physics by viewing these as complex systems. In this paper, I give examples of social, cognitive, and action mapping...... networks and how they can be analyzed. In so doing I show how a network can be methodologically described as a set of relations between a set of entities, and how a network can be characterized and analyzed as a mathematical object. Then, as an illustrative example, I discuss a relatively new example...

  2. Introduction to fuzzy systems

    CERN Document Server

    Chen, Guanrong

    2005-01-01

    Introduction to Fuzzy Systems provides students with a self-contained introduction that requires no preliminary knowledge of fuzzy mathematics and fuzzy control systems theory. Simplified and readily accessible, it encourages both classroom and self-directed learners to build a solid foundation in fuzzy systems. After introducing the subject, the authors move directly into presenting real-world applications of fuzzy logic, revealing its practical flavor. This practicality is then followed by basic fuzzy systems theory. The book also offers a tutorial on fuzzy control theory, based mainly on th

  3. An Integrated Safety Assessment Methodology for Generation IV Nuclear Systems

    International Nuclear Information System (INIS)

    Leahy, Timothy J.

    2010-01-01

    The Generation IV International Forum (GIF) Risk and Safety Working Group (RSWG) was created to develop an effective approach for the safety of Generation IV advanced nuclear energy systems. Early work of the RSWG focused on defining a safety philosophy founded on lessons learned from current and prior generations of nuclear technologies, and on identifying technology characteristics that may help achieve Generation IV safety goals. More recent RSWG work has focused on the definition of an integrated safety assessment methodology for evaluating the safety of Generation IV systems. The methodology, tentatively called ISAM, is an integrated 'toolkit' consisting of analytical techniques that are available and matched to appropriate stages of Generation IV system concept development. The integrated methodology is intended to yield safety-related insights that help actively drive the evolving design throughout the technology development cycle, potentially resulting in enhanced safety, reduced costs, and shortened development time.

  4. Decision-making methodology of optimal shielding materials by using fuzzy linear programming

    International Nuclear Information System (INIS)

    Kanai, Y.; Miura, T.; Hirao, Y.

    2000-01-01

    The main purpose of our studies are to select materials and determine the ratio of constituent materials as the first stage of optimum shielding design to suit the individual requirements of nuclear reactors, reprocessing facilities, casks for shipping spent fuel, etc. The parameters of the shield optimization are cost, space, weight and some shielding properties such as activation rates or individual irradiation and cooling time, and total dose rate for neutrons (including secondary gamma ray) and for primary gamma ray. Using conventional two-valued logic (i.e. crisp) approaches, huge combination calculations are needed to identify suitable materials for optimum shielding design. Also, re-computation is required for minor changes, as the approach does not react sensitively to the computation result. Present approach using a fuzzy linear programming method is much of the decision-making toward the satisfying solution might take place in fuzzy environment. And it can quickly and easily provide a guiding principle of optimal selection of shielding materials under the above-mentioned conditions. The possibility or reducing radiation effects by optimizing the ratio of constituent materials is investigated. (author)

  5. A mathematical theory of shape and neuro-fuzzy methodology-based diagnostic analysis: a comparative study on early detection and treatment planning of brain cancer.

    Science.gov (United States)

    Kar, Subrata; Majumder, D Dutta

    2017-08-01

    Investigation of brain cancer can detect the abnormal growth of tissue in the brain using computed tomography (CT) scans and magnetic resonance (MR) images of patients. The proposed method classifies brain cancer on shape-based feature extraction as either benign or malignant. The authors used input variables such as shape distance (SD) and shape similarity measure (SSM) in fuzzy tools, and used fuzzy rules to evaluate the risk status as an output variable. We presented a classifier neural network system (NNS), namely Levenberg-Marquardt (LM), which is a feed-forward back-propagation learning algorithm used to train the NN for the status of brain cancer, if any, and which achieved satisfactory performance with 100% accuracy. The proposed methodology is divided into three phases. First, we find the region of interest (ROI) in the brain to detect the tumors using CT and MR images. Second, we extract the shape-based features, like SD and SSM, and grade the brain tumors as benign or malignant with the concept of SD function and SSM as shape-based parameters. Third, we classify the brain cancers using neuro-fuzzy tools. In this experiment, we used a 16-sample database with SSM (μ) values and classified the benignancy or malignancy of the brain tumor lesions using the neuro-fuzzy system (NFS). We have developed a fuzzy expert system (FES) and NFS for early detection of brain cancer from CT and MR images. In this experiment, shape-based features, such as SD and SSM, were extracted from the ROI of brain tumor lesions. These shape-based features were considered as input variables and, using fuzzy rules, we were able to evaluate brain cancer risk values for each case. We used an NNS with LM, a feed-forward back-propagation learning algorithm, as a classifier for the diagnosis of brain cancer and achieved satisfactory performance with 100% accuracy. The proposed network was trained with MR image datasets of 16 cases. The 16 cases were fed to the ANN with 2 input neurons, one

  6. Stability analysis of polynomial fuzzy models via polynomial fuzzy Lyapunov functions

    OpenAIRE

    Bernal Reza, Miguel Ángel; Sala, Antonio; JAADARI, ABDELHAFIDH; Guerra, Thierry-Marie

    2011-01-01

    In this paper, the stability of continuous-time polynomial fuzzy models by means of a polynomial generalization of fuzzy Lyapunov functions is studied. Fuzzy Lyapunov functions have been fruitfully used in the literature for local analysis of Takagi-Sugeno models, a particular class of the polynomial fuzzy ones. Based on a recent Taylor-series approach which allows a polynomial fuzzy model to exactly represent a nonlinear model in a compact set of the state space, it is shown that a refinemen...

  7. A fuzzy intelligent system for land consolidation - a case study in Shunde, China

    Science.gov (United States)

    Wang, J.; Ge, A.; Hu, Y.; Li, C.; Wang, L.

    2015-04-01

    Traditionally, potential evaluation methods for farmland consolidation have depended mainly on the experts' experiences, statistical computations or subjective adjustments. Some biases usually exist in the results. Thus, computer-aided technology has become essential. In this study, an intelligent evaluation system based on a fuzzy decision tree was established, and this system can deal with numerical data, discrete data and symbolic data. When the original land data are input, the level of potential of the agricultural land for development will be output by this new model. The provision of objective proof for decision making by authorities in rural management is helpful. Agricultural land data characteristically comprise large volumes, complex varieties and more indexes. In land consolidation, it is very important to construct an effective index system. We needed to select a group of indexes useful for land consolidation according to the concrete demand. In this paper, a fuzzy measure, which can describe the importance of a single feature or a group of features, is adopted to accomplish the selection of specific features. A fuzzy integral that is based on a fuzzy measure is a type of fusion tool. We obtained the optimal solution for a fuzzy measure by solving a fuzzy integral. The fuzzy integrals can be transformed to a set of linear equations. We applied the L1-norm regularization method to solve the linear equations, and we found a solution with the fewest nonzero elements for the fuzzy measure; this solution shows the contribution of corresponding features or the combinations of decisions. This algorithm provides a quick and optimal way to identify the land index system when preparing to conduct the research, such as we describe herein, on land consolidation. Shunde's "Three Old" consolidation project provides the data for this work. Our estimation system was compared with a conventional evaluation system that is still accepted by the public. Our results prove

  8. Enfoque MDA para el diseño de un data warehouse difuso A model driven approach for fuzzy data warehouse design

    Directory of Open Access Journals (Sweden)

    Carolina Zambrano Matamala

    2012-04-01

    development life cycle are considered different methodologies and models that have the disadvantage that do not integrate the different levels of abstraction or the DW design process. However, MDA is an alternative approach to integration for the development of DW as it gives a comprehensive development framework based on the architecture of models and transformations between different levels of abstraction. This article presents a Fuzzy MDA approach to design fuzzy measures, fuzzy relations and fuzzy levels. For which we propose a Fuzzy OLAP CWM metamodel, QVT rules and an example of rule. Is the sequence methodology for applying the rules QVT. Finally, it provides a case study analysis in the field of education.

  9. Relational Demonic Fuzzy Refinement

    OpenAIRE

    Tchier, Fairouz

    2014-01-01

    We use relational algebra to define a refinement fuzzy order called demonic fuzzy refinement and also the associated fuzzy operators which are fuzzy demonic join $({\\bigsqcup }_{\\mathrm{\\text{f}}\\mathrm{\\text{u}}\\mathrm{\\text{z}}})$ , fuzzy demonic meet $({\\sqcap }_{\\mathrm{\\text{f}}\\mathrm{\\text{u}}\\mathrm{\\text{z}}})$ , and fuzzy demonic composition $({\\square }_{\\mathrm{\\text{f}}\\mathrm{\\text{u}}\\mathrm{\\text{z}}})$ . Our definitions and properties are illustrated by some examples using ma...

  10. Intuitionistic supra fuzzy topological spaces

    International Nuclear Information System (INIS)

    Abbas, S.E.

    2004-01-01

    In this paper, We introduce an intuitionistic supra fuzzy closure space and investigate the relationship between intuitionistic supra fuzzy topological spaces and intuitionistic supra fuzzy closure spaces. Moreover, we can obtain intuitionistic supra fuzzy topological space induced by an intuitionistic fuzzy bitopological space. We study the relationship between intuitionistic supra fuzzy closure space and the intuitionistic supra fuzzy topological space induced by an intuitionistic fuzzy bitopological space

  11. Intelligent control-I: review of fuzzy logic and fuzzy set theory

    International Nuclear Information System (INIS)

    Nagrial, M.H.

    2004-01-01

    In the past decade or so, fuzzy systems have supplanted conventional technologies in many engineering systems, in particular in control systems and pattern recognition. Fuzzy logic has found applications in a variety of consumer products e.g. washing machines, camcorders, digital cameras, air conditioners, subway trains, cement kilns and many others. The fuzzy technology is also being applied in information technology, where it provides decision-support and expert systems with powerful reasoning capabilities. Fuzzy sets, introduced by Zadeh in 1965 as a mathematical way to represent vagueness in linguistics, can be considered a generalisation of classical set theory. Fuzziness is often confused with probability. This lecture will introduce the principal concepts and mathematical notions of fuzzy set theory. (author)

  12. Fuzzy logic applied to prospecting for areas for installation of wood panel industries.

    Science.gov (United States)

    Dos Santos, Alexandre Rosa; Paterlini, Ewerthon Mattos; Fiedler, Nilton Cesar; Ribeiro, Carlos Antonio Alvares Soares; Lorenzon, Alexandre Simões; Domingues, Getulio Fonseca; Marcatti, Gustavo Eduardo; de Castro, Nero Lemos Martins; Teixeira, Thaisa Ribeiro; Dos Santos, Gleissy Mary Amaral Dino Alves; Juvanhol, Ronie Silva; Branco, Elvis Ricardo Figueira; Mota, Pedro Henrique Santos; da Silva, Lilianne Gomes; Pirovani, Daiani Bernardo; de Jesus, Waldir Cintra; Santos, Ana Carolina de Albuquerque; Leite, Helio Garcia; Iwakiri, Setsuo

    2017-05-15

    Prospecting for suitable areas for forestry operations, where the objective is a reduction in production and transportation costs, as well as the maximization of profits and available resources, constitutes an optimization problem. However, fuzzy logic is an alternative method for solving this problem. In the context of prospecting for suitable areas for the installation of wood panel industries, we propose applying fuzzy logic analysis for simulating the planting of different species and eucalyptus hybrids in Espírito Santo State, Brazil. The necessary methodological steps for this study are as follows: a) agriclimatological zoning of different species and eucalyptus hybrids; b) the selection of the vector variables; c) the application of the Euclidean distance to the vector variables; d) the application of fuzzy logic to matrix variables of the Euclidean distance; and e) the application of overlap fuzzy logic to locate areas for installation of wood panel industries. Among all the species and hybrids, Corymbia citriodora showed the highest percentage values for the combined very good and good classes, with 8.60%, followed by Eucalyptus grandis with 8.52%, Eucalyptus urophylla with 8.35% and Urograndis with 8.34%. The fuzzy logic analysis afforded flexibility in prospecting for suitable areas for the installation of wood panel industries in the Espírito Santo State can bring great economic and social benefits to the local population with the generation of jobs, income, tax revenues and GDP increase for the State and municipalities involved. The proposed methodology can be adapted to other areas and agricultural crops. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. Methodologies of Uncertainty Propagation Calculation

    International Nuclear Information System (INIS)

    Chojnacki, Eric

    2002-01-01

    After recalling the theoretical principle and the practical difficulties of the methodologies of uncertainty propagation calculation, the author discussed how to propagate input uncertainties. He said there were two kinds of input uncertainty: - variability: uncertainty due to heterogeneity, - lack of knowledge: uncertainty due to ignorance. It was therefore necessary to use two different propagation methods. He demonstrated this in a simple example which he generalised, treating the variability uncertainty by the probability theory and the lack of knowledge uncertainty by the fuzzy theory. He cautioned, however, against the systematic use of probability theory which may lead to unjustifiable and illegitimate precise answers. Mr Chojnacki's conclusions were that the importance of distinguishing variability and lack of knowledge increased as the problem was getting more and more complex in terms of number of parameters or time steps, and that it was necessary to develop uncertainty propagation methodologies combining probability theory and fuzzy theory

  14. Improving of Business Planning Using the Method of Fuzzy Numbers

    Directory of Open Access Journals (Sweden)

    Iryna Kosteteska

    2016-03-01

    Full Text Available Purpose: Summarize the experience of using modern methods in the business plan with the application of economic and mathematical modeling. Methodology: Theoretical and methodological basis of the study is the basic principles of economic theory, agricultural economics and scientific research of leading home and foreign scholars on the theory of planning. Originality: This further justifies business planning processes in agriculture from the standpoint of raising economic protection of farmers. The methodology for assessing farm income for planned indicators through the application of fuzzy numbers method in business planning is improved.

  15. Fuzzy multi-objective decision making on a low and intermediate level waste repository safety assessment

    International Nuclear Information System (INIS)

    Lemos, Francisco Luiz de; Deshpande, Ashok; Guimaraes, Lamartine

    2002-01-01

    Low and intermediate waste disposal facilities safety assessment is comprised of several steps from site selection , construction and operation to post-closure performance assessment. This is a multidisciplinary and complex task , and can not be analyzed by one expert only. This high complexity can lead to ambiguity and vagueness in information and consequently in the decision making process. In order to make the decision process clear and objective, there is the need to provide the decision makers with a clear and comprehensive picture of the whole process and, at the same time, simple and easily understandable by the public. This paper suggests the development of an inference system based on fuzzy decision making methodology. Fuzzy logic tools are specially suited to deal with ambiguous data by using language expressions. This process would be capable of integrating knowledge from various fields of environmental sciences. It has an advantage of keeping record of reasoning for each intermediate decision that lead to the final results which makes it more dependable and defensible as well. (author)

  16. A methodology approach for analysis of sustainability indicators as a tool for decision making using fuzzy logic

    International Nuclear Information System (INIS)

    Quinhoneiro, Fernando Henrique Franchi

    2015-01-01

    The greatest challenge of this century is focused on sustainability, due to world population growth and consequently to the increased demand for resources such as water, food and energy. The main difficulty when discussing the issue of sustainable development is the evaluation methodology. Because of this, there is a need for a measurement tool that addresses these resources in a holistic manner and be able to translate data into results that can be interpreted. There are tools validated for this purpose like, 'Dashboard of Sustainability' and other developing like the CLEW Nexus by the International Atomic Energy Agency - IAEA. This study aims to develop a new model to analyze the correlation between variables, energy, water, land use and climate, using Artificial Intelligence through Fuzzy Logic, having as a data source, indicators that represent one or more resource, considering the relative and temporal distribution required to research results and behaviors. The result is a final index generated by mapping these input data. The results presented using this methodology are indicators of Brazil, but can be applied to any other country, allowing a comparison analysis of the behavior of indices between regions. The contribution of this project will be the availability of a tool with powerful computational resource, aimed at decision makers to assist in developing strategies and development policies. (author)

  17. Using fuzzy logic for automatic control: Case study of a problem of cereals samples classification

    Directory of Open Access Journals (Sweden)

    Lakhoua Najeh Mohamed

    2009-01-01

    Full Text Available The aim of this paper is to present the use of fuzzy logic for automatic control of industrial systems particularly the way to approach a problem of classification. We present a case study of a grading system of cereals that allows us to determine the price of transactions of cereals in Tunisia. Our contribution in this work consists in proposing not only an application of the fuzzy logic on the grading system of cereals but also a methodology enabling the proposing of a new grading system based on the concept of 'Grade' while using the fuzzy logic techniques. .

  18. A hybrid intelligent algorithm for portfolio selection problem with fuzzy returns

    Science.gov (United States)

    Li, Xiang; Zhang, Yang; Wong, Hau-San; Qin, Zhongfeng

    2009-11-01

    Portfolio selection theory with fuzzy returns has been well developed and widely applied. Within the framework of credibility theory, several fuzzy portfolio selection models have been proposed such as mean-variance model, entropy optimization model, chance constrained programming model and so on. In order to solve these nonlinear optimization models, a hybrid intelligent algorithm is designed by integrating simulated annealing algorithm, neural network and fuzzy simulation techniques, where the neural network is used to approximate the expected value and variance for fuzzy returns and the fuzzy simulation is used to generate the training data for neural network. Since these models are used to be solved by genetic algorithm, some comparisons between the hybrid intelligent algorithm and genetic algorithm are given in terms of numerical examples, which imply that the hybrid intelligent algorithm is robust and more effective. In particular, it reduces the running time significantly for large size problems.

  19. Evaluation of E-Learning Web Sites Using Fuzzy Axiomatic Design Based Approach

    Directory of Open Access Journals (Sweden)

    2010-04-01

    Full Text Available High quality web site has been generally recognized as a critical enabler to conduct online business. Numerous studies exist in the literature to measure the business performance in relation to web site quality. In this paper, an axiomatic design based approach for fuzzy group decision making is adopted to evaluate the quality of e-learning web sites. Another multi-criteria decision making technique, namely fuzzy TOPSIS, is applied in order to validate the outcome. The methodology proposed in this paper has the advantage of incorporating requirements and enabling reductions in the problem size, as compared to fuzzy TOPSIS. A case study focusing on Turkish e-learning websites is presented, and based on the empirical findings, managerial implications and recommendations for future research are offered.

  20. Hesitant fuzzy sets theory

    CERN Document Server

    Xu, Zeshui

    2014-01-01

    This book provides the readers with a thorough and systematic introduction to hesitant fuzzy theory. It presents the most recent research results and advanced methods in the field. These includes: hesitant fuzzy aggregation techniques, hesitant fuzzy preference relations, hesitant fuzzy measures, hesitant fuzzy clustering algorithms and hesitant fuzzy multi-attribute decision making methods. Since its introduction by Torra and Narukawa in 2009, hesitant fuzzy sets have become more and more popular and have been used for a wide range of applications, from decision-making problems to cluster analysis, from medical diagnosis to personnel appraisal and information retrieval. This book offers a comprehensive report on the state-of-the-art in hesitant fuzzy sets theory and applications, aiming at becoming a reference guide for both researchers and practitioners in the area of fuzzy mathematics and other applied research fields (e.g. operations research, information science, management science and engineering) chara...

  1. Fuzzy logic in management

    CERN Document Server

    Carlsson, Christer; Fullér, Robert

    2004-01-01

    Fuzzy Logic in Management demonstrates that difficult problems and changes in the management environment can be more easily handled by bringing fuzzy logic into the practice of management. This explicit theme is developed through the book as follows: Chapter 1, "Management and Intelligent Support Technologies", is a short survey of management leadership and what can be gained from support technologies. Chapter 2, "Fuzzy Sets and Fuzzy Logic", provides a short introduction to fuzzy sets, fuzzy relations, the extension principle, fuzzy implications and linguistic variables. Chapter 3, "Group Decision Support Systems", deals with group decision making, and discusses methods for supporting the consensus reaching processes. Chapter 4, "Fuzzy Real Options for Strategic Planning", summarizes research where the fuzzy real options theory was implemented as a series of models. These models were thoroughly tested on a number of real life investments, and validated in 2001. Chapter 5, "Soft Computing Methods for Reducing...

  2. Analyzing data from a fuzzy rating scale-based questionnaire. A case study.

    Science.gov (United States)

    Gil, María Ángeles; Lubiano, María Asunción; de la Rosa de Sáa, Sara; Sinova, Beatriz

    2015-01-01

    The fuzzy rating scale was introduced to cope with the imprecision of human thought and experience in measuring attitudes in many fields of Psychology. The flexibility and expressiveness of this scale allow us to properly describe the answers to many questions involving psychological measurement. Analyzing the responses to a fuzzy rating scale-based questionnaire is indeed a critical problem. Nevertheless, over the last years, a methodology is being developed to analyze statistically fuzzy data in such a way that the information they contain is fully exploited. In this paper, a summary review of the main procedures is given. The methods are illustrated by their application on the dataset obtained from a case study with nine-year-old children. In this study, children replied to some questions from the well-known TIMSS/PIRLS questionnaire by using a fuzzy rating scale. The form could be filled in either on the computer or by hand. The study indicates that the requirements of background and training underlying the fuzzy rating scale are not too demanding. Moreover, it is clearly shown that statistical conclusions substantially often differ depending on the responses being given in accordance with either a Likert scale or a fuzzy rating scale.

  3. Systematic design of membership functions for fuzzy-logic control: A case study on one-stage partial nitritation/anammox treatment systems.

    Science.gov (United States)

    Boiocchi, Riccardo; Gernaey, Krist V; Sin, Gürkan

    2016-10-01

    A methodology is developed to systematically design the membership functions of fuzzy-logic controllers for multivariable systems. The methodology consists of a systematic derivation of the critical points of the membership functions as a function of predefined control objectives. Several constrained optimization problems corresponding to different qualitative operation states of the system are defined and solved to identify, in a consistent manner, the critical points of the membership functions for the input variables. The consistently identified critical points, together with the linguistic rules, determine the long term reachability of the control objectives by the fuzzy logic controller. The methodology is highlighted using a single-stage side-stream partial nitritation/Anammox reactor as a case study. As a result, a new fuzzy-logic controller for high and stable total nitrogen removal efficiency is designed. Rigorous simulations are carried out to evaluate and benchmark the performance of the controller. The results demonstrate that the novel control strategy is capable of rejecting the long-term influent disturbances, and can achieve a stable and high TN removal efficiency. Additionally, the controller was tested, and showed robustness, against measurement noise levels typical for wastewater sensors. A feedforward-feedback configuration using the present controller would give even better performance. In comparison, a previously developed fuzzy-logic controller using merely expert and intuitive knowledge performed worse. This proved the importance of using a systematic methodology for the derivation of the membership functions for multivariable systems. These results are promising for future applications of the controller in real full-scale plants. Furthermore, the methodology can be used as a tool to help systematically design fuzzy logic control applications for other biological processes. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. The World of Combinatorial Fuzzy Problems and the Efficiency of Fuzzy Approximation Algorithms

    OpenAIRE

    Yamakami, Tomoyuki

    2015-01-01

    We re-examine a practical aspect of combinatorial fuzzy problems of various types, including search, counting, optimization, and decision problems. We are focused only on those fuzzy problems that take series of fuzzy input objects and produce fuzzy values. To solve such problems efficiently, we design fast fuzzy algorithms, which are modeled by polynomial-time deterministic fuzzy Turing machines equipped with read-only auxiliary tapes and write-only output tapes and also modeled by polynomia...

