WorldWideScience

Sample records for fuzzy information processing

  1. Image matching navigation based on fuzzy information

    Institute of Scientific and Technical Information of China (English)

    田玉龙; 吴伟仁; 田金文; 柳健

    2003-01-01

    In conventional image matching methods, the image matching process is mostly based on image statistic information. One aspect neglected by all these methods is that there is much fuzzy information contained in these images. A new fuzzy matching algorithm based on fuzzy similarity for navigation is presented in this paper. Because the fuzzy theory is of the ability of making good description of the fuzzy information contained in images, the image matching method based on fuzzy similarity would look forward to producing good performance results. Experimental results using matching algorithm based on fuzzy information also demonstrate its reliability and practicability.

  2. A geographic information system for gas power plant location using analytical hierarchy process and fuzzy logic

    International Nuclear Information System (INIS)

    Alavipoor, F. S.; Karimi, S.; Balist, J.; Khakian, A. H.

    2016-01-01

    This research recommends a geographic information system-based and multi-criteria evaluation for locating a gas power plant in Natanz City in Iran. The multi-criteria decision framework offers a hierarchy model to select a suitable place for a gas power plant. This framework includes analytic hierarchy process, fuzzy set theory and weighted linear combination. The analytic hierarchy process was applied to compare the importance of criteria among hierarchy elements classified by environmental group criteria. In the next step, the fuzzy logic was used to regulate the criteria through various fuzzy membership functions and fuzzy layers were formed by using fuzzy operators in the Arc-GIS environment. Subsequently, they were categorized into 6 classes using reclassify function. Then weighted linear combination was applied to combine the research layers. Finally, the two approaches were analyzed to find the most suitable place to set up a gas power plant. According to the results, the utilization of GAMMA fuzzy operator was shown to be suitable for this site selection.

  3. PROCESSING THE INFORMATION CONTENT ON THE BASIS OF FUZZY NEURAL MODEL OF DECISION MAKING

    Directory of Open Access Journals (Sweden)

    Nina V. Komleva

    2013-01-01

    Full Text Available The article is devoted to the issues of mathematical modeling of the decision-making process of information content processing based on the fuzzy neural network TSK. Integral rating assessment of the content, which is necessary for taking a decision about its further usage, is made depended on varying characteristics. Mechanism for building individual trajectory and forming individual competence is provided to make the intellectual content search.

  4. Fuzzy control of pressurizer dynamic process

    International Nuclear Information System (INIS)

    Ming Zhedong; Zhao Fuyu

    2006-01-01

    Considering the characteristics of pressurizer dynamic process, the fuzzy control system that takes the advantages of both fuzzy controller and PID controller is designed for the dynamic process in pressurizer. The simulation results illustrate this type of composite control system is with better qualities than those of single fuzzy controller and single PID controller. (authors)

  5. Imprecision and uncertainty in information representation and processing new tools based on intuitionistic fuzzy sets and generalized nets

    CERN Document Server

    Sotirov, Sotir

    2016-01-01

    The book offers a comprehensive and timely overview of advanced mathematical tools for both uncertainty analysis and modeling of parallel processes, with a special emphasis on intuitionistic fuzzy sets and generalized nets. The different chapters, written by active researchers in their respective areas, are structured to provide a coherent picture of this interdisciplinary yet still evolving field of science. They describe key tools and give practical insights into and research perspectives on the use of Atanassov's intuitionistic fuzzy sets and logic, and generalized nets for describing and dealing with uncertainty in different areas of science, technology and business, in a single, to date unique book. Here, readers find theoretical chapters, dealing with intuitionistic fuzzy operators, membership functions and algorithms, among other topics, as well as application-oriented chapters, reporting on the implementation of methods and relevant case studies in management science, the IT industry, medicine and/or ...