  5. Integrating Fuzzy Logic, Optimization, and GIS for Ecological Impact Assessments

    Science.gov (United States)

    Bojórquez-Tapia, Luis A.; Juárez, Lourdes; Cruz-Bello, Gustavo

    2002-09-01

    Appraisal of ecological impacts has been problematic because of the behavior of ecological system and the responses of these systems to human intervention are far from fully understood. While it has been relatively easy to itemize the potential ecological impacts, it has been difficult to arrive at accurate predictions of how these impacts affect populations, communities, or ecosystems. Furthermore, the spatial heterogeneity of ecological systems has been overlooked because its examination is practically impossible through matrix techniques, the most commonly used impact assessment approach. Besides, the public has become increasingly aware of the importance of the EIA in decision-making and thus the interpretation of impact significance is complicated further by the different value judgments of stakeholders. Moreover, impact assessments are carried out with a minimum of data, high uncertainty, and poor conceptual understanding. Hence, the evaluation of ecological impacts entails the integration of subjective and often conflicting judgments from a variety of experts and stakeholders. The purpose of this paper is to present an environmental impact assessment approach based on the integration fuzzy logic, geographical information systems and optimization techniques. This approach enables environmental analysts to deal with the intrinsic imprecision and ambiguity associated with the judgments of experts and stakeholders, the description of ecological systems, and the prediction of ecological impacts. The application of this approach is illustrated through an example, which shows how consensus about impact mitigation can be attained within a conflict resolution framework.

  6. Fuzzy risk matrix

    International Nuclear Information System (INIS)

    Markowski, Adam S.; Mannan, M. Sam

    2008-01-01

    A risk matrix is a mechanism to characterize and rank process risks that are typically identified through one or more multifunctional reviews (e.g., process hazard analysis, audits, or incident investigation). This paper describes a procedure for developing a fuzzy risk matrix that may be used for emerging fuzzy logic applications in different safety analyses (e.g., LOPA). The fuzzification of frequency and severity of the consequences of the incident scenario are described which are basic inputs for fuzzy risk matrix. Subsequently using different design of risk matrix, fuzzy rules are established enabling the development of fuzzy risk matrices. Three types of fuzzy risk matrix have been developed (low-cost, standard, and high-cost), and using a distillation column case study, the effect of the design on final defuzzified risk index is demonstrated

  7. An Integrated Methodology for Emulsified Formulated Product Design

    DEFF Research Database (Denmark)

    Mattei, Michele

    are mixed together to determine the desired emulsified product. They are still mainly designed and analysed through trial - and - error based exper- imental techniques, therefore a systematic approach , integrating model-based as well a s experiment - based techniques, for design of these products could......The consumer oriented chemical based products are used every day by millions of people. They are structured products constituted of numerous chemicals, and many of them, especially household and personal care products, are emulsions where active ingredients, solvents, additives and surfactants...... significantly reduce both time and cost connected to product development by doing only the necessary experi- ments , and ensuring chances for innovation . The main contribution of this project i s the development of an integrated methodology for the design of emulsified formulated products. The methodology...

  8. Bimodal fuzzy analytic hierarchy process (BFAHP) for coronary heart disease risk assessment.

    Science.gov (United States)

    Sabahi, Farnaz

    2018-04-04

    Rooted deeply in medical multiple criteria decision-making (MCDM), risk assessment is very important especially when applied to the risk of being affected by deadly diseases such as coronary heart disease (CHD). CHD risk assessment is a stochastic, uncertain, and highly dynamic process influenced by various known and unknown variables. In recent years, there has been a great interest in fuzzy analytic hierarchy process (FAHP), a popular methodology for dealing with uncertainty in MCDM. This paper proposes a new FAHP, bimodal fuzzy analytic hierarchy process (BFAHP) that augments two aspects of knowledge, probability and validity, to fuzzy numbers to better deal with uncertainty. In BFAHP, fuzzy validity is computed by aggregating the validities of relevant risk factors based on expert knowledge and collective intelligence. By considering both soft and statistical data, we compute the fuzzy probability of risk factors using the Bayesian formulation. In BFAHP approach, these fuzzy validities and fuzzy probabilities are used to construct a reciprocal comparison matrix. We then aggregate fuzzy probabilities and fuzzy validities in a pairwise manner for each risk factor and each alternative. BFAHP decides about being affected and not being affected by ranking of high and low risks. For evaluation, the proposed approach is applied to the risk of being affected by CHD using a real dataset of 152 patients of Iranian hospitals. Simulation results confirm that adding validity in a fuzzy manner can accrue more confidence of results and clinically useful especially in the face of incomplete information when compared with actual results. Applying the proposed BFAHP on CHD risk assessment of the dataset, it yields high accuracy rate above 85% for correct prediction. In addition, this paper recognizes that the risk factors of diastolic blood pressure in men and high-density lipoprotein in women are more important in CHD than other risk factors. Copyright © 2018 Elsevier Inc. All

  9. Fuzzy measure analysis of public attitude towards the use of nuclear energy

    International Nuclear Information System (INIS)

    Nishiwaki, Y.; Preyssl, C.; Onisawa, T.; Sen'ichi Mokuya

    1996-01-01

    It is important to identify the structure of public acceptance or rejection when new technologies are developed and implemented The structure of attitudes should have the essential attributes and their interrelation. In such a structural analysis the attitudes need to be decomposed into meaningful attributes by a suitable model However, the data obtained in this type of study may be more or less subjective and fuzzy, and the following problems may be pointed out: (1.) A man does net always have an additive measure such as probability to evaluate fuzzy objects, (2.) The attributes of an object in bis evaluation process are not always independent of each other. In either case a linear model may not be applicable. This paper is concerned with applying fuzzy measures and fuzzy integrals to analyze public attitude towards the use of nuclear energy. We applied the fuzzy measures and fuzzy integrals to analyze public attitude towards the use of nuclear energy by distributing questionnaires to about 100 students of Engineering Department of Kinki University, Higashi-Osaka, Osaka, Japan. Before and after the Chernobyl Accident we noticed a distinct difference in mental structure Before the accident, the students of pro-nuclear group were whole-heartedly in favour of the use of nuclear energy, based on fringe benefits, impacts on society and economic progress, but after the accident they showed a favourable attitude towards the use of nuclear energy based on economic progress, but with some reservation because of the potential threats. (author)

  10. Virtual reality simulation of fuzzy-logic control during underwater dynamic positioning

    Science.gov (United States)

    Thekkedan, Midhin Das; Chin, Cheng Siong; Woo, Wai Lok

    2015-03-01

    In this paper, graphical-user-interface (GUI) software for simulation and fuzzy-logic control of a remotely operated vehicle (ROV) using MATLAB™ GUI Designing Environment is proposed. The proposed ROV's GUI platform allows the controller such as fuzzy-logic control systems design to be compared with other controllers such as proportional-integral-derivative (PID) and sliding-mode controller (SMC) systematically and interactively. External disturbance such as sea current can be added to improve the modelling in actual underwater environment. The simulated results showed the position responses of the fuzzy-logic control exhibit reasonable performance under the sea current disturbance.

  11. Current trends in Bayesian methodology with applications

    CERN Document Server

    Upadhyay, Satyanshu K; Dey, Dipak K; Loganathan, Appaia

    2015-01-01

    Collecting Bayesian material scattered throughout the literature, Current Trends in Bayesian Methodology with Applications examines the latest methodological and applied aspects of Bayesian statistics. The book covers biostatistics, econometrics, reliability and risk analysis, spatial statistics, image analysis, shape analysis, Bayesian computation, clustering, uncertainty assessment, high-energy astrophysics, neural networking, fuzzy information, objective Bayesian methodologies, empirical Bayes methods, small area estimation, and many more topics.Each chapter is self-contained and focuses on

  12. Adaptive Functional-Based Neuro-Fuzzy-PID Incremental Controller Structure

    Directory of Open Access Journals (Sweden)

    Ashraf Ahmed Fahmy

    2014-03-01

    Full Text Available This paper presents an adaptive functional-based Neuro-fuzzy-PID incremental (NFPID controller structure that can be tuned either offline or online according to required controller performance. First, differential membership functions are used to represent the fuzzy membership functions of the input-output space of the three term controller. Second, controller rules are generated based on the discrete proportional, derivative, and integral function for the fuzzy space. Finally, a fully differentiable fuzzy neural network is constructed to represent the developed controller for either offline or online controller parameter adaptation.  Two different adaptation methods are used for controller tuning, offline method based on controller transient performance cost function optimization using Bees Algorithm, and online method based on tracking error minimization using back-propagation with momentum algorithm. The proposed control system was tested to show the validity of the controller structure over a fixed PID controller gains to control SCARA type robot arm.

  13. Global sensitivity analysis for fuzzy inputs based on the decomposition of fuzzy output entropy

    Science.gov (United States)

    Shi, Yan; Lu, Zhenzhou; Zhou, Yicheng

    2018-06-01

    To analyse the component of fuzzy output entropy, a decomposition method of fuzzy output entropy is first presented. After the decomposition of fuzzy output entropy, the total fuzzy output entropy can be expressed as the sum of the component fuzzy entropy contributed by fuzzy inputs. Based on the decomposition of fuzzy output entropy, a new global sensitivity analysis model is established for measuring the effects of uncertainties of fuzzy inputs on the output. The global sensitivity analysis model can not only tell the importance of fuzzy inputs but also simultaneously reflect the structural composition of the response function to a certain degree. Several examples illustrate the validity of the proposed global sensitivity analysis, which is a significant reference in engineering design and optimization of structural systems.

  14. Intuitionistic Fuzzy Subbialgebras and Duality

    Directory of Open Access Journals (Sweden)

    Wenjuan Chen

    2014-01-01

    Full Text Available We investigate connections between bialgebras and Atanassov’s intuitionistic fuzzy sets. Firstly we define an intuitionistic fuzzy subbialgebra of a bialgebra with an intuitionistic fuzzy subalgebra structure and also with an intuitionistic fuzzy subcoalgebra structure. Secondly we investigate the related properties of intuitionistic fuzzy subbialgebras. Finally we prove that the dual of an intuitionistic fuzzy strong subbialgebra is an intuitionistic fuzzy strong subbialgebra.

  15. Estimation of the Net Present Value of the Investment Project in the Situation of Fuzzy Initial Data

    Directory of Open Access Journals (Sweden)

    Kotsyuba Oleksiy S.

    2017-03-01

    Full Text Available The article investigates the problem of estimating the net present value of the investment project using a methodology based on the theory of fuzzy sets in the situation when the initial data are described by fuzzy estimates. In the general case the fuzzy-multiple estimation of the specified indicator at a discrete-interval representation of the initial parameters is reduced to a set of homogeneous optimization problems. Often, depending on the characteristics of fuzzy estimates of cash flows of the investment project under consideration, the solutions to these problems can be found directly on the basis of relevant analytical expressions, while other problems require using special optimization methods. In the work there made an attempt to develop the analytical component of the fuzzy-multiple modeling of the net present value indicator. First, we examined the general search and optimization approach, which allows providing a predetermined degree of accuracy, as well as the method for approximate determination of the fuzzy estimate of the net present value on the basis of analytical relationships developed by Сhui-Yu Chiu and Chan S. Park. After that, the situation was analyzed, and the corresponding calculation model was proposed, when fuzzy estimates of the cash flows of the investment project can be interpreted from the perspective of the concept of the money-generating operation formulated by O. B. Lozhkin. Among other things, it allowed to develop a general scheme for determining the fuzzy estimate of the net present value, supplementing it with the situation of this concept. As the main direction of the further development of the problems discussed in the publication there determined the formation of a holistic methodology for evaluating the effectiveness of real investments, which would cover different in their nature and structural characteristics types of uncertainty from unified theoretical positions.

  16. Fuzzy topological digital space and digital fuzzy spline of electroencephalography during epileptic seizures

    Science.gov (United States)

    Shah, Mazlina Muzafar; Wahab, Abdul Fatah

    2017-08-01

    Epilepsy disease occurs because of there is a temporary electrical disturbance in a group of brain cells (nurons). The recording of electrical signals come from the human brain which can be collected from the scalp of the head is called Electroencephalography (EEG). EEG then considered in digital format and in fuzzy form makes it a fuzzy digital space data form. The purpose of research is to identify the area (curve and surface) in fuzzy digital space affected by inside epilepsy seizure in epileptic patient's brain. The main focus for this research is to generalize fuzzy topological digital space, definition and basic operation also the properties by using digital fuzzy set and the operations. By using fuzzy digital space, the theory of digital fuzzy spline can be introduced to replace grid data that has been use previously to get better result. As a result, the flat of EEG can be fuzzy topological digital space and this type of data can be use to interpolate the digital fuzzy spline.

  17. Intuitionistic Fuzzy Time Series Forecasting Model Based on Intuitionistic Fuzzy Reasoning

    Directory of Open Access Journals (Sweden)

    Ya’nan Wang

    2016-01-01

    Full Text Available Fuzzy sets theory cannot describe the data comprehensively, which has greatly limited the objectivity of fuzzy time series in uncertain data forecasting. In this regard, an intuitionistic fuzzy time series forecasting model is built. In the new model, a fuzzy clustering algorithm is used to divide the universe of discourse into unequal intervals, and a more objective technique for ascertaining the membership function and nonmembership function of the intuitionistic fuzzy set is proposed. On these bases, forecast rules based on intuitionistic fuzzy approximate reasoning are established. At last, contrast experiments on the enrollments of the University of Alabama and the Taiwan Stock Exchange Capitalization Weighted Stock Index are carried out. The results show that the new model has a clear advantage of improving the forecast accuracy.

  18. Dynamic Fuzzy Clustering Method for Decision Support in Electricity Markets Negotiation

    Directory of Open Access Journals (Sweden)

    Ricardo FAIA

    2016-10-01

    Full Text Available Artificial Intelligence (AI methods contribute to the construction of systems where there is a need to automate the tasks. They are typically used for problems that have a large response time, or when a mathematical method cannot be used to solve the problem. However, the application of AI brings an added complexity to the development of such applications. AI has been frequently applied in the power systems field, namely in Electricity Markets (EM. In this area, AI applications are essentially used to forecast / estimate the prices of electricity or to search for the best opportunity to sell the product. This paper proposes a clustering methodology that is combined with fuzzy logic in order to perform the estimation of EM prices. The proposed method is based on the application of a clustering methodology that groups historic energy contracts according to their prices’ similarity. The optimal number of groups is automatically calculated taking into account the preference for the balance between the estimation error and the number of groups. The centroids of each cluster are used to define a dynamic fuzzy variable that approximates the tendency of contracts’ history. The resulting fuzzy variable allows estimating expected prices for contracts instantaneously and approximating missing values in the historic contracts.

  19. Fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and the probabilities of trends of fuzzy logical relationships.

    Science.gov (United States)

    Chen, Shyi-Ming; Chen, Shen-Wen

    2015-03-01

    In this paper, we present a new method for fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and the probabilities of trends of fuzzy-trend logical relationships. Firstly, the proposed method fuzzifies the historical training data of the main factor and the secondary factor into fuzzy sets, respectively, to form two-factors second-order fuzzy logical relationships. Then, it groups the obtained two-factors second-order fuzzy logical relationships into two-factors second-order fuzzy-trend logical relationship groups. Then, it calculates the probability of the "down-trend," the probability of the "equal-trend" and the probability of the "up-trend" of the two-factors second-order fuzzy-trend logical relationships in each two-factors second-order fuzzy-trend logical relationship group, respectively. Finally, it performs the forecasting based on the probabilities of the down-trend, the equal-trend, and the up-trend of the two-factors second-order fuzzy-trend logical relationships in each two-factors second-order fuzzy-trend logical relationship group. We also apply the proposed method to forecast the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) and the NTD/USD exchange rates. The experimental results show that the proposed method outperforms the existing methods.

  20. Fuzzy probability based fault tree analysis to propagate and quantify epistemic uncertainty

    International Nuclear Information System (INIS)

    Purba, Julwan Hendry; Sony Tjahyani, D.T.; Ekariansyah, Andi Sofrany; Tjahjono, Hendro

    2015-01-01

    Highlights: • Fuzzy probability based fault tree analysis is to evaluate epistemic uncertainty in fuzzy fault tree analysis. • Fuzzy probabilities represent likelihood occurrences of all events in a fault tree. • A fuzzy multiplication rule quantifies epistemic uncertainty of minimal cut sets. • A fuzzy complement rule estimate epistemic uncertainty of the top event. • The proposed FPFTA has successfully evaluated the U.S. Combustion Engineering RPS. - Abstract: A number of fuzzy fault tree analysis approaches, which integrate fuzzy concepts into the quantitative phase of conventional fault tree analysis, have been proposed to study reliabilities of engineering systems. Those new approaches apply expert judgments to overcome the limitation of the conventional fault tree analysis when basic events do not have probability distributions. Since expert judgments might come with epistemic uncertainty, it is important to quantify the overall uncertainties of the fuzzy fault tree analysis. Monte Carlo simulation is commonly used to quantify the overall uncertainties of conventional fault tree analysis. However, since Monte Carlo simulation is based on probability distribution, this technique is not appropriate for fuzzy fault tree analysis, which is based on fuzzy probabilities. The objective of this study is to develop a fuzzy probability based fault tree analysis to overcome the limitation of fuzzy fault tree analysis. To demonstrate the applicability of the proposed approach, a case study is performed and its results are then compared to the results analyzed by a conventional fault tree analysis. The results confirm that the proposed fuzzy probability based fault tree analysis is feasible to propagate and quantify epistemic uncertainties in fault tree analysis

  1. Probabilistic fuzzy systems as additive fuzzy systems

    NARCIS (Netherlands)

    Almeida, R.J.; Verbeek, N.; Kaymak, U.; Costa Sousa, da J.M.; Laurent, A.; Strauss, O.; Bouchon-Meunier, B.; Yager, R.

    2014-01-01

    Probabilistic fuzzy systems combine a linguistic description of the system behaviour with statistical properties of data. It was originally derived based on Zadeh’s concept of probability of a fuzzy event. Two possible and equivalent additive reasoning schemes were proposed, that lead to the

  2. Analysis of decision fusion algorithms in handling uncertainties for integrated health monitoring systems

    Science.gov (United States)

    Zein-Sabatto, Saleh; Mikhail, Maged; Bodruzzaman, Mohammad; DeSimio, Martin; Derriso, Mark; Behbahani, Alireza

    2012-06-01

    It has been widely accepted that data fusion and information fusion methods can improve the accuracy and robustness of decision-making in structural health monitoring systems. It is arguably true nonetheless, that decision-level is equally beneficial when applied to integrated health monitoring systems. Several decisions at low-levels of abstraction may be produced by different decision-makers; however, decision-level fusion is required at the final stage of the process to provide accurate assessment about the health of the monitored system as a whole. An example of such integrated systems with complex decision-making scenarios is the integrated health monitoring of aircraft. Thorough understanding of the characteristics of the decision-fusion methodologies is a crucial step for successful implementation of such decision-fusion systems. In this paper, we have presented the major information fusion methodologies reported in the literature, i.e., probabilistic, evidential, and artificial intelligent based methods. The theoretical basis and characteristics of these methodologies are explained and their performances are analyzed. Second, candidate methods from the above fusion methodologies, i.e., Bayesian, Dempster-Shafer, and fuzzy logic algorithms are selected and their applications are extended to decisions fusion. Finally, fusion algorithms are developed based on the selected fusion methods and their performance are tested on decisions generated from synthetic data and from experimental data. Also in this paper, a modeling methodology, i.e. cloud model, for generating synthetic decisions is presented and used. Using the cloud model, both types of uncertainties; randomness and fuzziness, involved in real decision-making are modeled. Synthetic decisions are generated with an unbiased process and varying interaction complexities among decisions to provide for fair performance comparison of the selected decision-fusion algorithms. For verification purposes

  3. Models for cooperative games with fuzzy relations among the agents fuzzy communication, proximity relation and fuzzy permission

    CERN Document Server

    Jiménez-Losada, Andrés

    2017-01-01

    This book offers a comprehensive introduction to cooperative game theory and a practice-oriented reference guide to new models and tools for studying bilateral fuzzy relations among several agents or players. It introduces the reader to several fuzzy models, each of which is first analyzed in the context of classical games (crisp games) and subsequently in the context of fuzzy games. Special emphasis is given to the value of Shapley, which is presented for the first time in the context of fuzzy games. Students and researchers will find here a self-contained reference guide to cooperative fuzzy games, characterized by a wealth of examples, descriptions of a wide range of possible situations, step-by-step explanations of the basic mathematical concepts involved, and easy-to-follow information on axioms and properties.

  4. Using Logarithmic Fuzzy Preference Programming To Prioritization Social Media Utilization Based On Tourists’ Perspective

    Directory of Open Access Journals (Sweden)

    Balouchi Mina

    2015-06-01

    Full Text Available The advent of Web 2.0 or social media technologies gives travelers a chance to access quickly and conveniently to a mass of travel-related information. This study investigates the importance of social media in travel process in three different phases (pre-visit, on site, post-visit from the perspective of Iranian travelers. It is worthwhile to know the level of influence of social media on respondents’ travel behavior. Logarithmic fuzzy preference programming methodology is used in this article to determine the importance of social media usage in each phase of travel process and its subcategories. Fuzzy analytic hierarchy process methodology, based on Chang’s Fuzzy Extent Analysis is also used for the data analysis, then the results of these two methods are presented for comparison and better understanding. The results of this study suggest that the most usage of social media is on pre-visit phase while post-visit has the least usage. This study shows that Iranian travelers use social media mainly to share experiences (post-visit phase, get help in different circumstances and gain travel advice.

  5. Residual Generator Fuzzy Identification for Wind TurbineBenchmark Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Silvio Simani

    2014-11-01

    Full Text Available In order to improve the availability of wind turbines, thus improving theirefficiency, it is important to detect and isolate faults in their earlier occurrence. The mainproblem of model-based fault diagnosis applied to wind turbines is represented by thesystem complexity, as well as the reliability of the available measurements. In this work, adata-driven strategy relying on fuzzy models is presented, in order to build a fault diagnosissystem. Fuzzy theory jointly with the Frisch identification scheme for errors-in-variablemodels is exploited here, since it allows one to approximate unknown models and manageuncertain data. Moreover, the use of fuzzy models, which are directly identified from thewind turbine measurements, allows the design of the fault detection and isolation module.It is worth noting that, sometimes, the nonlinearity of a wind turbine system could lead toquite complex analytic solutions. However, IF-THEN fuzzy rules provide a simpler solution,important when on-line implementations have to be considered. The wind turbine benchmarkis used to validate the achieved performances of the suggested fault detection and isolationscheme. Finally, comparisons of the proposed methodology with respect to different faultdiagnosis methods serve to highlight the features of the suggested solution.

  6. Multicriteria optimization in a fuzzy environment: The fuzzy analytic hierarchy process

    Directory of Open Access Journals (Sweden)

    Gardašević-Filipović Milanka

    2010-01-01

    Full Text Available In the paper the fuzzy extension of the Analytic Hierarchy Process (AHP based on fuzzy numbers, and its application in solving a practical problem, are considered. The paper advocates the use of contradictory test to check the fuzzy user preferences during fuzzy AHP decision-making process. We also propose consistency check and deriving priorities from inconsistent fuzzy judgment matrices to be included in the process, in order to check if the fuzzy approach can be applied in the AHP for the problem considered. An aggregation of local priorities obtained at different levels into composite global priorities for the alternatives based on weighted-sum method is also discussed. The contradictory fuzzy judgment matrix is analyzed. Our theoretical consideration has been verified by an application of commercially available Super Decisions program (developed for solving multi-criteria optimization problems using AHP approach on the problem previously treated in the literature. The obtained results are compared with those from the literature. The conclusions are given and the possibilities for further work in the field are pointed out.

  7. A novel multi-model neuro-fuzzy-based MPPT for three-phase grid-connected photovoltaic system

    Energy Technology Data Exchange (ETDEWEB)

    Chaouachi, Aymen; Kamel, Rashad M.; Nagasaka, Ken [Department of Electronic and Information Engineering, Tokyo University of Agriculture and Technology, Nakamachi (Japan)

    2010-12-15

    This paper presents a novel methodology for Maximum Power Point Tracking (MPPT) of a grid-connected 20 kW photovoltaic (PV) system using neuro-fuzzy network. The proposed method predicts the reference PV voltage guarantying optimal power transfer between the PV generator and the main utility grid. The neuro-fuzzy network is composed of a fuzzy rule-based classifier and three multi-layered feed forwarded Artificial Neural Networks (ANN). Inputs of the network (irradiance and temperature) are classified before they are fed into the appropriated ANN for either training or estimation process while the output is the reference voltage. The main advantage of the proposed methodology, comparing to a conventional single neural network-based approach, is the distinct generalization ability regarding to the nonlinear and dynamic behavior of a PV generator. In fact, the neuro-fuzzy network is a neural network based multi-model machine learning that defines a set of local models emulating the complex and nonlinear behavior of a PV generator under a wide range of operating conditions. Simulation results under several rapid irradiance variations proved that the proposed MPPT method fulfilled the highest efficiency comparing to a conventional single neural network and the Perturb and Observe (P and O) algorithm dispositive. (author)

  8. Intelligent control a hybrid approach based on fuzzy logic, neural networks and genetic algorithms

    CERN Document Server

    Siddique, Nazmul

    2014-01-01

    Intelligent Control considers non-traditional modelling and control approaches to nonlinear systems. Fuzzy logic, neural networks and evolutionary computing techniques are the main tools used. The book presents a modular switching fuzzy logic controller where a PD-type fuzzy controller is executed first followed by a PI-type fuzzy controller thus improving the performance of the controller compared with a PID-type fuzzy controller.  The advantage of the switching-type fuzzy controller is that it uses one rule-base thus minimises the rule-base during execution. A single rule-base is developed by merging the membership functions for change of error of the PD-type controller and sum of error of the PI-type controller. Membership functions are then optimized using evolutionary algorithms. Since the two fuzzy controllers were executed in series, necessary further tuning of the differential and integral scaling factors of the controller is then performed. Neural-network-based tuning for the scaling parameters of t...

  9. Fuzzy weakly preopen (preclosed) function in Kubiak-Sostak fuzzy topological spaces

    International Nuclear Information System (INIS)

    Zahran, A.M.; Abd-Allah, M. Azab.; Abd El-Rahman, Abd El-Nasser G.

    2009-01-01

    In this paper, we introduce and characterize fuzzy weakly preopen and fuzzy weakly preclosed functions between L-fuzzy topological spaces in Kubiak-Sostak sense and also study these functions in relation to some other types of already known functions.

  10. On Fuzzy β-I-open sets and Fuzzy β-I-continuous functions

    International Nuclear Information System (INIS)

    Keskin, Aynur

    2009-01-01

    In this paper, first of all we obtain some properties and characterizations of fuzzy β-I-open sets. After that, we also define the notion of β-I-closed sets and obtain some properties. Lastly, we introduce the notions of fuzzy β-I-continuity with the help of fuzzy β-I-open sets to obtain decomposition of fuzzy continuity.

  11. On Fuzzy {beta}-I-open sets and Fuzzy {beta}-I-continuous functions

    Energy Technology Data Exchange (ETDEWEB)

    Keskin, Aynur [Department of Mathematics, Faculty of Science and Arts, Selcuk University, Campus, 42075 Konya (Turkey)], E-mail: akeskin@selcuk.edu.tr

    2009-11-15

    In this paper, first of all we obtain some properties and characterizations of fuzzy {beta}-I-open sets. After that, we also define the notion of {beta}-I-closed sets and obtain some properties. Lastly, we introduce the notions of fuzzy {beta}-I-continuity with the help of fuzzy {beta}-I-open sets to obtain decomposition of fuzzy continuity.

  12. Fuzzy stochastic damage mechanics (FSDM based on fuzzy auto-adaptive control theory

    Directory of Open Access Journals (Sweden)

    Ya-jun Wang

    2012-06-01

    Full Text Available In order to fully interpret and describe damage mechanics, the origin and development of fuzzy stochastic damage mechanics were introduced based on the analysis of the harmony of damage, probability, and fuzzy membership in the interval of [0,1]. In a complete normed linear space, it was proven that a generalized damage field can be simulated through β probability distribution. Three kinds of fuzzy behaviors of damage variables were formulated and explained through analysis of the generalized uncertainty of damage variables and the establishment of a fuzzy functional expression. Corresponding fuzzy mapping distributions, namely, the half-depressed distribution, swing distribution, and combined swing distribution, which can simulate varying fuzzy evolution in diverse stochastic damage situations, were set up. Furthermore, through demonstration of the generalized probabilistic characteristics of damage variables, the cumulative distribution function and probability density function of fuzzy stochastic damage variables, which show β probability distribution, were modified according to the expansion principle. The three-dimensional fuzzy stochastic damage mechanical behaviors of the Longtan rolled-concrete dam were examined with the self-developed fuzzy stochastic damage finite element program. The statistical correlation and non-normality of random field parameters were considered comprehensively in the fuzzy stochastic damage model described in this paper. The results show that an initial damage field based on the comprehensive statistical evaluation helps to avoid many difficulties in the establishment of experiments and numerical algorithms for damage mechanics analysis.

  13. ANALYSIS OF FUZZY QUEUES: PARAMETRIC PROGRAMMING APPROACH BASED ON RANDOMNESS - FUZZINESS CONSISTENCY PRINCIPLE

    OpenAIRE

    Dhruba Das; Hemanta K. Baruah

    2015-01-01

    In this article, based on Zadeh’s extension principle we have apply the parametric programming approach to construct the membership functions of the performance measures when the interarrival time and the service time are fuzzy numbers based on the Baruah’s Randomness- Fuzziness Consistency Principle. The Randomness-Fuzziness Consistency Principle leads to defining a normal law of fuzziness using two different laws of randomness. In this article, two fuzzy queues FM...

  14. A Hybrid Approach Using ISM For Leveling Agile Criteria And Fuzzy AHP To Determine The Relative Weights Of Evaluation Criteria And Fuzzy TOPSIS To Rank The Alternatives

    Directory of Open Access Journals (Sweden)

    Mahdi Karbasian1

    2012-02-01

    Full Text Available In today’s organizations, performance measurement comes more to the foreground with the advancement in the high technology. Supplier selection is an important issue in supply chain management. In recent years, determining the best supplier in the supply chain has become a key strategic consideration. However, these decisions usually involve several objectives or criteria, and it is often necessary to compromise among possibly conflicting factors. Thus, the multiple criteria decision making (MCDM becomes a useful approach to solve this kind of problem. In order to use the conceptual framework for measuring performance supplier, a methodology that takes into account both quantitative and qualitative factors and the interrelations between them should be utilized. for leveling an integrated approach of analytic hierarchy process AHP and fuzzy TOPSIS method is proposed to obtain final ranking. The interactions among the criteria are also analyzed before arriving at a decision for the selection of supplier from among six alternatives. Linguistic values are used to assess the ratings and weights for criterion. These linguistic ratings can be expressed in triangular fuzzy numbers. Then, a hierarchy multiple criteria decision-making (MCDM model based on fuzzy-sets theory including FAHP and FTOPSIS are applied. There are two approaches for aggregating values including relative importance of evaluation criteria with respect to the overall objective and rating of alternatives with respect to each criterion in fuzzy group TOPSIS: First aggregation and Last aggregation. In first aggregation approach weight of each criterion and rating of alternatives with respect to each criterion gained from decision makers are aggregated at first and TOPSIS method then apply to these aggregate values. In last aggregation approach weight of each criterion and rating of alternatives with respect to each criterion gained from decision makers are used in TOPSIS method

  15. ANALYSIS OF FUZZY QUEUES: PARAMETRIC PROGRAMMING APPROACH BASED ON RANDOMNESS - FUZZINESS CONSISTENCY PRINCIPLE

    Directory of Open Access Journals (Sweden)

    Dhruba Das

    2015-04-01

    Full Text Available In this article, based on Zadeh’s extension principle we have apply the parametric programming approach to construct the membership functions of the performance measures when the interarrival time and the service time are fuzzy numbers based on the Baruah’s Randomness- Fuzziness Consistency Principle. The Randomness-Fuzziness Consistency Principle leads to defining a normal law of fuzziness using two different laws of randomness. In this article, two fuzzy queues FM/M/1 and M/FM/1 has been studied and constructed their membership functions of the system characteristics based on the aforesaid principle. The former represents a queue with fuzzy exponential arrivals and exponential service rate while the latter represents a queue with exponential arrival rate and fuzzy exponential service rate.

  16. On Stochastic Finite-Time Control of Discrete-Time Fuzzy Systems with Packet Dropout

    Directory of Open Access Journals (Sweden)

    Yingqi Zhang

    2012-01-01

    Full Text Available This paper is concerned with the stochastic finite-time stability and stochastic finite-time boundedness problems for one family of fuzzy discrete-time systems over networks with packet dropout, parametric uncertainties, and time-varying norm-bounded disturbance. Firstly, we present the dynamic model description studied, in which the discrete-time fuzzy T-S systems with packet loss can be described by one class of fuzzy Markovian jump systems. Then, the concepts of stochastic finite-time stability and stochastic finite-time boundedness and problem formulation are given. Based on Lyapunov function approach, sufficient conditions on stochastic finite-time stability and stochastic finite-time boundedness are established for the resulting closed-loop fuzzy discrete-time system with Markovian jumps, and state-feedback controllers are designed to ensure stochastic finite-time stability and stochastic finite-time boundedness of the class of fuzzy systems. The stochastic finite-time stability and stochastic finite-time boundedness criteria can be tackled in the form of linear matrix inequalities with a fixed parameter. As an auxiliary result, we also give sufficient conditions on the stochastic stability of the class of fuzzy T-S systems with packet loss. Finally, two illustrative examples are presented to show the validity of the developed methodology.

  17. Fuzzy-valued linguistic soft set theory and multi-attribute decision-making application

    International Nuclear Information System (INIS)

    Aiwu, Zhao; Hongjun, Guan

    2016-01-01

    In this work, we propose the theory of fuzzy linguistic soft set (FLSS) to represent the uncertainty and multi-angle of view when decision makers evaluate an object during decision-making. FLSS integrates fuzzy set theory, linguistic variable and soft set theory. It allows decision makers to utilize linguistic variables to evaluate an object and utilize fuzzy values to describe the corresponding grade of their support of their decisions. Meanwhile, because of the flexibility of soft set, decision makers can use more than one pair of fuzzy-linguistic evaluations to express their opinions from multiple perspectives directly, if necessary. Therefore, it is more flexible and practical than traditional fuzzy set or 2-dimension uncertainty linguistic variable. We also develop a generalized weighted aggregation operator for FLSSs to solve corresponding decision-making issues. Finally, we give a numerical example to verify the practicality and effectiveness of the proposed method.

  18. Introduction to Fuzzy Set Theory

    Science.gov (United States)

    Kosko, Bart

    1990-01-01

    An introduction to fuzzy set theory is described. Topics covered include: neural networks and fuzzy systems; the dynamical systems approach to machine intelligence; intelligent behavior as adaptive model-free estimation; fuzziness versus probability; fuzzy sets; the entropy-subsethood theorem; adaptive fuzzy systems for backing up a truck-and-trailer; product-space clustering with differential competitive learning; and adaptive fuzzy system for target tracking.

  19. On the Expected Value of Fuzzy Events

    Czech Academy of Sciences Publication Activity Database

    Klement, E.P.; Mesiar, Radko

    2015-01-01

    Roč. 23, Supplement 1 (2015), s. 57-74 ISSN 0218-4885 Institutional support: RVO:67985556 Keywords : expected value * fuzzy event * Choquet integral Subject RIV: BA - General Mathematics Impact factor: 1.000, year: 2015 http://library.utia.cas.cz/separaty/2015/E/mesiar-0452568.pdf

  20. An Integrated Fuzzy Approach for Strategic Alliance Partner Selection in Third-Party Logistics

    Science.gov (United States)

    Gundogar, Emin; Yılmaz, Aysegul

    2012-01-01

    Outsourcing some of the logistic activities is a useful strategy for companies in recent years. This makes it possible for firms to concentrate on their main issues and processes and presents facility to improve logistics performance, to reduce costs, and to improve quality. Therefore provider selection and evaluation in third-party logistics become important activities for companies. Making a strategic decision like this is significantly hard and crucial. In this study we proposed a fuzzy multicriteria decision making (MCDM) approach to effectively select the most appropriate provider. First we identify the provider selection criteria and build the hierarchical structure of decision model. After building the hierarchical structure we determined the selection criteria weights by using fuzzy analytical hierarchy process (AHP) technique. Then we applied fuzzy technique for order preference by similarity to ideal solution (TOPSIS) to obtain final rankings for providers. And finally an illustrative example is also given to demonstrate the effectiveness of the proposed model. PMID:23365520

  1. An Integrated Fuzzy Approach for Strategic Alliance Partner Selection in Third-Party Logistics

    Directory of Open Access Journals (Sweden)

    Burak Erkayman

    2012-01-01

    Full Text Available Outsourcing some of the logistic activities is a useful strategy for companies in recent years. This makes it possible for firms to concentrate on their main issues and processes and presents facility to improve logistics performance, to reduce costs, and to improve quality. Therefore provider selection and evaluation in third-party logistics become important activities for companies. Making a strategic decision like this is significantly hard and crucial. In this study we proposed a fuzzy multicriteria decision making (MCDM approach to effectively select the most appropriate provider. First we identify the provider selection criteria and build the hierarchical structure of decision model. After building the hierarchical structure we determined the selection criteria weights by using fuzzy analytical hierarchy process (AHP technique. Then we applied fuzzy technique for order preference by similarity to ideal solution (TOPSIS to obtain final rankings for providers. And finally an illustrative example is also given to demonstrate the effectiveness of the proposed model.

  2. An integrated fuzzy approach for strategic alliance partner selection in third-party logistics.

    Science.gov (United States)

    Erkayman, Burak; Gundogar, Emin; Yilmaz, Aysegul

    2012-01-01

    Outsourcing some of the logistic activities is a useful strategy for companies in recent years. This makes it possible for firms to concentrate on their main issues and processes and presents facility to improve logistics performance, to reduce costs, and to improve quality. Therefore provider selection and evaluation in third-party logistics become important activities for companies. Making a strategic decision like this is significantly hard and crucial. In this study we proposed a fuzzy multicriteria decision making (MCDM) approach to effectively select the most appropriate provider. First we identify the provider selection criteria and build the hierarchical structure of decision model. After building the hierarchical structure we determined the selection criteria weights by using fuzzy analytical hierarchy process (AHP) technique. Then we applied fuzzy technique for order preference by similarity to ideal solution (TOPSIS) to obtain final rankings for providers. And finally an illustrative example is also given to demonstrate the effectiveness of the proposed model.

  3. Landslide susceptibility assessment by using a neuro-fuzzy model: a case study in the Rupestrian heritage rich area of Matera

    Science.gov (United States)

    Sdao, F.; Lioi, D. S.; Pascale, S.; Caniani, D.; Mancini, I. M.

    2013-02-01

    The complete assessment of landslide susceptibility needs uniformly distributed detailed information on the territory. This information, which is related to the temporal occurrence of landslide phenomena and their causes, is often fragmented and heterogeneous. The present study evaluates the landslide susceptibility map of the Natural Archaeological Park of Matera (Southern Italy) (Sassi and area Rupestrian Churches sites). The assessment of the degree of "spatial hazard" or "susceptibility" was carried out by the spatial prediction regardless of the return time of the events. The evaluation model for the susceptibility presented in this paper is very focused on the use of innovative techniques of artificial intelligence such as Neural Network, Fuzzy Logic and Neuro-fuzzy Network. The method described in this paper is a novel technique based on a neuro-fuzzy system. It is able to train data like neural network and it is able to shape and control uncertain and complex systems like a fuzzy system. This methodology allows us to derive susceptibility maps of the study area. These data are obtained from thematic maps representing the parameters responsible for the instability of the slopes. The parameters used in the analysis are: plan curvature, elevation (DEM), angle and aspect of the slope, lithology, fracture density, kinematic hazard index of planar and wedge sliding and toppling. Moreover, this method is characterized by the network training which uses a training matrix, consisting of input and output training data, which determine the landslide susceptibility. The neuro-fuzzy method was integrated to a sensitivity analysis in order to overcome the uncertainty linked to the used membership functions. The method was compared to the landslide inventory map and was validated by applying three methods: a ROC (Receiver Operating Characteristic) analysis, a confusion matrix and a SCAI method. The developed neuro-fuzzy method showed a good performance in the

  4. Novel Distance Measure in Fuzzy TOPSIS for Supply Chain Strategy Based Supplier Selection

    Directory of Open Access Journals (Sweden)

    B. Pardha Saradhi

    2016-01-01

    Full Text Available In today’s highly competitive environment, organizations need to evaluate and select suppliers based on their manufacturing strategy. Identification of supply chain strategy of the organization, determination of decision criteria, and methods of supplier selection are appearing to be the most important components in research area in the field of supply chain management. In this paper, evaluation of suppliers is done based on the balanced scorecard framework using new distance measure in fuzzy TOPSIS by considering the supply chain strategy of the manufacturing organization. To take care of vagueness in decision making, trapezoidal fuzzy number is assumed for pairwise comparisons to determine relative weights of perspectives and criteria of supplier selection. Also, linguistic variables specified in terms of trapezoidal fuzzy number are considered for the payoff values of criteria of the suppliers. These fuzzy numbers satisfied the Jensen based inequality. A detailed application of the proposed methodology is illustrated.

  5. Embedded system based on a real time fuzzy motor speed controller

    Directory of Open Access Journals (Sweden)

    Ebrahim Abd El-Hamid Mohamed Ramadan

    2014-06-01

    Full Text Available This paper describes an implementation of a fuzzy logic control (FLC system and a/the conventional proportional-integral (PI controller for speed control of DC motor, based on field programmable gate array (FPGA circuit. The proposed scheme is aimed to improve the tracking performance and to eliminate the load disturbance in the speed control of DC motors. The proposed fuzzy system has been applied to a permanent magnet DC motor, via a configuration of H-bridge. The fuzzy control algorithm is designed and verified with a nonlinear model, using the MATLAB® tools. Both FLC and conventional PI controller hardware are synthesized, functionally verified and implemented using Xilinx Integrated Software Environment (ISE Version 11.1i. The real time implementation of these controllers is made on Spartan-3E FPGA starter kit (XC3S500E. The practical results showed that the proposed FLC scheme has better tracking performance than the conventional PI controller for the speed control of DC motors.

  6. Fuzzy logic control of water level in advanced boiling water reactor

    International Nuclear Information System (INIS)

    Lin, Chaung; Lee, Chi-Szu; Raghavan, R.; Fahrner, D.M.

    1995-01-01

    The feedwater control system in the Advanced Boiling Water Reactor (ABWR) is more challenging to design compared to other control systems in the plant, due to the possible change in level from void collapses and swells during transient events. A basic fuzzy logic controller is developed using a simplified ABWR mathematical model to demonstrate and compare the performance of this controller with a simplified conventional controller. To reduce the design effort, methods are developed to automatically tune the scaling factors and control rules. As a first step in developing the fuzzy controller, a fuzzy controller with a limited number of rules is developed to respond to normal plant transients such as setpoint changes of plant parameters and load demand changes. Various simulations for setpoint and load demand changes of plant performances were conducted to evaluate the modeled fuzzy logic design against the simplified ABWR model control system. The simulation results show that the performance of the fuzzy logic controller is comparable to that of the Proportional-Integral (PI) controller, However, the fuzzy logic controller produced shorter settling time for step setpoint changes compared to the simplified conventional controller

  7. Real Time Implementation of Incremental Fuzzy Logic Controller for Gas Pipeline Corrosion Control

    Directory of Open Access Journals (Sweden)

    Gopalakrishnan Jayapalan

    2014-01-01

    Full Text Available A robust virtual instrumentation based fuzzy incremental corrosion controller is presented to protect metallic gas pipelines. Controller output depends on error and change in error of the controlled variable. For corrosion control purpose pipe to soil potential is considered as process variable. The proposed fuzzy incremental controller is designed using a very simple control rule base and the most natural and unbiased membership functions. The proposed scheme is tested for a wide range of pipe to soil potential control. Performance comparison between the conventional proportional integral type and proposed fuzzy incremental controller is made in terms of several performance criteria such as peak overshoot, settling time, and rise time. Result shows that the proposed controller outperforms its conventional counterpart in each case. Designed controller can be taken in automode without waiting for initial polarization to stabilize. Initial startup curve of proportional integral controller and fuzzy incremental controller is reported. This controller can be used to protect any metallic structures such as pipelines, tanks, concrete structures, ship, and offshore structures.

  8. Integrated cost estimation methodology to support high-performance building design

    Energy Technology Data Exchange (ETDEWEB)

    Vaidya, Prasad; Greden, Lara; Eijadi, David; McDougall, Tom [The Weidt Group, Minnetonka (United States); Cole, Ray [Axiom Engineers, Monterey (United States)

    2007-07-01

    Design teams evaluating the performance of energy conservation measures (ECMs) calculate energy savings rigorously with established modelling protocols, accounting for the interaction between various measures. However, incremental cost calculations do not have a similar rigor. Often there is no recognition of cost reductions with integrated design, nor is there assessment of cost interactions amongst measures. This lack of rigor feeds the notion that high-performance buildings cost more, creating a barrier for design teams pursuing aggressive high-performance outcomes. This study proposes an alternative integrated methodology to arrive at a lower perceived incremental cost for improved energy performance. The methodology is based on the use of energy simulations as means towards integrated design and cost estimation. Various points along the spectrum of integration are identified and characterized by the amount of design effort invested, the scheduling of effort, and relative energy performance of the resultant design. It includes a study of the interactions between building system parameters as they relate to capital costs. Several cost interactions amongst energy measures are found to be significant.The value of this approach is demonstrated with alternatives in a case study that shows the differences between perceived costs for energy measures along various points on the integration spectrum. These alternatives show design tradeoffs and identify how decisions would have been different with a standard costing approach. Areas of further research to make the methodology more robust are identified. Policy measures to encourage the integrated approach and reduce the barriers towards improved energy performance are discussed.

  9. Statistical Methods for Fuzzy Data

    CERN Document Server

    Viertl, Reinhard

    2011-01-01

    Statistical data are not always precise numbers, or vectors, or categories. Real data are frequently what is called fuzzy. Examples where this fuzziness is obvious are quality of life data, environmental, biological, medical, sociological and economics data. Also the results of measurements can be best described by using fuzzy numbers and fuzzy vectors respectively. Statistical analysis methods have to be adapted for the analysis of fuzzy data. In this book, the foundations of the description of fuzzy data are explained, including methods on how to obtain the characterizing function of fuzzy m

  10. Paired fuzzy sets

    DEFF Research Database (Denmark)

    Rodríguez, J. Tinguaro; Franco de los Ríos, Camilo; Gómez, Daniel

    2015-01-01

    In this paper we want to stress the relevance of paired fuzzy sets, as already proposed in previous works of the authors, as a family of fuzzy sets that offers a unifying view for different models based upon the opposition of two fuzzy sets, simply allowing the existence of different types...