  6. Solar Farm Suitability Using Geographic Information System Fuzzy Sets and Analytic Hierarchy Processes: Case Study of Ulleung Island, Korea

    Directory of Open Access Journals (Sweden)

    Jangwon Suh

    2016-08-01

    Full Text Available Solar farm suitability in remote areas will involve a multi-criteria evaluation (MCE process, particularly well suited for the geographic information system (GIS environment. Photovoltaic (PV solar farm criteria were evaluated for an island-based case region having complex topographic and regulatory criteria, along with high demand for low-carbon local electricity production: Ulleung Island, Korea. Constraint variables that identified areas forbidden to PV farm development were consolidated into a single binary constraint layer (e.g., environmental regulation, ecological protection, future land use. Six factor variables were selected as influential on-site suitability within the geospatial database to seek out increased annual average power performance and reduced potential investment costs, forming new criteria layers for site suitability: solar irradiation, sunshine hours, average temperature in summer, proximity to transmission line, proximity to roads, and slope. Each factor variable was normalized via a fuzzy membership function (FMF and parameter setting based on the local characteristics and criteria for a fixed axis PV system. Representative weighting of the relative importance for each factor variable was assigned via pairwise comparison completed by experts. A suitability index (SI with six factor variables was derived using a weighted fuzzy summation method. Sensitivity analysis was conducted to assess four different SI based on the development scenarios (i.e., the combination of factors being considered. From the resulting map, three highly suitable regions were suggested and validated by comparison with satellite images to confirm the candidate sites for solar farm development. The GIS-MCE method proposed can also be applicable widely to other PV solar farm site selection projects with appropriate adaption for local variables.

  7. 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.

  8. 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

  9. 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,

  10. Information Clustering Based on Fuzzy Multisets.

    Science.gov (United States)

    Miyamoto, Sadaaki

    2003-01-01

    Proposes a fuzzy multiset model for information clustering with application to information retrieval on the World Wide Web. Highlights include search engines; term clustering; document clustering; algorithms for calculating cluster centers; theoretical properties concerning clustering algorithms; and examples to show how the algorithms work.…

  11. Green Degree Comprehensive Evaluation of Elevator Based on Fuzzy Analytic Hierarchy Process

    Directory of Open Access Journals (Sweden)

    Lizhen

    2015-01-01

    Full Text Available The green design of the elevator has many characteristics which contains many factors and the combination of qualitative and quantitative. In view of the fuzzy problem of evaluation index information, fuzzy analytic hierarchy process and fuzzy comprehensive evaluation model are combined to evaluate the green degree of elevator. In this method, the weights of the indexes are calculated by using the fuzzy analytic hierarchy process and the fuzzy analytic hierarchy process is used to calculate the weights of each level. The feasibility will be defined of using green degree evaluation of elevator system as an example to verify the method.

  12. Fuzzy Privacy Decision for Context-Aware Access Personal Information

    Institute of Scientific and Technical Information of China (English)

    ZHANG Qingsheng; QI Yong; ZHAO Jizhong; HOU Di; NIU Yujie

    2007-01-01

    A context-aware privacy protection framework was designed for context-aware services and privacy control methods about access personal information in pervasive environment. In the process of user's privacy decision, it can produce fuzzy privacy decision as the change of personal information sensitivity and personal information receiver trust. The uncertain privacy decision model was proposed about personal information disclosure based on the change of personal information receiver trust and personal information sensitivity. A fuzzy privacy decision information system was designed according to this model. Personal privacy control policies can be extracted from this information system by using rough set theory. It also solves the problem about learning privacy control policies of personal information disclosure.

  13. Selection of Vendor Based on Intuitionistic Fuzzy Analytical Hierarchy Process

    Directory of Open Access Journals (Sweden)

    Prabjot Kaur

    2014-01-01

    Full Text Available Business environment is characterized by greater domestic and international competitive position in the global market. Vendors play a key role in achieving the so-called corporate competition. It is not easy however to identify good vendors because evaluation is based on multiple criteria. In practice, for VSP most of the input information about the criteria is not known precisely. Intuitionistic fuzzy set is an extension of the classical fuzzy set theory (FST, which is a suitable way to deal with impreciseness. In other words, the application of intuitionistic fuzzy sets instead of fuzzy sets means the introduction of another degree of freedom called nonmembership function into the set description. In this paper, we proposed a triangular intuitionistic fuzzy number based approach for the vendor selection problem using analytical hierarchy process. The crisp data of the vendors is represented in the form of triangular intuitionistic fuzzy numbers. By applying AHP which involves decomposition, pairwise comparison, and deriving priorities for the various levels of the hierarchy, an overall crisp priority is obtained for ranking the best vendor. A numerical example illustrates our method. Lastly a sensitivity analysis is performed to find the most critical criterion on the basis of which vendor is selected.