  11. Fuzzy Arden Syntax: A fuzzy programming language for medicine.

    Science.gov (United States)

    Vetterlein, Thomas; Mandl, Harald; Adlassnig, Klaus-Peter

    2010-05-01

    The programming language Arden Syntax has been optimised for use in clinical decision support systems. We describe an extension of this language named Fuzzy Arden Syntax, whose original version was introduced in S. Tiffe's dissertation on "Fuzzy Arden Syntax: Representation and Interpretation of Vague Medical Knowledge by Fuzzified Arden Syntax" (Vienna University of Technology, 2003). The primary aim is to provide an easy means of processing vague or uncertain data, which frequently appears in medicine. For both propositional and number data types, fuzzy equivalents have been added to Arden Syntax. The Boolean data type was generalised to represent any truth degree between the two extremes 0 (falsity) and 1 (truth); fuzzy data types were introduced to represent fuzzy sets. The operations on truth values and real numbers were generalised accordingly. As the conditions to decide whether a certain programme unit is executed or not may be indeterminate, a Fuzzy Arden Syntax programme may split. The data in the different branches may be optionally aggregated subsequently. Fuzzy Arden Syntax offers the possibility to formulate conveniently Medical Logic Modules (MLMs) based on the principle of a continuously graded applicability of statements. Furthermore, ad hoc decisions about sharp value boundaries can be avoided. As an illustrative example shows, an MLM making use of the features of Fuzzy Arden Syntax is not significantly more complex than its Arden Syntax equivalent; in the ideal case, a programme handling crisp data remains practically unchanged when compared to its fuzzified version. In the latter case, the output data, which can be a set of weighted alternatives, typically depends continuously from the input data. In typical applications an Arden Syntax MLM can produce a different output after only slight changes of the input; discontinuities are in fact unavoidable when the input varies continuously but the output is taken from a discrete set of possibilities

  12. Optimizing pipeline transportation using a fuzzy controller

    Energy Technology Data Exchange (ETDEWEB)

    Aramaki, Thiago L.; Correa, Joao L. L.; Montalvoa, Antonio F. F. [National Control and Operation Center Tranpetro, Rio de Janeiro, (Brazil)

    2010-07-01

    The optimization of pipeline transportation is a big concern for the transporter companies. This paper is the third of a series of three articles which investigated the application of a system to simulate the human ability to operate a pipeline in an optimized way. The present paper presents the development of a proportional integral (PI) fuzzy controller, in order to optimize pipeline transportation capacity. The fuzzy adaptive PI controller system was developed and tested with a hydraulic simulator. On-field data were used from the OSBRA pipeline. The preliminary tests showed that the performance of the software simulation was satisfactory. It varied the set-point of the conventional controller within the limits of flow meters. The transport capacity of the pipe was maximize without compromising the integrity of the commodities transported. The system developed proved that it can be easily deployed as a specialist optimizing system to be added to SCADA systems.

  13. Intuitionistic fuzzy logics

    CERN Document Server

    T Atanassov, Krassimir

    2017-01-01

    The book offers a comprehensive survey of intuitionistic fuzzy logics. By reporting on both the author’s research and others’ findings, it provides readers with a complete overview of the field and highlights key issues and open problems, thus suggesting new research directions. Starting with an introduction to the basic elements of intuitionistic fuzzy propositional calculus, it then provides a guide to the use of intuitionistic fuzzy operators and quantifiers, and lastly presents state-of-the-art applications of intuitionistic fuzzy sets. The book is a valuable reference resource for graduate students and researchers alike.

  14. Research on conflict resolution of collaborative design with fuzzy case-based reasoning method

    Institute of Scientific and Technical Information of China (English)

    HOU Jun-ming; SU Chong; LIANG Shuang; WANG Wan-shan

    2009-01-01

    Collaborative design is a new style for modern mechanical design to meet the requirement of increasing competition. Designers of different places complete the same work, but the conflict appears in the process of design which may interface the design. Case-based reasoning (CBR) method is applied to the problem of conflict resolution, which is in the artificial intelligence field. However, due to the uncertainties in knowledge representation, attribute description, and similarity measures of CBR, it is very difficult to find the similar cases from case database. A fuzzy CBR method was proposed to solve the problem of conflict resolution in collaborative design. The process of fuzzy CBR was introduced. Based on the feature attributes and their relative weights determined by a fuzzy technique, a fuzzy CBR retrieving mechanism was developed to retrieve conflict resolution cases that tend to enhance the functions of the database. By indexing, calculating the weight and defuzzicating of the cases, the case similarity can be obtained. Then the case consistency was measured to keep the right result. Finally, the fuzzy CBR method for conflict resolution was demonstrated by means of a case study. The prototype system based on web is developed to illustrate the methodology.

  15. Application of fuzzy consensus for oral pre-cancer and cancer susceptibility assessment

    Directory of Open Access Journals (Sweden)

    Satarupa Banerjee

    2016-11-01

    Full Text Available Health questionnaire data assessment conventionally relies upon statistical analysis in understanding disease susceptibility using discrete numbers and fails to reflect physician’s perspectives and missing narratives in data, which play subtle roles in disease prediction. In addressing such limitations, the present study applies fuzzy consensus in oral health and habit questionnaire data for a selected Indian population in the context of assessing susceptibility to oral pre-cancer and cancer. Methodically collected data were initially divided into age based small subgroups and fuzzy membership function was assigned to each. The methodology further proposed the susceptibility to oral precancers (viz. leukoplakia, oral submucous fibrosis and squamous cell carcinoma in patients considering a fuzzy rulebase through If-Then rules with certain conditions. Incorporation of similarity measures using the Jaccard index was used during conversion into the linguistic output of fuzzy set to predict the disease outcome in a more accurate manner and associated condition of the relevant features. It is also expected that this analytical approach will be effective in devising strategies for policy making through real-life questionnaire data handling.

  16. SOS based robust H(∞) fuzzy dynamic output feedback control of nonlinear networked control systems.

    Science.gov (United States)

    Chae, Seunghwan; Nguang, Sing Kiong

    2014-07-01

    In this paper, a methodology for designing a fuzzy dynamic output feedback controller for discrete-time nonlinear networked control systems is presented where the nonlinear plant is modelled by a Takagi-Sugeno fuzzy model and the network-induced delays by a finite state Markov process. The transition probability matrix for the Markov process is allowed to be partially known, providing a more practical consideration of the real world. Furthermore, the fuzzy controller's membership functions and premise variables are not assumed to be the same as the plant's membership functions and premise variables, that is, the proposed approach can handle the case, when the premise of the plant are not measurable or delayed. The membership functions of the plant and the controller are approximated as polynomial functions, then incorporated into the controller design. Sufficient conditions for the existence of the controller are derived in terms of sum of square inequalities, which are then solved by YALMIP. Finally, a numerical example is used to demonstrate the validity of the proposed methodology.

  17. A SOCIOLOGICAL ANALYSIS OF THE CHILDBEARING COEFFICIENT IN THE ALTAI REGION BASED ON METHOD OF FUZZY LINEAR REGRESSION

    Directory of Open Access Journals (Sweden)

    Sergei Vladimirovich Varaksin

    2017-06-01

    Full Text Available Purpose. Construction of a mathematical model of the dynamics of childbearing change in the Altai region in 2000–2016, analysis of the dynamics of changes in birth rates for multiple age categories of women of childbearing age. Methodology. A auxiliary analysis element is the construction of linear mathematical models of the dynamics of childbearing by using fuzzy linear regression method based on fuzzy numbers. Fuzzy linear regression is considered as an alternative to standard statistical linear regression for short time series and unknown distribution law. The parameters of fuzzy linear and standard statistical regressions for childbearing time series were defined with using the built in language MatLab algorithm. Method of fuzzy linear regression is not used in sociological researches yet. Results. There are made the conclusions about the socio-demographic changes in society, the high efficiency of the demographic policy of the leadership of the region and the country, and the applicability of the method of fuzzy linear regression for sociological analysis.

  18. Qualitative case study methodology in nursing research: an integrative review.

    Science.gov (United States)

    Anthony, Susan; Jack, Susan

    2009-06-01

    This paper is a report of an integrative review conducted to critically analyse the contemporary use of qualitative case study methodology in nursing research. Increasing complexity in health care and increasing use of case study in nursing research support the need for current examination of this methodology. In 2007, a search for case study research (published 2005-2007) indexed in the CINAHL, MEDLINE, EMBASE, PsychINFO, Sociological Abstracts and SCOPUS databases was conducted. A sample of 42 case study research papers met the inclusion criteria. Whittemore and Knafl's integrative review method guided the analysis. Confusion exists about the name, nature and use of case study. This methodology, including terminology and concepts, is often invisible in qualitative study titles and abstracts. Case study is an exclusive methodology and an adjunct to exploring particular aspects of phenomena under investigation in larger or mixed-methods studies. A high quality of case study exists in nursing research. Judicious selection and diligent application of literature review methods promote the development of nursing science. Case study is becoming entrenched in the nursing research lexicon as a well-accepted methodology for studying phenomena in health and social care, and its growing use warrants continued appraisal to promote nursing knowledge development. Attention to all case study elements, process and publication is important in promoting authenticity, methodological quality and visibility.

  19. A fuzzy approach for modelling radionuclide in lake system

    International Nuclear Information System (INIS)

    Desai, H.K.; Christian, R.A.; Banerjee, J.; Patra, A.K.

    2013-01-01

    Radioactive liquid waste is generated during operation and maintenance of Pressurised Heavy Water Reactors (PHWRs). Generally low level liquid waste is diluted and then discharged into the near by water-body through blowdown water discharge line as per the standard waste management practice. The effluents from nuclear installations are treated adequately and then released in a controlled manner under strict compliance of discharge criteria. An attempt was made to predict the concentration of 3 H released from Kakrapar Atomic Power Station at Ratania Regulator, about 2.5 km away from the discharge point, where human exposure is expected. Scarcity of data and complex geometry of the lake prompted the use of Heuristic approach. Under this condition, Fuzzy rule based approach was adopted to develop a model, which could predict 3 H concentration at Ratania Regulator. Three hundred data were generated for developing the fuzzy rules, in which input parameters were water flow from lake and 3 H concentration at discharge point. The Output was 3 H concentration at Ratania Regulator. These data points were generated by multiple regression analysis of the original data. Again by using same methodology hundred data were generated for the validation of the model, which were compared against the predicted output generated by using Fuzzy Rule based approach. Root Mean Square Error of the model came out to be 1.95, which showed good agreement by Fuzzy model of natural ecosystem. -- Highlights: • Uncommon approach (Fuzzy Rule Base) of modelling radionuclide dispersion in Lake. • Predicts 3 H released from Kakrapar Atomic Power Station at a point of human exposure. • RMSE of fuzzy model is 1.95, which means, it has well imitated natural ecosystem

  20. (L,M-Fuzzy σ-Algebras

    Directory of Open Access Journals (Sweden)

    Fu-Gui Shi

    2010-01-01

    Full Text Available The notion of (L,M-fuzzy σ-algebras is introduced in the lattice value fuzzy set theory. It is a generalization of Klement's fuzzy σ-algebras. In our definition of (L,M-fuzzy σ-algebras, each L-fuzzy subset can be regarded as an L-measurable set to some degree.

  1. A Fuzzy Multi-Criteria SWOT Analysis: An Application to Nuclear Power Plant Site Selection

    Directory of Open Access Journals (Sweden)

    Mehmet Ekmekcioglu

    2011-08-01

    Full Text Available SWOT (Strengths, Weaknesses, Opportunities and Threats analysis is a commonly used and an important technique for analyzing internal and external environments in order to provide a systematic approach and support for a decision making. SWOT is criticized mostly for considering only qualitative examination of environmental factors, no priority for various factors and strategies, and no vagueness of the factors under fuzziness. In this paper, fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution integrated with fuzzy AHP (Analytical Hierarchy Process is used to develop fuzzy multi-criteria SWOT analysis in order to overcome these shortcomings. Nuclear power plant site selection, which is a strategic and important issue for Turkeyrs energy policy making, is considered as an application case study that demonstrated the applicability of the developed fuzzy SWOT model.

  2. Recurrent fuzzy ranking methods

    Science.gov (United States)

    Hajjari, Tayebeh

    2012-11-01

    With the increasing development of fuzzy set theory in various scientific fields and the need to compare fuzzy numbers in different areas. Therefore, Ranking of fuzzy numbers plays a very important role in linguistic decision-making, engineering, business and some other fuzzy application systems. Several strategies have been proposed for ranking of fuzzy numbers. Each of these techniques has been shown to produce non-intuitive results in certain case. In this paper, we reviewed some recent ranking methods, which will be useful for the researchers who are interested in this area.

  3. A new systematic and quantitative approach to characterization of surface nanostructures using fuzzy logic

    Science.gov (United States)

    Al-Mousa, Amjed A.

    Thin films are essential constituents of modern electronic devices and have a multitude of applications in such devices. The impact of the surface morphology of thin films on the device characteristics where these films are used has generated substantial attention to advanced film characterization techniques. In this work, we present a new approach to characterize surface nanostructures of thin films by focusing on isolating nanostructures and extracting quantitative information, such as the shape and size of the structures. This methodology is applicable to any Scanning Probe Microscopy (SPM) data, such as Atomic Force Microscopy (AFM) data which we are presenting here. The methodology starts by compensating the AFM data for some specific classes of measurement artifacts. After that, the methodology employs two distinct techniques. The first, which we call the overlay technique, proceeds by systematically processing the raster data that constitute the scanning probe image in both vertical and horizontal directions. It then proceeds by classifying points in each direction separately. Finally, the results from both the horizontal and the vertical subsets are overlaid, where a final decision on each surface point is made. The second technique, based on fuzzy logic, relies on a Fuzzy Inference Engine (FIE) to classify the surface points. Once classified, these points are clustered into surface structures. The latter technique also includes a mechanism which can consistently distinguish crowded surfaces from those with sparsely distributed structures and then tune the fuzzy technique system uniquely for that surface. Both techniques have been applied to characterize organic semiconductor thin films of pentacene on different substrates. Also, we present a case study to demonstrate the effectiveness of our methodology to identify quantitatively particle sizes of two specimens of gold nanoparticles of different nominal dimensions dispersed on a mica surface. A comparison

  4. Optimization Settings in the Fuzzy Combined Mamdani PID Controller

    Science.gov (United States)

    Kudinov, Y. I.; Pashchenko, F. F.; Pashchenko, A. F.; Kelina, A. Y.; Kolesnikov, V. A.

    2017-11-01

    In the present work the actual problem of determining the optimal settings of fuzzy parallel proportional-integral-derivative (PID) controller is considered to control nonlinear plants that is not always possible to perform with classical linear PID controllers. In contrast to the linear fuzzy PID controllers there are no analytical methods of settings calculation. In this paper, we develop a numerical optimization approach to determining the coefficients of a fuzzy PID controller. Decomposition method of optimization is proposed, the essence of which was as follows. All homogeneous coefficients were distributed to the relevant groups, for example, three error coefficients, the three coefficients of the changes of errors and the three coefficients of the outputs P, I and D components. Consistently in each of such groups the search algorithm was selected that has determined the coefficients under which we receive the schedule of the transition process satisfying all the applicable constraints. Thus, with the help of Matlab and Simulink in a reasonable time were found the factors of a fuzzy PID controller, which meet the accepted limitations on the transition process.

  5. Fuzzy Logic Unmanned Air Vehicle Motion Planning

    Directory of Open Access Journals (Sweden)

    Chelsea Sabo

    2012-01-01

    Full Text Available There are a variety of scenarios in which the mission objectives rely on an unmanned aerial vehicle (UAV being capable of maneuvering in an environment containing obstacles in which there is little prior knowledge of the surroundings. With an appropriate dynamic motion planning algorithm, UAVs would be able to maneuver in any unknown environment towards a target in real time. This paper presents a methodology for two-dimensional motion planning of a UAV using fuzzy logic. The fuzzy inference system takes information in real time about obstacles (if within the agent's sensing range and target location and outputs a change in heading angle and speed. The FL controller was validated, and Monte Carlo testing was completed to evaluate the performance. Not only was the path traversed by the UAV often the exact path computed using an optimal method, the low failure rate makes the fuzzy logic controller (FLC feasible for exploration. The FLC showed only a total of 3% failure rate, whereas an artificial potential field (APF solution, a commonly used intelligent control method, had an average of 18% failure rate. These results highlighted one of the advantages of the FLC method: its adaptability to complex scenarios while maintaining low control effort.

  6. Construction of Fuzzy Sets and Applying Aggregation Operators for Fuzzy Queries

    DEFF Research Database (Denmark)

    Hudec, Miroslav; Sudzina, Frantisek

    Flexible query conditions could use linguistic terms described by fuzzy sets. The question is how to properly construct fuzzy sets for each linguistic term and apply an adequate aggregation function. For construction of fuzzy sets, the lowest value, the highest value of attribute...... and the distribution of data inside its domain are used. The logarithmic transformation of domains appears to be suitable. This way leads to a balanced distribution of tuples over fuzzy sets. In addition, users’ opinions about linguistic terms as well as current content in database are merged. The second investigated...

  7. Simplified Fuzzy Control for Flux-Weakening Speed Control of IPMSM Drive

    Directory of Open Access Journals (Sweden)

    M. J. Hossain

    2011-01-01

    Full Text Available This paper presents a simplified fuzzy logic-based speed control scheme of an interior permanent magnet synchronous motor (IPMSM above the base speed using a flux-weakening method. In this work, nonlinear expressions of d-axis and q-axis currents of the IPMSM have been derived and subsequently incorporated in the control algorithm for the practical purpose in order to implement fuzzy-based flux-weakening strategy to operate the motor above the base speed. The fundamentals of fuzzy logic algorithms as related to motor control applications are also illustrated. A simplified fuzzy speed controller (FLC for the IPMSM drive has been designed and incorporated in the drive system to maintain high performance standards. The efficacy of the proposed simplified FLC-based IPMSM drive is verified by simulation at various dynamic operating conditions. The simplified FLC is found to be robust and efficient. Laboratory test results of proportional integral (PI controller-based IPMSM drive have been compared with the simulated results of fuzzy controller-based flux-weakening IPMSM drive system.

  8. OPTIMASI DENGAN ALGORITMA RSM-CCD PADA EVAPORATOR VAKUM WATERJET DENGAN PENGENDALI SUHU FUZZY PADA PEMBUATAN PERMEN SUSU (RSM-CCD Algorithm for Optimizing Waterjet Vacuum Evaporator Using Fuzzy Temperature Control in The Milk Candy Production

    Directory of Open Access Journals (Sweden)

    Yusuf Hendrawan

    2016-10-01

    Full Text Available Milk candy is a product which has to be produced under a high temperature to achieve the caramelization process. The use of vacuum system during a food processing is one of the alternatives to engineer the value of a material’s boiling point. The temperature control system and the mixing speed in machine that produce the milk candy were expected to be able to prevent the formation of off-flavour in the final product. A smart control system based on fuzzy logic was applied in the temperature control within the double jacket vacuum evaporator machine that needs stable temperature in the cooking process. The objective of this research is developing vacuum evaporator for milk candy production using fuzzy temperature control. The result in machine and system planning showed that the process of milk candy production was going on well. The parameter optimization of water content and ash content purposed to acquire the temperature point parameter and mixing speed in milk candy production. The optimization method was response surface methodology (RSM, by using the model of central composite design (CCD. The optimization resulted 90.18oC for the temperature parameter and 512 RPM for the mixing speed, with the prediction about 4.69% of water content and 1.57% of ash content. Keywords: Optimization, vacuum evaporator, fuzzy, milk candy, response surface methodology ABSTRAK Permen susu merupakan salah satu produk yang diolah dengan suhu tinggi untuk mencapai proses karamelisasi. Pengolahan pangan dengan sistem vakum merupakan salah satu alternatif untuk merekayasa nilai titik didih suatu bahan. Sistem pengendalian suhu serta kecepatan pengadukan pada mesin produksi permen susu diharapkan dapat mencegah terbentuknya partikel hitam (off-flavour pada produk akhir. Sistem kontrol cerdas logika fuzzy diaplikasikan dalam pengendalian suhu pada mesin evaporator vakum double jacket yang membutuhkan tingkat stabilitas suhu pemasakan permen susu. Tujuan dari

  9. Fuzzy social choice theory

    CERN Document Server

    B Gibilisco, Michael; E Albert, Karen; N Mordeson, John; J Wierman, Mark; D Clark, Terry

    2014-01-01

    This book offers a comprehensive analysis of the social choice literature and shows, by applying fuzzy sets, how the use of fuzzy preferences, rather than that of strict ones, may affect the social choice theorems. To do this, the book explores the presupposition of rationality within the fuzzy framework and shows that the two conditions for rationality, completeness and transitivity, do exist with fuzzy preferences. Specifically, this book examines: the conditions under which a maximal set exists; the Arrow’s theorem;  the Gibbard-Satterthwaite theorem; and the median voter theorem.  After showing that a non-empty maximal set does exists for fuzzy preference relations, this book goes on to demonstrating the existence of a fuzzy aggregation rule satisfying all five Arrowian conditions, including non-dictatorship. While the Gibbard-Satterthwaite theorem only considers individual fuzzy preferences, this work shows that both individuals and groups can choose alternatives to various degrees, resulting in a so...

  10. Evaluation of sustainable supply chain risk management using an integrated fuzzy TOPSIS- CRITIC approach

    DEFF Research Database (Denmark)

    Rostamzadeh, Reza; Ghorabaee, Mehdi Keshavarz; Govindan, Kannan

    2018-01-01

    Supply chain risk management research has mainly mistreated the important of sustainability issues. Moreover, there is little knowledge about sustainable management of risk and supply chain and the way they impose losses for firms. Risk management's duty in the supply chain is to identify, analyze......, and provide solutions for accountability, control and monitor the risks in the economic and production cycle. This study aims to develop a framework for the sustainable supply chain risk management (SSCRM) evaluation. To this end, an integrated fuzzy multi-criteria decision-making (MCDM) approach is proposed...... based on the technique in order of preference by similarity to ideal solution (TOPSIS) and criteria importance through inter-criteria correlation (CRITIC) methods. The literature was reviewed and the potential criteria were identified. Through an expert panel the criteria were filtered. Seven main...

  11. A Fuzzy Approach of the Competition on the Air Transport Market

    Science.gov (United States)

    Charfeddine, Souhir; DeColigny, Marc; Camino, Felix Mora; Cosenza, Carlos Alberto Nunes

    2003-01-01

    The aim of this communication is to study with a new scope the conditions of the equilibrium in an air transport market where two competitive airlines are operating. Each airline is supposed to adopt a strategy maximizing its profit while its estimation of the demand has a fuzzy nature. This leads each company to optimize a program of its proposed services (frequency of the flights and ticket prices) characterized by some fuzzy parameters. The case of monopoly is being taken as a benchmark. Classical convex optimization can be used to solve this decision problem. This approach provides the airline with a new decision tool where uncertainty can be taken into account explicitly. The confrontation of the strategies of the companies, in the ease of duopoly, leads to the definition of a fuzzy equilibrium. This concept of fuzzy equilibrium is more general and can be applied to several other domains. The formulation of the optimization problem and the methodological consideration adopted for its resolution are presented in their general theoretical aspect. In the case of air transportation, where the conditions of management of operations are critical, this approach should offer to the manager elements needed to the consolidation of its decisions depending on the circumstances (ordinary, exceptional events,..) and to be prepared to face all possibilities. Keywords: air transportation, competition equilibrium, convex optimization , fuzzy modeling,

  12. Relations Among Some Fuzzy Entropy Formulae

    Institute of Scientific and Technical Information of China (English)

    卿铭

    2004-01-01

    Fuzzy entropy has been widely used to analyze and design fuzzy systems, and many fuzzy entropy formulae have been proposed. For further in-deepth analysis of fuzzy entropy, the axioms and some important formulae of fuzzy entropy are introduced. Some equivalence results among these fuzzy entropy formulae are proved, and it is shown that fuzzy entropy is a special distance measurement.

  13. A semi-linguistic approach based on fuzzy set theory: application to expert judgments aggregation

    International Nuclear Information System (INIS)

    Ghyym, Seong Ho

    1998-01-01

    In the present work, a semi-linguistic fuzzy algorithm is proposed to obtain the fuzzy weighting values for multi-criterion, multi-alternative performance evaluation problem, with application to the aggregated estimate in the aggregation process of multi-expert judgments. The algorithm framework proposed is composed of the hierarchical structure, the semi-linguistic approach, the fuzzy R-L type integral value, and the total risk attitude index. In this work, extending the Chang/Chen method for triangular fuzzy numbers, the total risk attitude index is devised for a trapezoidal fuzzy number system. To illustrate the application of the algorithm proposed, a case problem available in literature is studied in connection to the weighting value evaluation of three-alternative (i.e., the aggregation of three-expert judgments) under seven-criterion. The evaluation results such as overall utility value, aggregation weighting value, and aggregated estimate obtained using the present fuzzy model are compared with those for other fuzzy models based on the Kim/Park method, the Liou/Wang method, and the Chang/Chen method

  14. A semi-linguistic approach based on fuzzy set theory: application to expert judgments aggregation

    Energy Technology Data Exchange (ETDEWEB)

    Ghyym, Seong Ho [KEPRI, Taejon (Korea, Republic of)

    1998-10-01

    In the present work, a semi-linguistic fuzzy algorithm is proposed to obtain the fuzzy weighting values for multi-criterion, multi-alternative performance evaluation problem, with application to the aggregated estimate in the aggregation process of multi-expert judgments. The algorithm framework proposed is composed of the hierarchical structure, the semi-linguistic approach, the fuzzy R-L type integral value, and the total risk attitude index. In this work, extending the Chang/Chen method for triangular fuzzy numbers, the total risk attitude index is devised for a trapezoidal fuzzy number system. To illustrate the application of the algorithm proposed, a case problem available in literature is studied in connection to the weighting value evaluation of three-alternative (i.e., the aggregation of three-expert judgments) under seven-criterion. The evaluation results such as overall utility value, aggregation weighting value, and aggregated estimate obtained using the present fuzzy model are compared with those for other fuzzy models based on the Kim/Park method, the Liou/Wang method, and the Chang/Chen method.

  15. Expert system for fault diagnosis in process control valves using fuzzy-logic

    Energy Technology Data Exchange (ETDEWEB)

    Carneiro, Alvaro L.G., E-mail: carneiro@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil); Porto Junior, Almir C.S., E-mail: almir@ctmsp.mar.mil.br [Centro Tecnologico da Marinha em Sao Paulo (CIANA/CTMSP), Ipero, SP (Brazil). Centro de Instrucao e Adestramento Nuclear de ARAMAR

    2013-07-01

    The models of asset maintenance of a process plant basically are classified in corrective maintenance, preventive, predictive and proactive (online). The corrective maintenance is the elementary and most obvious way of the maintenance models. The preventive maintenance consists in a fault prevention work, based on statistical studies that can lead to low efficiency or even an unexpected shutdown of the plant. Predictive maintenance aims to prevent equipment or systems failures through monitoring and tracking of parameters, allowing continuous operation as long as possible. The proactive maintenance usually includes predictive maintenance, emphasizing the root cause analysis of the failure. The maintenance predictive/proactive planning frequently uses software that integrates data from different systems, which facilitates a quick and effective decision- making. In nuclear plants this model has an important role regarding the reliability of equipment and systems. The main focus of this work is to study the development of a model of non-intrusive monitoring and diagnosis applied to process control valves using artificial intelligence by fuzzy logic technique, contributing in the development of predictive methodologies identifying faults in incipient state. The control valve analyzed belongs to a steam plant which simulates the secondary circuit of a PWR nuclear reactor - Pressurized Water Reactor. This study makes use of MATLAB language through the fuzzy logic toolbox which uses the method of inference Mamdani, acting by fuzzy conjunction, through Triangular Norms (t-norm) and Triangular Conorms (t-conorm). As input variables are used air pressure and displacement of the valve stem. Input data coming into the fuzzy system by graph of the automation system Delta V ® available in the plant, which receives a signal of electric current from an 'intelligent' positioned installed on the valve. The output variable is the 'status' of the valve. Through a

  16. Expert system for fault diagnosis in process control valves using fuzzy-logic

    International Nuclear Information System (INIS)

    Carneiro, Alvaro L.G.; Porto Junior, Almir C.S.

    2013-01-01

    The models of asset maintenance of a process plant basically are classified in corrective maintenance, preventive, predictive and proactive (online). The corrective maintenance is the elementary and most obvious way of the maintenance models. The preventive maintenance consists in a fault prevention work, based on statistical studies that can lead to low efficiency or even an unexpected shutdown of the plant. Predictive maintenance aims to prevent equipment or systems failures through monitoring and tracking of parameters, allowing continuous operation as long as possible. The proactive maintenance usually includes predictive maintenance, emphasizing the root cause analysis of the failure. The maintenance predictive/proactive planning frequently uses software that integrates data from different systems, which facilitates a quick and effective decision- making. In nuclear plants this model has an important role regarding the reliability of equipment and systems. The main focus of this work is to study the development of a model of non-intrusive monitoring and diagnosis applied to process control valves using artificial intelligence by fuzzy logic technique, contributing in the development of predictive methodologies identifying faults in incipient state. The control valve analyzed belongs to a steam plant which simulates the secondary circuit of a PWR nuclear reactor - Pressurized Water Reactor. This study makes use of MATLAB language through the fuzzy logic toolbox which uses the method of inference Mamdani, acting by fuzzy conjunction, through Triangular Norms (t-norm) and Triangular Conorms (t-conorm). As input variables are used air pressure and displacement of the valve stem. Input data coming into the fuzzy system by graph of the automation system Delta V ® available in the plant, which receives a signal of electric current from an 'intelligent' positioned installed on the valve. The output variable is the 'status' of the valve. Through a rule base

  17. New fuzzy EWMA control charts for monitoring phase II fuzzy profiles

    Directory of Open Access Journals (Sweden)

    Ghazale Moghadam

    2016-01-01

    Full Text Available In many quality control applications, the quality of a process or product is explained by the relationship between response variable and one or more explanatory variables, called a profile. In this paper, a new fuzzy EWMA control chart for phase II fuzzy profile monitoring is proposed. To this end, we extend EWMA control charts to its equivalent Fuzzy type and then implement fuzzy ranking methods to determine whether the process fuzzy profile is under or out of control. The proposed method is capable of identifying small changes in process under condition of process profile explaining parameters vagueness, roughness and uncertainty. Determining the source of changes, this method provides us with the possibility of recognizing the causes of process transition from stable mode, removing these causes and restoring the process stable mode.

  18. A modified dynamic evolving neural-fuzzy approach to modeling customer satisfaction for affective design.

    Science.gov (United States)

    Kwong, C K; Fung, K Y; Jiang, Huimin; Chan, K Y; Siu, Kin Wai Michael

    2013-01-01

    Affective design is an important aspect of product development to achieve a competitive edge in the marketplace. A neural-fuzzy network approach has been attempted recently to model customer satisfaction for affective design and it has been proved to be an effective one to deal with the fuzziness and non-linearity of the modeling as well as generate explicit customer satisfaction models. However, such an approach to modeling customer satisfaction has two limitations. First, it is not suitable for the modeling problems which involve a large number of inputs. Second, it cannot adapt to new data sets, given that its structure is fixed once it has been developed. In this paper, a modified dynamic evolving neural-fuzzy approach is proposed to address the above mentioned limitations. A case study on the affective design of mobile phones was conducted to illustrate the effectiveness of the proposed methodology. Validation tests were conducted and the test results indicated that: (1) the conventional Adaptive Neuro-Fuzzy Inference System (ANFIS) failed to run due to a large number of inputs; (2) the proposed dynamic neural-fuzzy model outperforms the subtractive clustering-based ANFIS model and fuzzy c-means clustering-based ANFIS model in terms of their modeling accuracy and computational effort.

  19. A Modified Dynamic Evolving Neural-Fuzzy Approach to Modeling Customer Satisfaction for Affective Design

    Directory of Open Access Journals (Sweden)

    C. K. Kwong

    2013-01-01

    Full Text Available Affective design is an important aspect of product development to achieve a competitive edge in the marketplace. A neural-fuzzy network approach has been attempted recently to model customer satisfaction for affective design and it has been proved to be an effective one to deal with the fuzziness and non-linearity of the modeling as well as generate explicit customer satisfaction models. However, such an approach to modeling customer satisfaction has two limitations. First, it is not suitable for the modeling problems which involve a large number of inputs. Second, it cannot adapt to new data sets, given that its structure is fixed once it has been developed. In this paper, a modified dynamic evolving neural-fuzzy approach is proposed to address the above mentioned limitations. A case study on the affective design of mobile phones was conducted to illustrate the effectiveness of the proposed methodology. Validation tests were conducted and the test results indicated that: (1 the conventional Adaptive Neuro-Fuzzy Inference System (ANFIS failed to run due to a large number of inputs; (2 the proposed dynamic neural-fuzzy model outperforms the subtractive clustering-based ANFIS model and fuzzy c-means clustering-based ANFIS model in terms of their modeling accuracy and computational effort.

  20. [Application of fuzzy mathematics on modifying taste of oral solution of traditional Chinese drug].

    Science.gov (United States)

    Wang, Youjie; Feng, Yi; Zhang, Bo

    2009-01-01

    To apply Fuzzy mathematical methods to choose the best taste modifying prescription of oral solution of traditional Chinese drug. Jin-Fukang oral solution was used as a model drug. The oral solution was prepared in different taste modifying prescriptions, whose tastes were evaluated by the fuzzy quality synthetic evaluation system. Compound-sweeteners with Sucralose and Erythritol was the best choice. Fuzzy integrated evaluation can be used to evaluate the taste of traditional Chinese medicinal pharmaceuticals, which overcame the artificial factors and achieve more objective conclusion.

  1. Design of a self-adaptive fuzzy PID controller for piezoelectric ceramics micro-displacement system

    Science.gov (United States)

    Zhang, Shuang; Zhong, Yuning; Xu, Zhongbao

    2008-12-01

    In order to improve control precision of the piezoelectric ceramics (PZT) micro-displacement system, a self-adaptive fuzzy Proportional Integration Differential (PID) controller is designed based on the traditional digital PID controller combining with fuzzy control. The arithmetic gives a fuzzy control rule table with the fuzzy control rule and fuzzy reasoning, through this table, the PID parameters can be adjusted online in real time control. Furthermore, the automatic selective control is achieved according to the change of the error. The controller combines the good dynamic capability of the fuzzy control and the high stable precision of the PID control, adopts the method of using fuzzy control and PID control in different segments of time. In the initial and middle stage of the transition process of system, that is, when the error is larger than the value, fuzzy control is used to adjust control variable. It makes full use of the fast response of the fuzzy control. And when the error is smaller than the value, the system is about to be in the steady state, PID control is adopted to eliminate static error. The problems of PZT existing in the field of precise positioning are overcome. The results of the experiments prove that the project is correct and practicable.

  2. Automatic thoracic anatomy segmentation on CT images using hierarchical fuzzy models and registration

    Science.gov (United States)

    Sun, Kaioqiong; Udupa, Jayaram K.; Odhner, Dewey; Tong, Yubing; Torigian, Drew A.

    2014-03-01

    This paper proposes a thoracic anatomy segmentation method based on hierarchical recognition and delineation guided by a built fuzzy model. Labeled binary samples for each organ are registered and aligned into a 3D fuzzy set representing the fuzzy shape model for the organ. The gray intensity distributions of the corresponding regions of the organ in the original image are recorded in the model. The hierarchical relation and mean location relation between different organs are also captured in the model. Following the hierarchical structure and location relation, the fuzzy shape model of different organs is registered to the given target image to achieve object recognition. A fuzzy connected delineation method is then used to obtain the final segmentation result of organs with seed points provided by recognition. The hierarchical structure and location relation integrated in the model provide the initial parameters for registration and make the recognition efficient and robust. The 3D fuzzy model combined with hierarchical affine registration ensures that accurate recognition can be obtained for both non-sparse and sparse organs. The results on real images are presented and shown to be better than a recently reported fuzzy model-based anatomy recognition strategy.

  3. Clinical effect of fuzzy numbers based on center of gravity ...

    African Journals Online (AJOL)

    In this study, a model called “fuzzy reasoning model” was proposed for the case when the explanatory variables were crisp and the value of the binary response variable was reported as a number between zero and one. In this regard, the concept of possibilistic odds is also introduced. Then, the methodology and ...

  4. Human reliability analysis data obtainment through fuzzy logic in nuclear plants

    International Nuclear Information System (INIS)

    Nascimento, C.S. do; Mesquita, R.N. de

    2012-01-01

    Highlights: ► Human Error Probability estimates from operator's reactions to emergency situations. ► Human Reliability Analysis input data obtainment through fuzzy logic inference. ► Performance Shaping Factors evaluation influence level onto the operator's actions. - Abstract: Human error has been recognized as an important factor for many industrial and nuclear accidents occurrence. Human error data is scarcely available for different reasons among which, lapses in historical database registry methodology is an important one. Human Reliability Analysis (HRA) is an usual tool employed to estimate the probability that an operator will reasonably perform a system required task in required time without degrading the system. This meta-analysis requires specific Human Error Probability estimates for most of its procedure. This work obtains Human Error Probability (HEP) estimates from operator's actions in response to emergency situations hypothesis on Research Reactor IEA-R1 from IPEN, Brazil. Through this proposed methodology HRA should be able to be performed even with shortage of related human error statistical data. A Performance Shaping Factors (PSF's) evaluation in order to classify and estimate their influence level onto the operator's actions and to determine their actual state over the plant was also done. Both HEP estimation and PSF evaluation were done based on expert judgment using interviews and questionnaires. Expert group was established based on selected IEA-R1 operators, and their evaluation were put into a knowledge representation system which used linguistic variables and group evaluation values that were obtained through Fuzzy Logic and Fuzzy Set theory. HEP obtained values show good agreement with literature published data corroborating the proposed methodology as a good alternative to be used on HRA.

  5. Takagi-Sugeno's fuzzy models

    Directory of Open Access Journals (Sweden)

    Yann Blanco

    2001-01-01

    Full Text Available This paper outlines a methodology to study the stability of Takagi-Sugeno's (TS fuzzy models. The stability analysis of the TS model is performed using a quadratic Liapunov candidate function. This paper proposes a relaxation of Tanaka's stability condition: unlike related works, the equations to be solved are not Liapunov equations for each rule matrix, but a convex combination of them. The coefficients of this sums depend on the membership functions. This method is applied to the design of continuous controllers for the TS model. Three different control structures are investigated, among which the Parallel Distributed Compensation (PDC. An application to the inverted pendulum is proposed here.

  6. An Integrated Risk Index Model Based on Hierarchical Fuzzy Logic for Underground Risk Assessment

    Directory of Open Access Journals (Sweden)

    Muhammad Fayaz

    2017-10-01

    Full Text Available Available space in congested cities is getting scarce due to growing urbanization in the recent past. The utilization of underground space is considered as a solution to the limited space in smart cities. The numbers of underground facilities are growing day by day in the developing world. Typical underground facilities include the transit subway, parking lots, electric lines, water supply and sewer lines. The likelihood of the occurrence of accidents due to underground facilities is a random phenomenon. To avoid any accidental loss, a risk assessment method is required to conduct the continuous risk assessment and report any abnormality before it happens. In this paper, we have proposed a hierarchical fuzzy inference based model for under-ground risk assessment. The proposed hierarchical fuzzy inference architecture reduces the total number of rules from the rule base. Rule reduction is important because the curse of dimensionality damages the transparency and interpretation as it is very tough to understand and justify hundreds or thousands of fuzzy rules. The computation time also increases as rules increase. The proposed model takes 175 rules having eight input parameters to compute the risk index, and the conventional fuzzy logic requires 390,625 rules, having the same number of input parameters to compute risk index. Hence, the proposed model significantly reduces the curse of dimensionality. Rule design for fuzzy logic is also a tedious task. In this paper, we have also introduced new rule schemes, namely maximum rule-based and average rule-based; both schemes can be used interchangeably according to the logic needed for rule design. The experimental results show that the proposed method is a virtuous choice for risk index calculation where the numbers of variables are greater.

  7. Integrated Fuzzy ANP, Fuzzy VIKOR and goal programming for sourcing in a supply chain: A case study from cable industry

    Directory of Open Access Journals (Sweden)

    Masoud Rezaei

    2013-10-01

    Full Text Available In today’s competitive business environment, companies strive to increase their market shares. All companies clearly understand that they have to reach this goal by implementing cost effective methods and increase profits as much as possible. The cost of purchasing raw materials and component parts are significant portion of products in most manufacturing firms. Supplier selection and evaluation have been widely recognized to be one of the most substantial issues on material purchasing. In order to choose reliable suppliers it is necessary to have a trade-off between some tangible and intangible factors where some of them are in serious conflict. In this paper, an integrated technique of analytical network process improved by VIKOR and fuzzy sets theory and multi-objective mixed integer nonlinear programming is proposed to determine the appropriate suppliers. The proposed model of this paper also determines the order quantity allocated to each supplier in the case of multiple sourcing, multiple products and multi-period time horizon for an Iranian cable company.

  8. Methodology for dimensional variation analysis of ITER integrated systems

    International Nuclear Information System (INIS)

    Fuentes, F. Javier; Trouvé, Vincent; Cordier, Jean-Jacques; Reich, Jens

    2016-01-01

    Highlights: • Tokamak dimensional management methodology, based on 3D variation analysis, is presented. • Dimensional Variation Model implementation workflow is described. • Methodology phases are described in detail. The application of this methodology to the tolerance analysis of ITER Vacuum Vessel is presented. • Dimensional studies are a valuable tool for the assessment of Tokamak PCR (Project Change Requests), DR (Deviation Requests) and NCR (Non-Conformance Reports). - Abstract: The ITER machine consists of a large number of complex systems highly integrated, with critical functional requirements and reduced design clearances to minimize the impact in cost and performances. Tolerances and assembly accuracies in critical areas could have a serious impact in the final performances, compromising the machine assembly and plasma operation. The management of tolerances allocated to part manufacture and assembly processes, as well as the control of potential deviations and early mitigation of non-compliances with the technical requirements, is a critical activity on the project life cycle. A 3D tolerance simulation analysis of ITER Tokamak machine has been developed based on 3DCS dedicated software. This integrated dimensional variation model is representative of Tokamak manufacturing functional tolerances and assembly processes, predicting accurate values for the amount of variation on critical areas. This paper describes the detailed methodology to implement and update the Tokamak Dimensional Variation Model. The model is managed at system level. The methodology phases are illustrated by its application to the Vacuum Vessel (VV), considering the status of maturity of VV dimensional variation model. The following topics are described in this paper: • Model description and constraints. • Model implementation workflow. • Management of input and output data. • Statistical analysis and risk assessment. The management of the integration studies based on

  9. Methodology for dimensional variation analysis of ITER integrated systems

    Energy Technology Data Exchange (ETDEWEB)

    Fuentes, F. Javier, E-mail: FranciscoJavier.Fuentes@iter.org [ITER Organization, Route de Vinon-sur-Verdon—CS 90046, 13067 St Paul-lez-Durance (France); Trouvé, Vincent [Assystem Engineering & Operation Services, rue J-M Jacquard CS 60117, 84120 Pertuis (France); Cordier, Jean-Jacques; Reich, Jens [ITER Organization, Route de Vinon-sur-Verdon—CS 90046, 13067 St Paul-lez-Durance (France)

    2016-11-01

    Highlights: • Tokamak dimensional management methodology, based on 3D variation analysis, is presented. • Dimensional Variation Model implementation workflow is described. • Methodology phases are described in detail. The application of this methodology to the tolerance analysis of ITER Vacuum Vessel is presented. • Dimensional studies are a valuable tool for the assessment of Tokamak PCR (Project Change Requests), DR (Deviation Requests) and NCR (Non-Conformance Reports). - Abstract: The ITER machine consists of a large number of complex systems highly integrated, with critical functional requirements and reduced design clearances to minimize the impact in cost and performances. Tolerances and assembly accuracies in critical areas could have a serious impact in the final performances, compromising the machine assembly and plasma operation. The management of tolerances allocated to part manufacture and assembly processes, as well as the control of potential deviations and early mitigation of non-compliances with the technical requirements, is a critical activity on the project life cycle. A 3D tolerance simulation analysis of ITER Tokamak machine has been developed based on 3DCS dedicated software. This integrated dimensional variation model is representative of Tokamak manufacturing functional tolerances and assembly processes, predicting accurate values for the amount of variation on critical areas. This paper describes the detailed methodology to implement and update the Tokamak Dimensional Variation Model. The model is managed at system level. The methodology phases are illustrated by its application to the Vacuum Vessel (VV), considering the status of maturity of VV dimensional variation model. The following topics are described in this paper: • Model description and constraints. • Model implementation workflow. • Management of input and output data. • Statistical analysis and risk assessment. The management of the integration studies based on

  10. Inference of RMR value using fuzzy set theory and neuro-fuzzy techniques

    Energy Technology Data Exchange (ETDEWEB)

    Bae, Gyu-Jin; Cho, Mahn-Sup [Korea Institute of Construction Technology, Koyang(Korea)

    2001-12-31

    In the design of tunnel, it contains inaccuracy of data, fuzziness of evaluation, observer error and so on. The face observation during tunnel excavation, therefore, plays an important role to raise stability and to reduce supporting cost. This study is carried out to minimize the subjectiveness of observer and to exactly evaluate the natural properties of ground during the face observation. For these purpose, fuzzy set theory and neuro-fuzzy techniques in artificial intelligent techniques are applied to the inference of the RMR(Rock Mass Rating) value from the observation data. The correlation between original RMR value and inferred RMR{sub {sub F}U} and RMR{sub {sub N}F} values from fuzzy Set theory and neuro-fuzzy techniques is investigated using 46 data. The results show that good correlation between original RMR value and inferred RMR{sub {sub F}U} and RMR{sub {sub N}F} values is observed when the correlation coefficients are |R|=0.96 and |R|=0.95 respectively. >From these results, applicability of fuzzy set theory and neuro-fuzzy techniques to rock mass classification is proved to be sufficiently high enough. (author). 17 refs., 5 tabs., 9 figs.

  11. Outdoor altitude stabilization of QuadRotor based on type-2 fuzzy and fuzzy PID

    Science.gov (United States)

    Wicaksono, H.; Yusuf, Y. G.; Kristanto, C.; Haryanto, L.

    2017-11-01

    This paper presents a design of altitude stabilization of QuadRotor based on type-2 fuzzy and fuzzy PID. This practical design is implemented outdoor. Barometric and sonar sensor were used in this experiment as an input for the controller YoHe. The throttle signal as a control input was provided by the controller to leveling QuadRotor in particular altitude and known well as altitude stabilization. The parameter of type-2 fuzzy and fuzzy PID was tuned in several heights to get the best control parameter for any height. Type-2 fuzzy produced better result than fuzzy PID but had a slow response in the beginning.