  14. Fuzzy Control in the Process Industry

    DEFF Research Database (Denmark)

    Jantzen, Jan; Verbruggen, Henk; Østergaard, Jens-Jørgen

    1999-01-01

    Control problems in the process industry are dominated by non-linear and time-varying behaviour, many inner loops, and much interaction between the control loops. Fuzzy controllers have in some cases nevertheless mimicked the control actions of a human operator. Simple fuzzy controllers can...... be designed starting from PID controllers, and in more complex cases these can be used in connection with model-based predictive control. For high level control and supervisory control several simple controllers can be combined in a priority hierarchy such as the one developed in the cement industry...

  15. 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

  16. Use of fuzzy logic in signal processing and validation

    International Nuclear Information System (INIS)

    Heger, A.S.; Alang-Rashid, N.K.; Holbert, K.E.

    1993-01-01

    The advent of fuzzy logic technology has afforded another opportunity to reexamine the signal processing and validation process (SPV). The features offered by fuzzy logic can lend themselves to a more reliable and perhaps fault-tolerant approach to SPV. This is particularly attractive to complex system operations, where optimal control for safe operation depends on reliable input data. The reason for the use of fuzzy logic as the tool for SPV is its ability to transform information from the linguistic domain to a mathematical domain for processing and then transformation of its result back into the linguistic domain for presentation. To ensure the safe and optimal operation of a nuclear plant, for example, reliable and valid data must be available to the human and computer operators. Based on these input data, the operators determine the current state of the power plant and project corrective actions for future states. This determination is based on available data and the conceptual and mathematical models for the plant. A fault-tolerant SPV based on fuzzy logic can help the operators meet the objective of effective, efficient, and safe operation of the nuclear power plant. The ultimate product of this project will be a code that will assist plant operators in making informed decisions under uncertain conditions when conflicting signals may be present

  17. Fuzzy-based HAZOP study for process industry

    Energy Technology Data Exchange (ETDEWEB)

    Ahn, Junkeon; Chang, Daejun, E-mail: djchang@kaist.edu

    2016-11-05

    Highlights: • HAZOP is the important technique to evaluate system safety and its risks while process operations. • Fuzzy theory can handle the inherent uncertainties of process systems for the HAZOP. • Fuzzy-based HAZOP considers the aleatory and epistemic uncertainties and provides the risk level with less uncertainty. • Risk acceptance criteria should be considered regarding the transition region for each risk. - Abstract: This study proposed a fuzzy-based HAZOP for analyzing process hazards. Fuzzy theory was used to express uncertain states. This theory was found to be a useful approach to overcome the inherent uncertainty in HAZOP analyses. Fuzzy logic sharply contrasted with classical logic and provided diverse risk values according to its membership degree. Appropriate process parameters and guidewords were selected to describe the frequency and consequence of an accident. Fuzzy modeling calculated risks based on the relationship between the variables of an accident. The modeling was based on the mean expected value, trapezoidal fuzzy number, IF-THEN rules, and the center of gravity method. A cryogenic LNG (liquefied natural gas) testing facility was the objective process for the fuzzy-based and conventional HAZOPs. The most significant index is the frequency to determine risks. The comparison results showed that the fuzzy-based HAZOP provides better sophisticated risks than the conventional HAZOP. The fuzzy risk matrix presents the significance of risks, negligible risks, and necessity of risk reduction.

  18. using fuzzy logic in image processing

    International Nuclear Information System (INIS)

    Ashabrawy, M.A.F.