  12. Fuzzy set implementation for controlling and evaluation of factors affecting melting, crystallinity and interaction in polymer blends

    International Nuclear Information System (INIS)

    Al-Rawajfeh, Aiman Eid; Mamlook, Rustom

    2008-01-01

    In this study, the factors (i.e. weight fractions, crystallization temperatures and interaction such as hydrogen bonding) affecting melting, crystallinity, interaction parameters and miscibility of polymer blends (PB) have been studied by implementation of a fuzzy set. The interaction parameters were calculated using the Nishi-Wang equation, which is based on the Flory-Huggins theory. The values of interaction parameters χ 12 were negative for all blend compositions suggesting that χ 12 depends on the volume fraction (Φ) of the polymer. The various characteristics for the case study was synthesized and converted into relative weights w.r.t fuzzy set method. The fuzzy set analysis for the case study reveal increase as confirmed by the experimental data. The application of the fuzzy set methodology offers reasonable prediction and assessment for detecting yield in polymer blends

  13. ps-ro Fuzzy Open(Closed Functions and ps-ro Fuzzy Semi-Homeomorphism

    Directory of Open Access Journals (Sweden)

    Pankaj Chettri

    2015-11-01

    Full Text Available The aim of this paper is to introduce and characterize some new class of functions in a fuzzy topological space termed as ps-ro fuzzy open(closed functions, ps-ro fuzzy pre semiopen functions and ps-ro fuzzy semi-homeomorphism. The interrelation among these concepts and also their relations with the parallel existing concepts are established. It is also shown with the help of examples that these newly introduced concepts are independent of the well known existing allied concepts.

  14. Innovation and Integrity in Intervention Research: Conceptual Issues, Methodology, and Knowledge Translation.

    Science.gov (United States)

    Malti, Tina; Beelmann, Andreas; Noam, Gil G; Sommer, Simon

    2018-04-01

    In this article, we introduce the special issue entitled Innovation and Integrity in Intervention Science. Its focus is on essential problems and prospects for intervention research examining two related topics, i.e., methodological issues and research integrity, and challenges in the transfer of research knowledge into practice and policy. The main aims are to identify how to advance methodology in order to improve research quality, examine scientific integrity in the field of intervention science, and discuss future steps to enhance the transfer of knowledge about evidence-based intervention principles into sustained practice, routine activities, and policy decisions. Themes of the special issue are twofold. The first includes questions about research methodology in intervention science, both in terms of research design and methods, as well as data analyses and the reporting of findings. Second, the issue tackles questions surrounding the types of knowledge translation frameworks that might be beneficial to mobilize the transfer of research-based knowledge into practice and public policies. The issue argues that innovations in methodology and thoughtful approaches to knowledge translation can enable transparency, quality, and sustainability of intervention research.

  15. Fuzzy portfolio optimization advances in hybrid multi-criteria methodologies

    CERN Document Server

    Gupta, Pankaj; Inuiguchi, Masahiro; Chandra, Suresh

    2014-01-01

    This monograph presents a comprehensive study of portfolio optimization, an important area of quantitative finance. Considering that the information available in financial markets is incomplete and that the markets are affected by vagueness and ambiguity, the monograph deals with fuzzy portfolio optimization models. At first, the book makes the reader familiar with basic concepts, including the classical mean–variance portfolio analysis. Then, it introduces advanced optimization techniques and applies them for the development of various multi-criteria portfolio optimization models in an uncertain environment. The models are developed considering both the financial and non-financial criteria of investment decision making, and the inputs from the investment experts. The utility of these models in practice is then demonstrated using numerical illustrations based on real-world data, which were collected from one of the premier stock exchanges in India. The book addresses both academics and professionals pursuin...

  16. Incremental Adaptive Fuzzy Control for Sensorless Stroke Control of A Halbach-type Linear Oscillatory Motor

    Science.gov (United States)

    Lei, Meizhen; Wang, Liqiang

    2018-01-01

    The halbach-type linear oscillatory motor (HT-LOM) is multi-variable, highly coupled, nonlinear and uncertain, and difficult to get a satisfied result by conventional PID control. An incremental adaptive fuzzy controller (IAFC) for stroke tracking was presented, which combined the merits of PID control, the fuzzy inference mechanism and the adaptive algorithm. The integral-operation is added to the conventional fuzzy control algorithm. The fuzzy scale factor can be online tuned according to the load force and stroke command. The simulation results indicate that the proposed control scheme can achieve satisfied stroke tracking performance and is robust with respect to parameter variations and external disturbance.

  17. Synchronization of discrete-time spatiotemporal chaos via adaptive fuzzy control

    International Nuclear Information System (INIS)

    Xue Yueju; Yang Shiyuan

    2003-01-01

    A discrete-time adaptive fuzzy control scheme is presented to synchronize model-unknown coupled Henon-map lattices (CHMLs). The proposed method is robust to approximate errors, parameter mismatches and disturbances, because it integrates the merits of the adaptive fuzzy systems and the variable structure control with a sector. The simulation results of synchronization of CHMLs show that it not only can synchronize model-unknown CHMLs but also is robust against parameter mismatches and noise of the systems. These merits are advantageous for engineering realization

  18. Synchronization of discrete-time spatiotemporal chaos via adaptive fuzzy control

    Energy Technology Data Exchange (ETDEWEB)

    Xue Yueju E-mail: xueyj@mail.tsinghua.edu.cn; Yang Shiyuan E-mail: ysy-dau@tsinghua.edu.cn

    2003-08-01

    A discrete-time adaptive fuzzy control scheme is presented to synchronize model-unknown coupled Henon-map lattices (CHMLs). The proposed method is robust to approximate errors, parameter mismatches and disturbances, because it integrates the merits of the adaptive fuzzy systems and the variable structure control with a sector. The simulation results of synchronization of CHMLs show that it not only can synchronize model-unknown CHMLs but also is robust against parameter mismatches and noise of the systems. These merits are advantageous for engineering realization.

  19. A fuzzy logic sliding mode controlled electronic differential for a direct wheel drive EV

    Science.gov (United States)

    Ozkop, Emre; Altas, Ismail H.; Okumus, H. Ibrahim; Sharaf, Adel M.

    2015-11-01

    In this study, a direct wheel drive electric vehicle based on an electronic differential system with a fuzzy logic sliding mode controller (FLSMC) is studied. The conventional sliding surface is modified using a fuzzy rule base to obtain fuzzy dynamic sliding surfaces by changing its slopes using the global error and its derivative in a fuzzy logic inference system. The controller is compared with proportional-integral-derivative (PID) and sliding mode controllers (SMCs), which are usually preferred to be used in industry. The proposed controller provides robustness and flexibility to direct wheel drive electric vehicles. The fuzzy logic sliding mode controller, electronic differential system and the overall electrical vehicle mechanism are modelled and digitally simulated by using the Matlab software. Simulation results show that the system with FLSMC has better efficiency and performance compared to those of PID and SMCs.

  20. Design Genetic Algorithm Optimization Education Software Based Fuzzy Controller for a Tricopter Fly Path Planning

    Science.gov (United States)

    Tran, Huu-Khoa; Chiou, Juing -Shian; Peng, Shou-Tao

    2016-01-01

    In this paper, the feasibility of a Genetic Algorithm Optimization (GAO) education software based Fuzzy Logic Controller (GAO-FLC) for simulating the flight motion control of Unmanned Aerial Vehicles (UAVs) is designed. The generated flight trajectories integrate the optimized Scaling Factors (SF) fuzzy controller gains by using GAO algorithm. The…

  1. Determination of interrill soil erodibility coefficient based on Fuzzy and Fuzzy-Genetic Systems

    Directory of Open Access Journals (Sweden)

    Habib Palizvan Zand

    2017-02-01

    Full Text Available Introduction: Although the fuzzy logic science has been used successfully in various sudies of hydrology and soil erosion, but in literature review no article was found about its performance for estimating of interrill erodibility. On the other hand, studies indicate that genetic algorithm techniques can be used in fuzzy models and finding the appropriate membership functions for linguistic variables and fuzzy rules. So this study was conducted to develop the fuzzy and fuzzy–genetics models and investigation of their performance in the estimation of soil interrill erodibility factor (Ki. Materials and Methods: For this reason 36 soil samples with different physical and chemical properties were collected from west of Azerbaijan province . soilsamples were also taken from the Ap or A horizon of each soil profile. The samples were air-dried , sieved and Some soil characteristics such as soil texture, organic matter (OM, cation exchange capacity (CEC, sodium adsorption ratio (SAR, EC and pH were determined by the standard laboratory methods. Aggregates size distributions (ASD were determined by the wet-sieving method and fractal dimension of soil aggregates (Dn was also calculated. In order to determination of soil interrill erodibility, the flume experiment performed by packing soil a depth of 0.09-m in 0.5 × 1.0 m. soil was saturated from the base and adjusted to 9% slope and was subjected to at least 90 min rainfall . Rainfall intensity treatments were 20, 37 and 47 mm h-1. During each rainfall event, runoff was collected manually in different time intervals, being less than 60 s at the beginning, up to 15 min near the end of the test. At the end of the experiment, the volumes of runoff samples and the mass of sediment load at each time interval were measured. Finally interrill erodibility values were calculated using Kinnell (11 Equation. Then by statistical analyses Dn and sand percent of the soils were selected as input variables and Ki as

  2. Methodological Problems on the Way to Integrative Human Neuroscience.

    Science.gov (United States)

    Kotchoubey, Boris; Tretter, Felix; Braun, Hans A; Buchheim, Thomas; Draguhn, Andreas; Fuchs, Thomas; Hasler, Felix; Hastedt, Heiner; Hinterberger, Thilo; Northoff, Georg; Rentschler, Ingo; Schleim, Stephan; Sellmaier, Stephan; Tebartz Van Elst, Ludger; Tschacher, Wolfgang

    2016-01-01

    Neuroscience is a multidisciplinary effort to understand the structures and functions of the brain and brain-mind relations. This effort results in an increasing amount of data, generated by sophisticated technologies. However, these data enhance our descriptive knowledge , rather than improve our understanding of brain functions. This is caused by methodological gaps both within and between subdisciplines constituting neuroscience, and the atomistic approach that limits the study of macro- and mesoscopic issues. Whole-brain measurement technologies do not resolve these issues, but rather aggravate them by the complexity problem. The present article is devoted to methodological and epistemic problems that obstruct the development of human neuroscience. We neither discuss ontological questions (e.g., the nature of the mind) nor review data, except when it is necessary to demonstrate a methodological issue. As regards intradisciplinary methodological problems, we concentrate on those within neurobiology (e.g., the gap between electrical and chemical approaches to neurophysiological processes) and psychology (missing theoretical concepts). As regards interdisciplinary problems, we suggest that core disciplines of neuroscience can be integrated using systemic concepts that also entail human-environment relations. We emphasize the necessity of a meta-discussion that should entail a closer cooperation with philosophy as a discipline of systematic reflection. The atomistic reduction should be complemented by the explicit consideration of the embodiedness of the brain and the embeddedness of humans. The discussion is aimed at the development of an explicit methodology of integrative human neuroscience , which will not only link different fields and levels, but also help in understanding clinical phenomena.

  3. Methodological Problems on the Way to Integrative Human Neuroscience

    Science.gov (United States)

    Kotchoubey, Boris; Tretter, Felix; Braun, Hans A.; Buchheim, Thomas; Draguhn, Andreas; Fuchs, Thomas; Hasler, Felix; Hastedt, Heiner; Hinterberger, Thilo; Northoff, Georg; Rentschler, Ingo; Schleim, Stephan; Sellmaier, Stephan; Tebartz Van Elst, Ludger; Tschacher, Wolfgang

    2016-01-01

    Neuroscience is a multidisciplinary effort to understand the structures and functions of the brain and brain-mind relations. This effort results in an increasing amount of data, generated by sophisticated technologies. However, these data enhance our descriptive knowledge, rather than improve our understanding of brain functions. This is caused by methodological gaps both within and between subdisciplines constituting neuroscience, and the atomistic approach that limits the study of macro- and mesoscopic issues. Whole-brain measurement technologies do not resolve these issues, but rather aggravate them by the complexity problem. The present article is devoted to methodological and epistemic problems that obstruct the development of human neuroscience. We neither discuss ontological questions (e.g., the nature of the mind) nor review data, except when it is necessary to demonstrate a methodological issue. As regards intradisciplinary methodological problems, we concentrate on those within neurobiology (e.g., the gap between electrical and chemical approaches to neurophysiological processes) and psychology (missing theoretical concepts). As regards interdisciplinary problems, we suggest that core disciplines of neuroscience can be integrated using systemic concepts that also entail human-environment relations. We emphasize the necessity of a meta-discussion that should entail a closer cooperation with philosophy as a discipline of systematic reflection. The atomistic reduction should be complemented by the explicit consideration of the embodiedness of the brain and the embeddedness of humans. The discussion is aimed at the development of an explicit methodology of integrative human neuroscience, which will not only link different fields and levels, but also help in understanding clinical phenomena. PMID:27965548

  4. Integrated structure/control design - Present methodology and future opportunities

    Science.gov (United States)

    Weisshaar, T. A.; Newsom, J. R.; Zeiler, T. A.; Gilbert, M. G.

    1986-01-01

    Attention is given to current methodology applied to the integration of the optimal design process for structures and controls. Multilevel linear decomposition techniques proved to be most effective in organizing the computational efforts necessary for ISCD (integrated structures and control design) tasks. With the development of large orbiting space structures and actively controlled, high performance aircraft, there will be more situations in which this concept can be applied.

  5. GO-FLOW methodology. Basic concept and integrated analysis framework for its applications

    International Nuclear Information System (INIS)

    Matsuoka, Takeshi

    2010-01-01

    GO-FLOW methodology is a success oriented system analysis technique, and is capable of evaluating a large system with complex operational sequences. Recently an integrated analysis framework of the GO-FLOW has been developed for the safety evaluation of elevator systems by the Ministry of Land, Infrastructure, Transport and Tourism, Japanese Government. This paper describes (a) an Overview of the GO-FLOW methodology, (b) Procedure of treating a phased mission problem, (c) Common cause failure analysis, (d) Uncertainty analysis, and (e) Integrated analysis framework. The GO-FLOW methodology is a valuable and useful tool for system reliability analysis and has a wide range of applications. (author)

  6. LANDSLIDE SUSCEPTIBILITY ASSESSMENT THROUGH FUZZY LOGIC INFERENCE SYSTEM (FLIS

    Directory of Open Access Journals (Sweden)

    T. Bibi

    2016-09-01

    Full Text Available Landslide is among one of the most important natural hazards that lead to modification of the environment. It is a regular feature of a rapidly growing district Mansehra, Pakistan. This caused extensive loss of life and property in the district located at the foothills of Himalaya. Keeping in view the situation it is concluded that besides structural approaches the non-structural approaches such as hazard and risk assessment maps are effective tools to reduce the intensity of damage. A landslide susceptibility map is base for engineering geologists and geomorphologists. However, it is not easy to produce a reliable susceptibility map due to complex nature of landslides. Since 1980s, several mathematical models have been developed to map landslide susceptibility and hazard. Among various models this paper is discussing the effectiveness of fuzzy logic approach for landslide susceptibility mapping in District Mansehra, Pakistan. The factor maps were modified as landslide susceptibility and fuzzy membership functions were assessed for each class. Likelihood ratios are obtained for each class of contributing factors by considering the expert opinion. The fuzzy operators are applied to generate landslide susceptibility maps. According to this map, 17% of the study area is classified as high susceptibility, 32% as moderate susceptibility, 51% as low susceptibility and areas. From the results it is found that the fuzzy model can integrate effectively with various spatial data for landslide hazard mapping, suggestions in this study are hope to be helpful to improve the applications including interpretation, and integration phases in order to obtain an accurate decision supporting layer.

  7. A fuzzy logic intelligent diagnostic system for spacecraft integrated vehicle health management

    Science.gov (United States)

    Wu, G. Gordon

    1995-01-01

    Due to the complexity of future space missions and the large amount of data involved, greater autonomy in data processing is demanded for mission operations, training, and vehicle health management. In this paper, we develop a fuzzy logic intelligent diagnostic system to perform data reduction, data analysis, and fault diagnosis for spacecraft vehicle health management applications. The diagnostic system contains a data filter and an inference engine. The data filter is designed to intelligently select only the necessary data for analysis, while the inference engine is designed for failure detection, warning, and decision on corrective actions using fuzzy logic synthesis. Due to its adaptive nature and on-line learning ability, the diagnostic system is capable of dealing with environmental noise, uncertainties, conflict information, and sensor faults.

  8. A Fuzzy Collaborative Forecasting Approach for Forecasting the Productivity of a Factory

    Directory of Open Access Journals (Sweden)

    Yi-Chi Wang

    2013-01-01

    Full Text Available Productivity is always considered as one of the most basic and important factors to the competitiveness of a factory. For this reason, all factories have sought to enhance productivity. To achieve this goal, we first need to estimate the productivity. However, there is considerable degree of uncertainty in productivity. For this reason, a fuzzy collaborative forecasting approach is proposed in this study to forecast the productivity of a factory. First, a learning model is established to estimate the future productivity. Subsequently, the learning model is converted into three equivalent nonlinear programming problems to be solved from various viewpoints. The fuzzy productivity forecasts by different experts may not be equal and should therefore be aggregated. To this end, the fuzzy intersection and back propagation network approach is applied. The practical example of a dynamic random access memory (DRAM factory is used to evaluate the effectiveness of the proposed methodology.

  9. Impulsive control for a Takagi–Sugeno fuzzy model with time-delay and its application to chaotic systems

    International Nuclear Information System (INIS)

    Shi-Guo, Peng; Si-Min, Yu

    2009-01-01

    A control approach where the fuzzy logic methodology is combined with impulsive control is developed for controlling some time-delay chaotic systems in this paper. We first introduce impulses into each subsystem with delay of the Takagi–Sugeno (TS) fuzzy IF–THEN rules and then present a unified TS impulsive fuzzy model with delay for chaos control. Based on the new model, a simple and unified set of conditions for controlling chaotic systems is derived by the Lyapunov–Razumikhin method, and a design procedure for estimating bounds on control matrices is also given. Several numerical examples are presented to illustrate the effectiveness of this method

  10. The fuzzy cube and causal efficacy: representation of concomitant mechanisms in stroke.

    Science.gov (United States)

    Jobe, Thomas H.; Helgason, Cathy M.

    1998-04-01

    Twentieth century medical science has embraced nineteenth century Boolean probability theory based upon two-valued Aristotelian logic. With the later addition of bit-based, von Neumann structured computational architectures, an epistemology based on randomness has led to a bivalent epidemiological methodology that dominates medical decision making. In contrast, fuzzy logic, based on twentieth century multi-valued logic, and computational structures that are content addressed and adaptively modified, has advanced a new scientific paradigm for the twenty-first century. Diseases such as stroke involve multiple concomitant causal factors that are difficult to represent using conventional statistical methods. We tested which paradigm best represented this complex multi-causal clinical phenomenon-stroke. We show that the fuzzy logic paradigm better represented clinical complexity in cerebrovascular disease than current probability theory based methodology. We believe this finding is generalizable to all of clinical science since multiple concomitant causal factors are involved in nearly all known pathological processes.

  11. Development and comparison of integrated dynamics control systems with fuzzy logic control and sliding mode control

    International Nuclear Information System (INIS)

    Song, Jeong Hoon

    2013-01-01

    In this study, four integrated dynamics control (IDC) systems abbreviated as IDCB, IDCS, IDCF, and IDCR are developed, evaluated and compared. IDC systems were integrated with brake and steer control systems to enhance lateral stability and handling performance. To construct the IDC systems, a vehicle model with fourteen degrees of freedom, a fuzzy logic controller, and a sliding mode ABS controller were used. They were tested with various steering inputs when excessive full brake pressure or no brake pressure was applied on dry asphalt, wet asphalt, a snow-covered paved road, and a split-µ road. The results showed that an IDC-equipped vehicle improved lateral stability and controllability in every driving condition compared to an ABS-equipped vehicle. Under all road conditions, IDC controllers enabled the yaw rate to follow the reference yaw rate almost perfectly and reduced the body slip angle. On a split-µ road, IDCB, IDCS, IDCF, and IDCR vehicles drove straight ahead with only very small deviations.

  12. Use of a fuzzy decision-making method in evaluating severe accident management strategies

    International Nuclear Information System (INIS)

    Jae, M.; Moon, J.H.

    2002-01-01

    In developing severe accident management strategies, an engineering decision would be made based on the available data and information that are vague, imprecise and uncertain by nature. These sorts of vagueness and uncertainty are due to lack of knowledge for the severe accident sequences of interest. The fuzzy set theory offers a possibility of handling these sorts of data and information. In this paper, the possibility to apply the decision-making method based on fuzzy set theory to the evaluation of the accident management strategies at a nuclear power plant is scrutinized. The fuzzy decision-making method uses linguistic variables and fuzzy numbers to represent the decision-maker's subjective assessments for the decision alternatives according to the decision criteria. The fuzzy mean operator is used to aggregate the decision-maker's subjective assessments, while the total integral value method is used to rank the decision alternatives. As a case study, the proposed method is applied to evaluating the accident management strategies at a nuclear power plant

  13. A Fuzzy-AHP-QFD approach for achieving lean attributes for competitive advantages development, Case study: The Staam Sanat Company

    Directory of Open Access Journals (Sweden)

    Emad Roghanian

    2013-01-01

    Full Text Available As one of the new producing approaches, lean production has brought in new opportunities for producers all around the world. Many producers have adopted the technique for surviving the growing world market. By combining competitive advantages, lean attributes, and lean enablers as three factors, the present study attempts to determine the most suitable enablers for improvement of lean attributes in a case study. Quality Function Deployment (QFD in fuzzy environment and House of Quality (HOQ matrix, successfully employed for development of new products, are adopted as approach of the study. Weights of competitive advantages, lean attributes and enablers are calculated through fuzzy analysis hierarchy process (FAHP, while fuzzy logarithmic least square method (LLSM is used in calculation of the weights. Throughout the methodology, fuzzy logic is the basis for translating linguistic judgments required for the relationships and correlation matrix to numerical values. Moreover, final ranking of lean enablers is represented through area ranking method and taking into account various techniques of decision makers’ risk. Finally, a case study in automotive industry is introduced to demonstrate the implementation of the proposed methodology.

  14. Properties of Bipolar Fuzzy Hypergraphs

    OpenAIRE

    Akram, M.; Dudek, W. A.; Sarwar, S.

    2013-01-01

    In this article, we apply the concept of bipolar fuzzy sets to hypergraphs and investigate some properties of bipolar fuzzy hypergraphs. We introduce the notion of $A-$ tempered bipolar fuzzy hypergraphs and present some of their properties. We also present application examples of bipolar fuzzy hypergraphs.

  15. River water quality management considering agricultural return flows: application of a nonlinear two-stage stochastic fuzzy programming.

    Science.gov (United States)

    Tavakoli, Ali; Nikoo, Mohammad Reza; Kerachian, Reza; Soltani, Maryam

    2015-04-01

    In this paper, a new fuzzy methodology is developed to optimize water and waste load allocation (WWLA) in rivers under uncertainty. An interactive two-stage stochastic fuzzy programming (ITSFP) method is utilized to handle parameter uncertainties, which are expressed as fuzzy boundary intervals. An iterative linear programming (ILP) is also used for solving the nonlinear optimization model. To accurately consider the impacts of the water and waste load allocation strategies on the river water quality, a calibrated QUAL2Kw model is linked with the WWLA optimization model. The soil, water, atmosphere, and plant (SWAP) simulation model is utilized to determine the quantity and quality of each agricultural return flow. To control pollution loads of agricultural networks, it is assumed that a part of each agricultural return flow can be diverted to an evaporation pond and also another part of it can be stored in a detention pond. In detention ponds, contaminated water is exposed to solar radiation for disinfecting pathogens. Results of applying the proposed methodology to the Dez River system in the southwestern region of Iran illustrate its effectiveness and applicability for water and waste load allocation in rivers. In the planning phase, this methodology can be used for estimating the capacities of return flow diversion system and evaporation and detention ponds.

  16. Systematic methods for the design of a class of fuzzy logic controllers

    Science.gov (United States)

    Yasin, Saad Yaser

    2002-09-01

    Fuzzy logic control, a relatively new branch of control, can be used effectively whenever conventional control techniques become inapplicable or impractical. Various attempts have been made to create a generalized fuzzy control system and to formulate an analytically based fuzzy control law. In this study, two methods, the left and right parameterization method and the normalized spline-base membership function method, were utilized for formulating analytical fuzzy control laws in important practical control applications. The first model was used to design an idle speed controller, while the second was used to control an inverted control problem. The results of both showed that a fuzzy logic control system based on the developed models could be used effectively to control highly nonlinear and complex systems. This study also investigated the application of fuzzy control in areas not fully utilizing fuzzy logic control. Three important practical applications pertaining to the automotive industries were studied. The first automotive-related application was the idle speed of spark ignition engines, using two fuzzy control methods: (1) left and right parameterization, and (2) fuzzy clustering techniques and experimental data. The simulation and experimental results showed that a conventional controller-like performance fuzzy controller could be designed based only on experimental data and intuitive knowledge of the system. In the second application, the automotive cruise control problem, a fuzzy control model was developed using parameters adaptive Proportional plus Integral plus Derivative (PID)-type fuzzy logic controller. Results were comparable to those using linearized conventional PID and linear quadratic regulator (LQR) controllers and, in certain cases and conditions, the developed controller outperformed the conventional PID and LQR controllers. The third application involved the air/fuel ratio control problem, using fuzzy clustering techniques, experimental

  17. Active Queue Management in TCP Networks Based on Fuzzy-Pid Controller

    Directory of Open Access Journals (Sweden)

    Hossein ASHTIANI

    2012-01-01

    Full Text Available We introduce a novel and robust active queue management (AQM scheme based on a fuzzy controller, called hybrid fuzzy-PID controller. In the TCP network, AQM is important to regulate the queue length by passing or dropping the packets at the intermediate routers. RED, PI, and PID algorithms have been used for AQM. But these algorithms show weaknesses in the detection and control of congestion under dynamically changing network situations. In this paper a novel Fuzzy-based proportional-integral derivative (PID controller, which acts as an active queue manager (AQM for Internet routers, is proposed. These controllers are used to reduce packet loss and improve network utilization in TCP/IP networks. A new hybrid controller is proposed and compared with traditional RED based controller. Simulations are carried out to demonstrate the effectiveness of the proposed method and show that, the new hybrid fuzzy PID controller provides better performance than random early detection (RED and PID controllers

  18. Estimation of collapse moment for the wall-thinned pipe bends using fuzzy model identification

    International Nuclear Information System (INIS)

    Na, Man Gyun; Kim, Jin Weon; Hwang, In Joon

    2006-01-01

    In this work, the collapse moment due to wall-thinned defects is estimated through fuzzy model identification. A subtractive clustering method is used as the basis of a fast and robust algorithm for identifying the fuzzy model. The fuzzy model is optimized by a genetic algorithm combined with a least squares method. The developed fuzzy model has been applied to the numerical data obtained from the finite element analysis. Principal component analysis is used to preprocess the input signals into the fuzzy model to reduce the sensitivity to the input change and the fuzzy model are trained by using the data set prepared for training (training data) and verified by using another data set different (independent) from the training data. Also, three fuzzy models are trained, respectively, for three data sets divided into the three classes of extrados, intrados, and crown defects, which is because they have different characteristics. The relative root mean square (RMS) errors of the estimated collapse moment are 0.5397% for the training data and 0.8673% for the test data. It is known from this result that the fuzzy models are sufficiently accurate to be used in the integrity evaluation of wall-thinned pipe bends and elbows

  19. Synchronization of generalized Henon map by using adaptive fuzzy controller

    Energy Technology Data Exchange (ETDEWEB)

    Xue Yueju E-mail: xueyj@mail.tsinghua.edu.cn; Yang Shiyuan E-mail: ysy-dau@tsinghua.edu.cn

    2003-08-01

    In this paper, an adaptive fuzzy control method is presented to synchronize model-unknown discrete-time generalized Henon map. The proposed method is robust to approximate errors and disturbances, because it integrates the merits of adaptive fuzzy and the variable structure control. Moreover, it can realize the synchronizations of non-identical chaotic systems. The simulation results of synchronization of generalized Henon map show that it not only can synchronize model-unknown generalized Henon map but also is robust against the noise of the systems. These merits are advantageous for engineering realization.

  20. Synchronization of generalized Henon map by using adaptive fuzzy controller

    International Nuclear Information System (INIS)

    Xue Yueju; Yang Shiyuan

    2003-01-01

    In this paper, an adaptive fuzzy control method is presented to synchronize model-unknown discrete-time generalized Henon map. The proposed method is robust to approximate errors and disturbances, because it integrates the merits of adaptive fuzzy and the variable structure control. Moreover, it can realize the synchronizations of non-identical chaotic systems. The simulation results of synchronization of generalized Henon map show that it not only can synchronize model-unknown generalized Henon map but also is robust against the noise of the systems. These merits are advantageous for engineering realization

  1. Cardiovascular Dysautonomias Diagnosis Using Crisp and Fuzzy Decision Tree: A Comparative Study.

    Science.gov (United States)

    Kadi, Ilham; Idri, Ali

    2016-01-01

    Decision trees (DTs) are one of the most popular techniques for learning classification systems, especially when it comes to learning from discrete examples. In real world, many data occurred in a fuzzy form. Hence a DT must be able to deal with such fuzzy data. In fact, integrating fuzzy logic when dealing with imprecise and uncertain data allows reducing uncertainty and providing the ability to model fine knowledge details. In this paper, a fuzzy decision tree (FDT) algorithm was applied on a dataset extracted from the ANS (Autonomic Nervous System) unit of the Moroccan university hospital Avicenne. This unit is specialized on performing several dynamic tests to diagnose patients with autonomic disorder and suggest them the appropriate treatment. A set of fuzzy classifiers were generated using FID 3.4. The error rates of the generated FDTs were calculated to measure their performances. Moreover, a comparison between the error rates obtained using crisp and FDTs was carried out and has proved that the results of FDTs were better than those obtained using crisp DTs.

  2. TRStalker: an efficient heuristic for finding fuzzy tandem repeats.

    Science.gov (United States)

    Pellegrini, Marco; Renda, M Elena; Vecchio, Alessio

    2010-06-15

    Genomes in higher eukaryotic organisms contain a substantial amount of repeated sequences. Tandem Repeats (TRs) constitute a large class of repetitive sequences that are originated via phenomena such as replication slippage and are characterized by close spatial contiguity. They play an important role in several molecular regulatory mechanisms, and also in several diseases (e.g. in the group of trinucleotide repeat disorders). While for TRs with a low or medium level of divergence the current methods are rather effective, the problem of detecting TRs with higher divergence (fuzzy TRs) is still open. The detection of fuzzy TRs is propaedeutic to enriching our view of their role in regulatory mechanisms and diseases. Fuzzy TRs are also important as tools to shed light on the evolutionary history of the genome, where higher divergence correlates with more remote duplication events. We have developed an algorithm (christened TRStalker) with the aim of detecting efficiently TRs that are hard to detect because of their inherent fuzziness, due to high levels of base substitutions, insertions and deletions. To attain this goal, we developed heuristics to solve a Steiner version of the problem for which the fuzziness is measured with respect to a motif string not necessarily present in the input string. This problem is akin to the 'generalized median string' that is known to be an NP-hard problem. Experiments with both synthetic and biological sequences demonstrate that our method performs better than current state of the art for fuzzy TRs and that the fuzzy TRs of the type we detect are indeed present in important biological sequences. TRStalker will be integrated in the web-based TRs Discovery Service (TReaDS) at bioalgo.iit.cnr.it. Supplementary data are available at Bioinformatics online.

  3. Word Similarity from Dictionaries: Inferring Fuzzy Measures from Fuzzy Graphs

    Directory of Open Access Journals (Sweden)

    Vicenc Torra

    2008-01-01

    Full Text Available WORD SIMILARITY FROM DICTIONARIES: INFERRING FUZZY MEASURES FROM FUZZY GRAPHS The computation of similarities between words is a basic element of information retrieval systems, when retrieval is not solely based on word matching. In this work we consider a measure between words based on dictionaries. This is achieved assuming that a dictionary is formalized as a fuzzy graph. We show that the approach permits to compute measures not only for pairs of words but for sets of them.

  4. Comparison of fuzzy AHP and fuzzy TODIM methods for landfill location selection.

    Science.gov (United States)

    Hanine, Mohamed; Boutkhoum, Omar; Tikniouine, Abdessadek; Agouti, Tarik

    2016-01-01

    Landfill location selection is a multi-criteria decision problem and has a strategic importance for many regions. The conventional methods for landfill location selection are insufficient in dealing with the vague or imprecise nature of linguistic assessment. To resolve this problem, fuzzy multi-criteria decision-making methods are proposed. The aim of this paper is to use fuzzy TODIM (the acronym for Interactive and Multi-criteria Decision Making in Portuguese) and the fuzzy analytic hierarchy process (AHP) methods for the selection of landfill location. The proposed methods have been applied to a landfill location selection problem in the region of Casablanca, Morocco. After determining the criteria affecting the landfill location decisions, fuzzy TODIM and fuzzy AHP methods are applied to the problem and results are presented. The comparisons of these two methods are also discussed.

  5. A comparison of fuzzy logic-PID control strategies for PWR pressurizer control

    International Nuclear Information System (INIS)

    Kavaklioglu, K.; Ikonomopoulos, A.

    1993-01-01

    This paper describes the results obtained from a comparison performed between classical proportional-integral-derivative (PID) and fuzzy logic (FL) controlling the pressure in a pressurized water reactor (PWR). The two methodologies have been tested under various transient scenarios, and their performances are evaluated with respect to robustness and on-time response to external stimuli. One of the main concerns in the safe operation of PWR is the pressure control in the primary side of the system. In order to maintain the pressure in a PWR at the desired level, the pressurizer component equipped with sprayers, heaters, and safety relief valves is used. The control strategy in a Westinghouse PWR is implemented with a PID controller that initiates either the electric heaters or the sprayers, depending on the direction of the coolant pressure deviation from the setpoint

  6. A Comparison of Various Software Development Methodologies: Feasibility and Methods of Integration

    Directory of Open Access Journals (Sweden)

    Samir Abou El-Seoud

    2016-12-01

    Full Text Available System development methodologies which have being used in the academic and commercial environments during last two decades have advantages and disadvantages. Researchers had tried to identify objectives, scope …etc. of the methodologies by following different approaches. Each approach has its Limitation, specific interest, coverage …etc. In this paper, we tried to perform a comparative study of those methodologies which are popular and commonly used in banking and commercial environment. We tried in our study to determine objectives, scope, tools and other features of the methodologies. We also, tried to determine how and to what extent the methodologies incorporate the facilities such as project management, cost benefit analysis, documentation …etc. One of the most important aspects of our study was how to integrate the methodologies and develop a global methodology which covers the complete span of the software development life cycle? A prototype system which integrates the selected methodologies has been developed. The developed system helps analysts and designers how to choose suitable tools or to obtain guidelines on what to do in a particular situation. The prototype system has been tested during the development of a software for an ATM “Auto Teller Machine” by selecting and applying SASD methodology during software development. This resulted in the development of high quality and well documented software system.

  7. (Fuzzy) Ideals of BN-Algebras

    Science.gov (United States)

    Walendziak, Andrzej

    2015-01-01

    The notions of an ideal and a fuzzy ideal in BN-algebras are introduced. The properties and characterizations of them are investigated. The concepts of normal ideals and normal congruences of a BN-algebra are also studied, the properties of them are displayed, and a one-to-one correspondence between them is presented. Conditions for a fuzzy set to be a fuzzy ideal are given. The relationships between ideals and fuzzy ideals of a BN-algebra are established. The homomorphic properties of fuzzy ideals of a BN-algebra are provided. Finally, characterizations of Noetherian BN-algebras and Artinian BN-algebras via fuzzy ideals are obtained. PMID:26125050

  8. Implementation of the fuzzy theory in control of alternative energy generation system; Aplicacao da teoria fuzzy no controle de sistemas de geracao de energias alternativas

    Energy Technology Data Exchange (ETDEWEB)

    Caneppele, Fernando de Lima [Universidade Estadual Paulista (FCA/UNESP), Botucatu, SP (Brazil). Fac. de Ciencias Agronomicas. Curso de Pos-Graduacao em Energia na Agricultura], E-mail: fernando@itapeva.unesp.br; Seraphim, Odivaldo Jose [Universidade Estadual Paulista (FCA/UNESP), Botucatu, SP (Brazil). Fac. de Ciencias Agronomicas. Dept. de Engenharia Rural], E-mail: seraphim@fca.unesp.br

    2010-07-01

    This paper presents the application and use of a methodology based on fuzzy theory and simulates its use in intelligent control of a hybrid system for generating electricity, using solar energy, photovoltaic and wind. When using a fuzzy control system, it reached the point of maximum generation of energy, thus shifting all energy generated from the alternative sources-solar photovoltaic and wind, cargo and / or batteries when its use not immediately. The model uses three variables used for entry, which are: wind speed, solar radiation and loading the bank of batteries. For output variable has to choose which of the batteries of the battery bank is charged. For the simulations of this work is used MATLAB software. In this environment mathematical computational are analyzed and simulated all mathematical modeling, rules and other variables in the system described fuzzy. This model can be used in a system of control of hybrid systems for generating energy, providing the best use of energy sources, sun and wind, so we can extract the maximum energy possible these alternative sources without any prejudice to the environment. (author)

  9. Fuzzy multiobjective models for optimal operation of a hydropower system

    Science.gov (United States)

    Teegavarapu, Ramesh S. V.; Ferreira, André R.; Simonovic, Slobodan P.

    2013-06-01

    Optimal operation models for a hydropower system using new fuzzy multiobjective mathematical programming models are developed and evaluated in this study. The models use (i) mixed integer nonlinear programming (MINLP) with binary variables and (ii) integrate a new turbine unit commitment formulation along with water quality constraints used for evaluation of reservoir downstream impairment. Reardon method used in solution of genetic algorithm optimization problems forms the basis for development of a new fuzzy multiobjective hydropower system optimization model with creation of Reardon type fuzzy membership functions. The models are applied to a real-life hydropower reservoir system in Brazil. Genetic Algorithms (GAs) are used to (i) solve the optimization formulations to avoid computational intractability and combinatorial problems associated with binary variables in unit commitment, (ii) efficiently address Reardon method formulations, and (iii) deal with local optimal solutions obtained from the use of traditional gradient-based solvers. Decision maker's preferences are incorporated within fuzzy mathematical programming formulations to obtain compromise operating rules for a multiobjective reservoir operation problem dominated by conflicting goals of energy production, water quality and conservation releases. Results provide insight into compromise operation rules obtained using the new Reardon fuzzy multiobjective optimization framework and confirm its applicability to a variety of multiobjective water resources problems.

  10. Fuzzy Behaviors for Control of Mobile Robots

    Directory of Open Access Journals (Sweden)

    Saleh Zein-Sabatto

    2003-02-01

    Full Text Available In this research work, an RWI B-14 robot has been used as the development platform to embody some basic behaviors that can be combined to build more complex robotics behaviors. Emergency, avoid-obstacle, left wall- following, right wall-following, and move-to-point behaviors have been designed and embodied as basic robot behaviors. The basic behaviors developed in this research are designed based on fuzzy control technique and are integrated and coordinated to from complex robotics system. More behaviors can be added into the system as needed. A robot task can be defined by the user and executed by the intelligent robot control system. Testing results showed that fuzzy behaviors made the robot move intelligently and adapt to changes in its environment.

  11. An Application of Fuzzy Inference System by Clustering Subtractive Fuzzy Method for Estimating of Product Requirement

    Directory of Open Access Journals (Sweden)

    Fajar Ibnu Tufeil

    2009-06-01

    Full Text Available Model fuzzy memiliki kemampuan untuk menjelaskan secara linguistik suatu sistem yang terlalu kompleks. Aturan-aturan dalam model fuzzy pada umumnya dibangun berdasarkan keahlian manusia dan pengetahuan heuristik dari sistem yang dimodelkan. Teknik ini selanjutnya dikembangkan menjadi teknik yang dapat mengidentifikasi aturan-aturan dari suatu basis data yang telah dikelompokkan berdasarkan persamaan strukturnya. Dalam hal ini metode pengelompokan fuzzy berfungsi untuk mencari kelompok-kelompok data. Informasi yang dihasilkan dari metode pengelompokan ini, yaitu informasi tentang pusat kelompok, digunakan untuk membentuk aturan-aturan dalam sistem penalaran fuzzy. Dalam skripsi ini dibahas mengenai penerapan fuzzy infereance system dengan metode pengelompokan fuzzy subtractive clustering, yaitu untuk membentuk sistem penalaran fuzzy dengan menggunakan model fuzzy Takagi-Sugeno orde satu. Selanjutnya, metode pengelompokan fuzzy subtractive clustering diterapkan dalam memodelkan masalah dibidang pemasaran, yaitu untuk memprediksi permintaan pasar terhadap suatu produk susu. Aplikasi ini dibangun menggunakan Borland Delphi 6.0. Dari hasil pengujian diperoleh tingkat error prediksi terkecil yaitu dengan Error Average 0.08%.

  12. Practical Implementation for the interval type-2 fuzzy PID controller using a low cost microcontroller

    Directory of Open Access Journals (Sweden)

    Ahmad M. El-Nagar

    2014-06-01

    Full Text Available In this study, we propose an embedded real-time interval type-2 fuzzy proportional – integral – derivative (IT2F-PID controller which is a parallel combination of the interval type-2 fuzzy proportional – integral (IT2F-PI controller and the interval type-2 fuzzy proportional – derivative (IT2F-PD controller. The proposed IT2F-PID controller is able to handle the effect of the system uncertainties due to the structure of the interval type-2 fuzzy logic controller. The proposed IT2F-PID controller is implemented practically using a low cost PIC microcontroller for controlling the uncertain nonlinear inverted pendulum to minimize the effect of the system uncertainties due to the uncertainty in the mass of the pendulum, the measurement error in the rotation angle of the pendulum and the structural uncertainty. The test is carried out using the hardware-in-the-loop (HIL simulation. The experimental results show that the performance of the IT2F-PID controller improves significantly the performance over a wide range of system uncertainties.

  13. Sub-optimal control of fuzzy linear dynamical systems under granular differentiability concept.

    Science.gov (United States)

    Mazandarani, Mehran; Pariz, Naser

    2018-05-01

    This paper deals with sub-optimal control of a fuzzy linear dynamical system. The aim is to keep the state variables of the fuzzy linear dynamical system close to zero in an optimal manner. In the fuzzy dynamical system, the fuzzy derivative is considered as the granular derivative; and all the coefficients and initial conditions can be uncertain. The criterion for assessing the optimality is regarded as a granular integral whose integrand is a quadratic function of the state variables and control inputs. Using the relative-distance-measure (RDM) fuzzy interval arithmetic and calculus of variations, the optimal control law is presented as the fuzzy state variables feedback. Since the optimal feedback gains are obtained as fuzzy functions, they need to be defuzzified. This will result in the sub-optimal control law. This paper also sheds light on the restrictions imposed by the approaches which are based on fuzzy standard interval arithmetic (FSIA), and use strongly generalized Hukuhara and generalized Hukuhara differentiability concepts for obtaining the optimal control law. The granular eigenvalues notion is also defined. Using an RLC circuit mathematical model, it is shown that, due to their unnatural behavior in the modeling phenomenon, the FSIA-based approaches may obtain some eigenvalues sets that might be different from the inherent eigenvalues set of the fuzzy dynamical system. This is, however, not the case with the approach proposed in this study. The notions of granular controllability and granular stabilizability of the fuzzy linear dynamical system are also presented in this paper. Moreover, a sub-optimal control for regulating a Boeing 747 in longitudinal direction with uncertain initial conditions and parameters is gained. In addition, an uncertain suspension system of one of the four wheels of a bus is regulated using the sub-optimal control introduced in this paper. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  14. Human reliability analysis data obtainment through fuzzy logic in nuclear plants

    Energy Technology Data Exchange (ETDEWEB)

    Nascimento, C.S. do, E-mail: claudio.souza@ctmsp.mar.mil.br [Centro Tecnologico da Marinha em Sao Paulo (CTMSP), Av. Professor Lineu Prestes 2468, 05508-000 Sao Paulo, SP (Brazil); Mesquita, R.N. de, E-mail: rnavarro@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN - SP), Av. Professor Lineu Prestes 2242, 05508-000 Sao Paulo, SP (Brazil)

    2012-09-15

    Highlights: Black-Right-Pointing-Pointer Human Error Probability estimates from operator's reactions to emergency situations. Black-Right-Pointing-Pointer Human Reliability Analysis input data obtainment through fuzzy logic inference. Black-Right-Pointing-Pointer Performance Shaping Factors evaluation influence level onto the operator's actions. - Abstract: Human error has been recognized as an important factor for many industrial and nuclear accidents occurrence. Human error data is scarcely available for different reasons among which, lapses in historical database registry methodology is an important one. Human Reliability Analysis (HRA) is an usual tool employed to estimate the probability that an operator will reasonably perform a system required task in required time without degrading the system. This meta-analysis requires specific Human Error Probability estimates for most of its procedure. This work obtains Human Error Probability (HEP) estimates from operator's actions in response to emergency situations hypothesis on Research Reactor IEA-R1 from IPEN, Brazil. Through this proposed methodology HRA should be able to be performed even with shortage of related human error statistical data. A Performance Shaping Factors (PSF's) evaluation in order to classify and estimate their influence level onto the operator's actions and to determine their actual state over the plant was also done. Both HEP estimation and PSF evaluation were done based on expert judgment using interviews and questionnaires. Expert group was established based on selected IEA-R1 operators, and their evaluation were put into a knowledge representation system which used linguistic variables and group evaluation values that were obtained through Fuzzy Logic and Fuzzy Set theory. HEP obtained values show good agreement with literature published data corroborating the proposed methodology as a good alternative to be used on HRA.

  15. Diagnostics of D.C. Starter Generators While Using Fuzzy Logic Theory

    Directory of Open Access Journals (Sweden)

    A. A. Lobaty

    2011-01-01

    Full Text Available Methodology for sparking control in generator brush contact has been developed on the basis of the proposed fuzzy diagnostic model for ad.c.starter-generator and complex processing of diagnostic data. The paper provides investigation results, namely: dependence of voltage parameters  in an external generator circuit on collector sparking intensity.

  16. Fuzzy Multicriteria Decision Analysis for Adaptive Watershed Management

    Science.gov (United States)

    Chang, N.