    2002-01-01

    due to the unavoidable merge between computer and mathematics, the signal processing in general and the processing in particular have greatly improved and advanced. signal processing deals with the processing of any signal data for use by a computer, while image processing deals with all kinds of images (just images). image processing involves the manipulation of image data for better appearance and viewing by people; consequently, it is a rapidly growing and exciting field to be involved in today . this work takes an applications - oriented approach to image processing .the applications; the maps and documents of the first egyptian research reactor (ETRR-1), the x-ray medical images and the fingerprints image. since filters, generally, work continuous ranges rather than discrete values, fuzzy logic techniques are more convenient.thee techniques are powerful in image processing and can deal with one- dimensional, 1-D and two - dimensional images, 2-D images as well

  19. Some fuzzy techniques for staff selection process: A survey

    Science.gov (United States)

    Md Saad, R.; Ahmad, M. Z.; Abu, M. S.; Jusoh, M. S.

    2013-04-01

    With high level of business competition, it is vital to have flexible staff that are able to adapt themselves with work circumstances. However, staff selection process is not an easy task to be solved, even when it is tackled in a simplified version containing only a single criterion and a homogeneous skill. When multiple criteria and various skills are involved, the problem becomes much more complicated. In adddition, there are some information that could not be measured precisely. This is patently obvious when dealing with opinions, thoughts, feelings, believes, etc. One possible tool to handle this issue is by using fuzzy set theory. Therefore, the objective of this paper is to review the existing fuzzy techniques for solving staff selection process. It classifies several existing research methods and identifies areas where there is a gap and need further research. Finally, this paper concludes by suggesting new ideas for future research based on the gaps identified.

  20. 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)

  1. Fuzzy model for Laser Assisted Bending Process

    Directory of Open Access Journals (Sweden)

    Giannini Oliviero

    2016-01-01

    Full Text Available In the present study, a fuzzy model was developed to predict the residual bending in a conventional metal bending process assisted by a high power diode laser. The study was focused on AA6082T6 aluminium thin sheets. In most dynamic sheet metal forming operations, the highly nonlinear deformation processes cause large amounts of elastic strain energy stored in the formed material. The novel hybrid forming process was thus aimed at inducing the local heating of the mechanically bent workpiece in order to decrease or eliminate the related springback phenomena. In particular, the influence on the extent of springback phenomena of laser process parameters such as source power, scan speed and starting elastic deformation of mechanically bent sheets, was experimentally assessed. Consistent trends in experimental response according to operational parameters were found. Accordingly, 3D process maps of the extent of the springback phenomena according to operational parameters were constructed. The effect of the inherent uncertainties on the predicted residual bending caused by the approximation in the model parameters was evaluated. In particular, a fuzzy-logic based approach was used to describe the model uncertainties and the transformation method was applied to propagate their effect on the residual bending.

  2. 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.

  3. 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.

  4. Fuzzy analytical hierarchy process and GIS for predictive cu -au ...

    African Journals Online (AJOL)

    Mineral exploration generally starts on small scale (small areas) and, then progresses to large scale (small area). There are many methods for achieving this goal. To achieve this goal one of these methods is Fuzzy analytical hierarchy process (Fuzzy AHP) that is the most popular multi-criteria decision-making techniques.

  5. 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

  6. 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.

  7. Formalization of software requirements for information systems using fuzzy logic

    Science.gov (United States)

    Yegorov, Y. S.; Milov, V. R.; Kvasov, A. S.; Sorokoumova, S. N.; Suvorova, O. V.

    2018-05-01

    The paper considers an approach to the design of information systems based on flexible software development methodologies. The possibility of improving the management of the life cycle of information systems by assessing the functional relationship between requirements and business objectives is described. An approach is proposed to establish the relationship between the degree of achievement of business objectives and the fulfillment of requirements for the projected information system. It describes solutions that allow one to formalize the process of formation of functional and non-functional requirements with the help of fuzzy logic apparatus. The form of the objective function is formed on the basis of expert knowledge and is specified via learning from very small data set.