    2006-12-01

    The dramatic changes of societal complexity due to intensive interactions among agricultural, industrial, and municipal sectors have resulted in acute issues of water resources redistribution and water quality management in many river basins. Given the fact that integrated watershed management is more a political and societal than a technical challenge, there is a need for developing a compelling method leading to justify a water-based land use program in some critical regions. Adaptive watershed management is viewed as an indispensable tool nowadays for providing step-wise constructive decision support that is concerned with all related aspects of the water consumption cycle and those facilities affecting water quality and quantity temporally and spatially. Yet the greatest challenge that decision makers face today is to consider how to leverage ambiguity, paradox, and uncertainty to their competitive advantage of management policy quantitatively. This paper explores a fuzzy multicriteria evaluation method for water resources redistribution and subsequent water quality management with respect to a multipurpose channel-reservoir system--the Tseng- Wen River Basin, South Taiwan. Four fuzzy operators tailored for this fuzzy multicriteria decision analysis depict greater flexibility in representing the complexity of various possible trade-offs among management alternatives constrained by physical, economic, and technical factors essential for adaptive watershed management. The management strategies derived may enable decision makers to integrate a vast number of internal weirs, water intakes, reservoirs, drainage ditches, transfer pipelines, and wastewater treatment facilities within the basin and bring up the permitting issue for transboundary diversion from a neighboring river basin. Experience gained indicates that the use of different types of fuzzy operators is highly instructive, which also provide unique guidance collectively for achieving the overarching goals

  17. Fuzzy control and identification

    CERN Document Server

    Lilly, John H

    2010-01-01

    This book gives an introduction to basic fuzzy logic and Mamdani and Takagi-Sugeno fuzzy systems. The text shows how these can be used to control complex nonlinear engineering systems, while also also suggesting several approaches to modeling of complex engineering systems with unknown models. Finally, fuzzy modeling and control methods are combined in the book, to create adaptive fuzzy controllers, ending with an example of an obstacle-avoidance controller for an autonomous vehicle using modus ponendo tollens logic.

  18. Fuzzy Expert System based on a Novel Hybrid Stem Cell (HSC) Algorithm for Classification of Micro Array Data.

    Science.gov (United States)

    Vijay, S Arul Antran; GaneshKumar, P

    2018-02-21

    In the growing scenario, microarray data is extensively used since it provides a more comprehensive understanding of genetic variants among diseases. As the gene expression samples have high dimensionality it becomes tedious to analyze the samples manually. Hence an automated system is needed to analyze these samples. The fuzzy expert system offers a clear classification when compared to the machine learning and statistical methodologies. In fuzzy classification, knowledge acquisition would be a major concern. Despite several existing approaches for knowledge acquisition much effort is necessary to enhance the learning process. This paper proposes an innovative Hybrid Stem Cell (HSC) algorithm that utilizes Ant Colony optimization and Stem Cell algorithm for designing fuzzy classification system to extract the informative rules to form the membership functions from the microarray dataset. The HSC algorithm uses a novel Adaptive Stem Cell Optimization (ASCO) to improve the points of membership function and Ant Colony Optimization to produce the near optimum rule set. In order to extract the most informative genes from the large microarray dataset a method called Mutual Information is used. The performance results of the proposed technique evaluated using the five microarray datasets are simulated. These results prove that the proposed Hybrid Stem Cell (HSC) algorithm produces a precise fuzzy system than the existing methodologies.

  19. Fuzzy pharmacology: theory and applications.

    Science.gov (United States)

    Sproule, Beth A; Naranjo, Claudio A; Türksen, I Burhan

    2002-09-01

    Fuzzy pharmacology is a term coined to represent the application of fuzzy logic and fuzzy set theory to pharmacological problems. Fuzzy logic is the science of reasoning, thinking and inference that recognizes and uses the real world phenomenon that everything is a matter of degree. It is an extension of binary logic that is able to deal with complex systems because it does not require crisp definitions and distinctions for the system components. In pharmacology, fuzzy modeling has been used for the mechanical control of drug delivery in surgical settings, and work has begun evaluating its use in other pharmacokinetic and pharmacodynamic applications. Fuzzy pharmacology is an emerging field that, based on these initial explorations, warrants further investigation.

  20. Application of fuzzy system theory in addressing the presence of uncertainties

    Energy Technology Data Exchange (ETDEWEB)

    Yusmye, A. Y. N. [Institute of Engineering Mathematics, Universiti Malaysia Perlis Kampus Pauh Putra, 02600, Arau, Perlis (Malaysia); Goh, B. Y.; Adnan, N. F.; Ariffin, A. K. [Department of Mechanical and Materials, Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia 43600 UKM Bangi, Selangor (Malaysia)

    2015-02-03

    In this paper, the combinations of fuzzy system theory with the finite element methods are present and discuss to deal with the uncertainties. The present of uncertainties is needed to avoid for prevent the failure of the material in engineering. There are three types of uncertainties, which are stochastic, epistemic and error uncertainties. In this paper, the epistemic uncertainties have been considered. For the epistemic uncertainty, it exists as a result of incomplete information and lack of knowledge or data. Fuzzy system theory is a non-probabilistic method, and this method is most appropriate to interpret the uncertainty compared to statistical approach when the deal with the lack of data. Fuzzy system theory contains a number of processes started from converting the crisp input to fuzzy input through fuzzification process and followed by the main process known as mapping process. The term mapping here means that the logical relationship between two or more entities. In this study, the fuzzy inputs are numerically integrated based on extension principle method. In the final stage, the defuzzification process is implemented. Defuzzification is an important process to allow the conversion of the fuzzy output to crisp outputs. Several illustrative examples are given and from the simulation, the result showed that propose the method produces more conservative results comparing with the conventional finite element method.

  1. Application of fuzzy system theory in addressing the presence of uncertainties

    International Nuclear Information System (INIS)

    Yusmye, A. Y. N.; Goh, B. Y.; Adnan, N. F.; Ariffin, A. K.

    2015-01-01

    In this paper, the combinations of fuzzy system theory with the finite element methods are present and discuss to deal with the uncertainties. The present of uncertainties is needed to avoid for prevent the failure of the material in engineering. There are three types of uncertainties, which are stochastic, epistemic and error uncertainties. In this paper, the epistemic uncertainties have been considered. For the epistemic uncertainty, it exists as a result of incomplete information and lack of knowledge or data. Fuzzy system theory is a non-probabilistic method, and this method is most appropriate to interpret the uncertainty compared to statistical approach when the deal with the lack of data. Fuzzy system theory contains a number of processes started from converting the crisp input to fuzzy input through fuzzification process and followed by the main process known as mapping process. The term mapping here means that the logical relationship between two or more entities. In this study, the fuzzy inputs are numerically integrated based on extension principle method. In the final stage, the defuzzification process is implemented. Defuzzification is an important process to allow the conversion of the fuzzy output to crisp outputs. Several illustrative examples are given and from the simulation, the result showed that propose the method produces more conservative results comparing with the conventional finite element method

  2. A Methodology for Conducting Integrative Mixed Methods Research and Data Analyses

    Science.gov (United States)

    Castro, Felipe González; Kellison, Joshua G.; Boyd, Stephen J.; Kopak, Albert

    2011-01-01

    Mixed methods research has gained visibility within the last few years, although limitations persist regarding the scientific caliber of certain mixed methods research designs and methods. The need exists for rigorous mixed methods designs that integrate various data analytic procedures for a seamless transfer of evidence across qualitative and quantitative modalities. Such designs can offer the strength of confirmatory results drawn from quantitative multivariate analyses, along with “deep structure” explanatory descriptions as drawn from qualitative analyses. This article presents evidence generated from over a decade of pilot research in developing an integrative mixed methods methodology. It presents a conceptual framework and methodological and data analytic procedures for conducting mixed methods research studies, and it also presents illustrative examples from the authors' ongoing integrative mixed methods research studies. PMID:22167325

  3. A fuzzy approach for modelling radionuclide in lake system.

    Science.gov (United States)

    Desai, H K; Christian, R A; Banerjee, J; Patra, A K

    2013-10-01

    Radioactive liquid waste is generated during operation and maintenance of Pressurised Heavy Water Reactors (PHWRs). Generally low level liquid waste is diluted and then discharged into the near by water-body through blowdown water discharge line as per the standard waste management practice. The effluents from nuclear installations are treated adequately and then released in a controlled manner under strict compliance of discharge criteria. An attempt was made to predict the concentration of (3)H released from Kakrapar Atomic Power Station at Ratania Regulator, about 2.5 km away from the discharge point, where human exposure is expected. Scarcity of data and complex geometry of the lake prompted the use of Heuristic approach. Under this condition, Fuzzy rule based approach was adopted to develop a model, which could predict (3)H concentration at Ratania Regulator. Three hundred data were generated for developing the fuzzy rules, in which input parameters were water flow from lake and (3)H concentration at discharge point. The Output was (3)H concentration at Ratania Regulator. These data points were generated by multiple regression analysis of the original data. Again by using same methodology hundred data were generated for the validation of the model, which were compared against the predicted output generated by using Fuzzy Rule based approach. Root Mean Square Error of the model came out to be 1.95, which showed good agreement by Fuzzy model of natural ecosystem. Copyright © 2013 Elsevier Ltd. All rights reserved.

  4. A fuzzy inference model for short-term load forecasting

    International Nuclear Information System (INIS)

    Mamlook, Rustum; Badran, Omar; Abdulhadi, Emad

    2009-01-01

    This paper is concerned with the short-term load forecasting (STLF) in power system operations. It provides load prediction for generation scheduling and unit commitment decisions, and therefore precise load forecasting plays an important role in reducing the generation cost and the spinning reserve capacity. Short-term electricity demand forecasting (i.e., the prediction of hourly loads (demand)) is one of the most important tools by which an electric utility/company plans, dispatches the loading of generating units in order to meet system demand. The accuracy of the dispatching system, which is derived from the accuracy of the forecasting algorithm used, will determine the economics of the operation of the power system. The inaccuracy or large error in the forecast simply means that load matching is not optimized and consequently the generation and transmission systems are not being operated in an efficient manner. In the present study, a proposed methodology has been introduced to decrease the forecasted error and the processing time by using fuzzy logic controller on an hourly base. Therefore, it predicts the effect of different conditional parameters (i.e., weather, time, historical data, and random disturbances) on load forecasting in terms of fuzzy sets during the generation process. These parameters are chosen with respect to their priority and importance. The forecasted values obtained by fuzzy method were compared with the conventionally forecasted ones. The results showed that the STLF of the fuzzy implementation have more accuracy and better outcomes

  5. Fuzzy data analysis

    CERN Document Server

    Bandemer, Hans

    1992-01-01

    Fuzzy data such as marks, scores, verbal evaluations, imprecise observations, experts' opinions and grey tone pictures, are quite common. In Fuzzy Data Analysis the authors collect their recent results providing the reader with ideas, approaches and methods for processing such data when looking for sub-structures in knowledge bases for an evaluation of functional relationship, e.g. in order to specify diagnostic or control systems. The modelling presented uses ideas from fuzzy set theory and the suggested methods solve problems usually tackled by data analysis if the data are real numbers. Fuzzy Data Analysis is self-contained and is addressed to mathematicians oriented towards applications and to practitioners in any field of application who have some background in mathematics and statistics.

  6. Genetic algorithm for project time-cost optimization in fuzzy environment

    Directory of Open Access Journals (Sweden)

    Khan Md. Ariful Haque

    2012-12-01

    Full Text Available Purpose: The aim of this research is to develop a more realistic approach to solve project time-cost optimization problem under uncertain conditions, with fuzzy time periods. Design/methodology/approach: Deterministic models for time-cost optimization are never efficient considering various uncertainty factors. To make such problems realistic, triangular fuzzy numbers and the concept of a-cut method in fuzzy logic theory are employed to model the problem. Because of NP-hard nature of the project scheduling problem, Genetic Algorithm (GA has been used as a searching tool. Finally, Dev-C++ 4.9.9.2 has been used to code this solver. Findings: The solution has been performed under different combinations of GA parameters and after result analysis optimum values of those parameters have been found for the best solution. Research limitations/implications: For demonstration of the application of the developed algorithm, a project on new product (Pre-paid electric meter, a project under government finance launching has been chosen as a real case. The algorithm is developed under some assumptions. Practical implications: The proposed model leads decision makers to choose the desired solution under different risk levels. Originality/value: Reports reveal that project optimization problems have never been solved under multiple uncertainty conditions. Here, the function has been optimized using Genetic Algorithm search technique, with varied level of risks and fuzzy time periods.

  7. Compound Option Pricing under Fuzzy Environment

    Directory of Open Access Journals (Sweden)

    Xiandong Wang

    2014-01-01

    Full Text Available Considering the uncertainty of a financial market includes two aspects: risk and vagueness; in this paper, fuzzy sets theory is applied to model the imprecise input parameters (interest rate and volatility. We present the fuzzy price of compound option by fuzzing the interest and volatility in Geske’s compound option pricing formula. For each α, the α-level set of fuzzy prices is obtained according to the fuzzy arithmetics and the definition of fuzzy-valued function. We apply a defuzzification method based on crisp possibilistic mean values of the fuzzy interest rate and fuzzy volatility to obtain the crisp possibilistic mean value of compound option price. Finally, we present a numerical analysis to illustrate the compound option pricing under fuzzy environment.

  8. Classification and Prioritization of Strategic Plans in Balanced Score Card (BSC Model by Fuzzy Quality Function Deployment and Zero-One Goal Programming (ZOGP

    Directory of Open Access Journals (Sweden)

    mehdi pourmostafa

    2012-02-01

    Full Text Available Due to continuous changes in organizational environment, there is no warranty for long term survival in the market. Currently, those organizations can succeed that are agile and able to rapidly respond to environmental requirements. In this research a model has been proposed for applying proper strategies for achieving long term organizational success. The proposed model is an integration of Balanced Score Card (BSC approach, Fuzzy Quality Function Development (FQFD and Zero-One Goal Programming (ZOGP. In fact by BSC, appropriate strategic plans can be designed and prioritized by FQFD. Then, based on multiple objectives and existing problem constraints, feasible strategic plans are identified by ZOGP. Findings imply that decision making techniques can be well utilized in designing BSC through a structured methodology make improvement in all aspects and have a positive influence on organization's performance in long term .   Keywords : B alanced Score Card , Fuzzy Quality Function Development, Zero-One Goal Programming, Strategic plans

  9. Fuzzy Control Tutorial

    DEFF Research Database (Denmark)

    Dotoli, M.; Jantzen, Jan

    1999-01-01

    The tutorial concerns automatic control of an inverted pendulum, especially rule based control by means of fuzzy logic. A ball balancer, implemented in a software simulator in Matlab, is used as a practical case study. The objectives of the tutorial are to teach the basics of fuzzy control......, and to show how to apply fuzzy logic in automatic control. The tutorial is distance learning, where students interact one-to-one with the teacher using e-mail....

  10. Pemodelan Sistem Fuzzy Dengan Menggunakan Matlab

    Directory of Open Access Journals (Sweden)

    Afan Galih Salman

    2010-12-01

    Full Text Available Fuzzy logic is a method in soft computing category, a method that could process uncertain, inaccurate, and less cost implemented data. Some methods in soft computing category besides fuzzy logic are artificial network nerve, probabilistic reasoning, and evolutionary computing. Fuzzy logic has the ability to develop fuzzy system that is intelligent system in uncertain environment. Some stages in fuzzy system formation process is input and output analysis, determining input and output variable, defining each fuzzy set member function, determining rules based on experience or knowledge of an expert in his field, and implementing fuzzy system. Overall, fuzzy logic uses simple mathematical concept, understandable, detectable uncertain and accurate data. Fuzzy system could create and apply expert experiences directly without exercise process and effort to decode the knowledge into a computer until becoming a modeling system that could be relied on decision making.

  11. Memory H ∞ performance control of a class T-S fuzzy system

    Science.gov (United States)

    Wang, Yanhua; He, Xiqin; Wu, Zhihua; Kang, Xiulan; Xiu, Wei

    2018-03-01

    For much nonlinear system in the control system, both the stability of the system and certain performance indicators are required. The characteristics of T-S model in fuzzy system make it possible to illustrate a great amount of nonlinear system efficiently. First and foremost, the T-S model with uncertainties and external disturbance is utilized to interpret nonlinear system so as to implement H∞ performance control by means of fuzzy control theory. Meantime, owing to the tremendous existence of time delay phenomenon in the controlled, feedback controller with memory fuzzy state is fabricated. On the basis of Lyapunov Stability Theory, the closed-loop system becomes stable by establishing Lyapunov function. Gain matrix of the memory state feedback controller is obtained by applying linear matrix inequality methodology. And simultaneously it makes the system meet the requirement of the H∞ performance indicator. Ultimately, the efficiency of the above-mentioned method is exemplified by the numerical computation.

  12. Modelling and Internal Fuzzy Model Power Control of a Francis Water Turbine

    Directory of Open Access Journals (Sweden)

    Klemen Nagode

    2014-02-01

    Full Text Available This paper presents dynamic modelling of a Francis turbine with a surge tank and the control of a hydro power plant (HPP. Non-linear and linear models include technical parameters and show high similarity to measurement data. Turbine power control with an internal model control (IMC is proposed, based on a turbine fuzzy model. Considering appropriate control responses in the entire area of turbine power, the model parameters of the process are determined from a fuzzy model, which are further included in the internal model controller. The results are compared to a proportional-integral (PI controller tuned with an integral absolute error (IAE objective function, and show an improved response of internal model control.

  13. A fuzzy approach to a multiple criteria and geographical information system for decision support on suitable locations for biogas plants

    DEFF Research Database (Denmark)

    Franco de los Rios, Camilo Andres; Bojesen, Mikkel; Hougaard, Jens Leth

    The purpose of this paper is to model the multi-criteria decision problem of identifying the most suitable facility locations for biogas plants under an integrated decision support methodology. Here the Geographical Information System (GIS) is used for measuring the attributes of the alternatives...... according to a given set of criteria. Measurements are taken in interval form, expressing the natural imprecision of common data, and the Fuzzy Weighted Overlap Dominance (FWOD) procedure is applied for aggregating and exploiting this kind of data, obtaining suitability degrees for every alternative....... The estimation of criteria weights, which is necessary for applying the FWOD procedure, is done by means of the Analytical Hierarchy Process (AHP), such that a combined AHP-FWOD methodology allows identifying the more suitable sites for building biogas plants. We show that the FWOD relevance-ranking procedure...

  14. Fuzzy Graph Language Recognizability

    OpenAIRE

    Kalampakas , Antonios; Spartalis , Stefanos; Iliadis , Lazaros

    2012-01-01

    Part 5: Fuzzy Logic; International audience; Fuzzy graph language recognizability is introduced along the lines of the established theory of syntactic graph language recognizability by virtue of the algebraic structure of magmoids. The main closure properties of the corresponding class are investigated and several interesting examples of fuzzy graph languages are examined.

  15. Fuzzy ABC: modeling the uncertainty in environmental cost allocation

    OpenAIRE

    Borba, José Alonso; Murcia, Fernando Dal Ri; Maior, Cesar Duarte Souto

    2007-01-01

    In many cases, preventing pollution and environmental destruction is cheaper than remedying these damages. In this sense, environmental cost allocation enables a better visualization and analysis of a product's profitability. However, the environmental allocation process involves estimated information and assumes linearity between activity consumption and product that is not real in many cases. In order to handle this not-linearity, this research presents a methodology based on fuzzy logic co...

  16. Safety critical application of fuzzy control

    International Nuclear Information System (INIS)

    Schildt, G.H.

    1995-01-01

    After an introduction into safety terms a short description of fuzzy logic will be given. Especially, for safety critical applications of fuzzy controllers a possible controller structure will be described. The following items will be discussed: Configuration of fuzzy controllers, design aspects like fuzzfiication, inference strategies, defuzzification and types of membership functions. As an example a typical fuzzy rule set will be presented. Especially, real-time behaviour a fuzzy controllers is mentioned. An example of fuzzy controlling for temperature control purpose within a nuclear reactor together with membership functions and inference strategy of such a fuzzy controller will be presented. (author). 4 refs, 17 figs

  17. Radiation protection and fuzzy set theory

    International Nuclear Information System (INIS)

    Nishiwaki, Y.

    1993-01-01

    In radiation protection we encounter a variety of sources of uncertainties which are due to fuzziness in our cognition or perception of objects. For systematic treatment of this type of uncertainty, the concepts of fuzzy sets or fuzzy measures could be applied to construct system models, which may take into consideration both subjective or intrinsic fuzziness and objective or extrinsic fuzziness. The theory of fuzzy sets and fuzzy measures is still in a developing stage, but its concept may be applied to various problems of subjective perception of risk, nuclear safety, radiation protection and also to the problems of man-machine interface and human factor engineering or ergonomic

  18. Multi-objective evolutionary algorithms for fuzzy classification in survival prediction.

    Science.gov (United States)

    Jiménez, Fernando; Sánchez, Gracia; Juárez, José M

    2014-03-01

    This paper presents a novel rule-based fuzzy classification methodology for survival/mortality prediction in severe burnt patients. Due to the ethical aspects involved in this medical scenario, physicians tend not to accept a computer-based evaluation unless they understand why and how such a recommendation is given. Therefore, any fuzzy classifier model must be both accurate and interpretable. The proposed methodology is a three-step process: (1) multi-objective constrained optimization of a patient's data set, using Pareto-based elitist multi-objective evolutionary algorithms to maximize accuracy and minimize the complexity (number of rules) of classifiers, subject to interpretability constraints; this step produces a set of alternative (Pareto) classifiers; (2) linguistic labeling, which assigns a linguistic label to each fuzzy set of the classifiers; this step is essential to the interpretability of the classifiers; (3) decision making, whereby a classifier is chosen, if it is satisfactory, according to the preferences of the decision maker. If no classifier is satisfactory for the decision maker, the process starts again in step (1) with a different input parameter set. The performance of three multi-objective evolutionary algorithms, niched pre-selection multi-objective algorithm, elitist Pareto-based multi-objective evolutionary algorithm for diversity reinforcement (ENORA) and the non-dominated sorting genetic algorithm (NSGA-II), was tested using a patient's data set from an intensive care burn unit and a standard machine learning data set from an standard machine learning repository. The results are compared using the hypervolume multi-objective metric. Besides, the results have been compared with other non-evolutionary techniques and validated with a multi-objective cross-validation technique. Our proposal improves the classification rate obtained by other non-evolutionary techniques (decision trees, artificial neural networks, Naive Bayes, and case

  19. Fuzziness and fuzzy modelling in Bulgaria's energy policy decision-making dilemma

    International Nuclear Information System (INIS)

    Wang Xingquan

    2006-01-01

    The decision complexity resulting from imprecision in decision variables and parameters, a major difficulty for conventional decision analysis methods, can be relevantly analysed and modelled by fuzzy logic. Bulgaria's nuclear policy decision-making process implicates such complexity of imprecise nature: stakeholders, criteria, measurement, etc. Given the suitable applicability of fuzzy logic in this case, this article tries to offer a concrete fuzzy paradigm including delimitation of decision space, quantification of imprecise variables, and, of course, parameterisation. (author)

  20. An optimization methodology for identifying robust process integration investments under uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Svensson, Elin; Berntsson, Thore [Department of Energy and Environment, Division of Heat and Power Technology, Chalmers University of Technology, SE-412 96 Goeteborg (Sweden); Stroemberg, Ann-Brith [Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Chalmers Science Park, SE-412 88 Gothenburg (Sweden); Patriksson, Michael [Department of Mathematical Sciences, Chalmers University of Technology and Department of Mathematical Sciences, University of Gothenburg, SE-412 96 Goeteborg (Sweden)

    2009-02-15

    Uncertainties in future energy prices and policies strongly affect decisions on investments in process integration measures in industry. In this paper, we present a five-step methodology for the identification of robust investment alternatives incorporating explicitly such uncertainties in the optimization model. Methods for optimization under uncertainty (or, stochastic programming) are thus combined with a deep understanding of process integration and process technology in order to achieve a framework for decision-making concerning the investment planning of process integration measures under uncertainty. The proposed methodology enables the optimization of investments in energy efficiency with respect to their net present value or an environmental objective. In particular, as a result of the optimization approach, complex investment alternatives, allowing for combinations of energy efficiency measures, can be analyzed. Uncertainties as well as time-dependent parameters, such as energy prices and policies, are modelled using a scenario-based approach, enabling the identification of robust investment solutions. The methodology is primarily an aid for decision-makers in industry, but it will also provide insight for policy-makers into how uncertainties regarding future price levels and policy instruments affect the decisions on investments in energy efficiency measures. (author)