  8. Multi-Model Adaptive Fuzzy Controller for a CSTR Process

    Directory of Open Access Journals (Sweden)

    Shubham Gogoria

    2015-09-01

    Full Text Available Continuous Stirred Tank Reactors are intensively used to control exothermic reactions in chemical industries. It is a very complex multi-variable system with non-linear characteristics. This paper deals with linearization of the mathematical model of a CSTR Process. Multi model adaptive fuzzy controller has been designed to control the reactor concentration and temperature of CSTR process. This method combines the output of multiple Fuzzy controllers, which are operated at various operating points. The proposed solution is a straightforward implementation of Fuzzy controller with gain scheduler to control the linearly inseparable parameters of a highly non-linear process.

  9. Modelling and management of subjective information in a fuzzy setting

    Science.gov (United States)

    Bouchon-Meunier, Bernadette; Lesot, Marie-Jeanne; Marsala, Christophe

    2013-01-01

    Subjective information is very natural for human beings. It is an issue at the crossroad of cognition, semiotics, linguistics, and psycho-physiology. Its management requires dedicated methods, among which we point out the usefulness of fuzzy and possibilistic approaches and related methods, such as evidence theory. We distinguish three aspects of subjectivity: the first deals with perception and sensory information, including the elicitation of quality assessment and the establishment of a link between physical and perceived properties; the second is related to emotions, their fuzzy nature, and their identification; and the last aspect stems from natural language and takes into account information quality and reliability of information.

  10. Fuzzy Information Retrieval Using Genetic Algorithms and Relevance Feedback.

    Science.gov (United States)

    Petry, Frederick E.; And Others

    1993-01-01

    Describes an approach that combines concepts from information retrieval, fuzzy set theory, and genetic programing to improve weighted Boolean query formulation via relevance feedback. Highlights include background on information retrieval systems; genetic algorithms; subproblem formulation; and preliminary results based on a testbed. (Contains 12…

  11. Evaluating supplier quality performance using fuzzy analytical hierarchy process

    Science.gov (United States)

    Ahmad, Nazihah; Kasim, Maznah Mat; Rajoo, Shanmugam Sundram Kalimuthu

    2014-12-01

    Evaluating supplier quality performance is vital in ensuring continuous supply chain improvement, reducing the operational costs and risks towards meeting customer's expectation. This paper aims to illustrate an application of Fuzzy Analytical Hierarchy Process to prioritize the evaluation criteria in a context of automotive manufacturing in Malaysia. Five main criteria were identified which were quality, cost, delivery, customer serviceand technology support. These criteria had been arranged into hierarchical structure and evaluated by an expert. The relative importance of each criteria was determined by using linguistic variables which were represented as triangular fuzzy numbers. The Center of Gravity defuzzification method was used to convert the fuzzy evaluations into their corresponding crisps values. Such fuzzy evaluation can be used as a systematic tool to overcome the uncertainty evaluation of suppliers' performance which usually associated with human being subjective judgments.

  12. Fuzzy Search Method for Hi Education Information Security

    Directory of Open Access Journals (Sweden)

    Grigory Grigorevich Novikov

    2016-03-01

    Full Text Available The main reason of the research is how to use fuzzy search method for information security of Hi Education or some similar purposes. So many sensitive information leaks are through non SUMMARY 149 classified documents legal publishing. That’s why many intelligence services so love to use the «mosaic» information collection method. This article is about how to prevent it.

  13. Geometrical Fuzzy Search Method for the Business Information Security Systems

    Directory of Open Access Journals (Sweden)

    Grigory Grigorievich Novikov

    2014-12-01

    Full Text Available The main reason of the article is how to use one of new fuzzy search method for information security of business or some other purposes. So many sensitive information leaks are through non-classified documents legal publishing. That’s why many intelligence services like to use the “mosaic” information collection method so much: This article is about how to prevent it.

  14. A fuzzy MCDM approach for evaluating school performance based on linguistic information

    Science.gov (United States)

    Musani, Suhaina; Jemain, Abdul Aziz

    2013-11-01

    Decision making is the process of finding the best option among the feasible alternatives. This process should consider a variety of criteria, but this study only focus on academic achievement. The data used is the percentage of candidates who obtained Malaysian Certificate of Education (SPM) in Melaka based on school academic achievement for each subject. 57 secondary schools in Melaka as listed by the Ministry of Education involved in this study. Therefore the school ranking can be done using MCDM (Multi Criteria Decision Making) methods. The objective of this study is to develop a rational method for evaluating school performance based on linguistic information. Since the information or level of academic achievement provided in linguistic manner, there is a possible chance of getting incomplete or uncertain problems. So in order to overcome the situation, the information could be provided as fuzzy numbers. Since fuzzy set represents the uncertainty in human perceptions. In this research, VIKOR (Multi Criteria Optimization and Compromise Solution) has been used as a MCDM tool for the school ranking process in fuzzy environment. Results showed that fuzzy set theory can solve the limitations of using MCDM when there is uncertainty problems exist in the data.

  15. APPLICATION OF FUZZY ANALYTIC HIERARCHY PROCESS TO BUILDING RESEARCH TEAMS

    Directory of Open Access Journals (Sweden)

    Karol DĄBROWSKI

    2016-01-01

    Full Text Available Building teams has a fundamental impact for execution of research and development projects. The teams appointed for the needs of given projects are based on individuals from both inside and outside of the organization. Knowledge is not only a product available on the market but also an intangible resource affecting their internal and external processes. Thus it is vitally important for businesses and scientific research facilities to effectively manage knowledge within project teams. The article presents a proposal to use Fuzzy AHP (Analytic Hierarchy Process and ANFIS (Adaptive Neuro Fuzzy Inference System methods in working groups building for R&D projects on the basis of employees skills.

  16. Application of Fuzzy Analytic Hierarchy Process to Building Research Teams

    Science.gov (United States)

    Dąbrowski, Karol; Skrzypek, Katarzyna

    2016-03-01

    Building teams has a fundamental impact for execution of research and development projects. The teams appointed for the needs of given projects are based on individuals from both inside and outside of the organization. Knowledge is not only a product available on the market but also an intangible resource affecting their internal and external processes. Thus it is vitally important for businesses and scientific research facilities to effectively manage knowledge within project teams. The article presents a proposal to use Fuzzy AHP (Analytic Hierarchy Process) and ANFIS (Adaptive Neuro Fuzzy Inference System) methods in working groups building for R&D projects on the basis of employees skills.

  17. Multiattribute Supplier Selection Using Fuzzy Analytic Hierarchy Process

    Directory of Open Access Journals (Sweden)

    Serhat Aydin

    2010-11-01

    Full Text Available Supplier selection is a multiattribute decision making (MADM problem which contains both qualitative and quantitative factors. Supplier selection has vital importance for most companies. The aim of this paper is to provide an AHP based analytical tool for decision support enabling an effective multicriteria supplier selection process in an air conditioner seller firm under fuzziness. In this article, the Analytic Hierarchy Process (AHP under fuzziness is employed for its permissiveness to use an evaluation scale including linguistic expressions, crisp numerical values, fuzzy numbers and range numerical values. This scale provides a more flexible evaluation compared with the other fuzzy AHP methods. In this study, the modified AHP was used in supplier selection in an air conditioner firm. Three experts evaluated the suppliers according to the proposed model and the most appropriate supplier was selected. The proposed model enables decision makers select the best supplier among supplier firms effectively. We confirm that the modified fuzzy AHP is appropriate for group decision making in supplier selection problems.

  18. A fuzzy art neural network based color image processing and ...

    African Journals Online (AJOL)

    To improve the learning process from the input data, a new learning rule was suggested. In this paper, a new method is proposed to deal with the RGB color image pixels, which enables a Fuzzy ART neural network to process the RGB color images. The application of the algorithm was implemented and tested on a set of ...

  19. Determining e-Portfolio Elements in Learning Process Using Fuzzy Delphi Analysis

    Science.gov (United States)

    Mohamad, Syamsul Nor Azlan; Embi, Mohamad Amin; Nordin, Norazah

    2015-01-01

    The present article introduces the Fuzzy Delphi method results obtained in the study on determining e-Portfolio elements in learning process for art and design context. This method bases on qualified experts that assure the validity of the collected information. In particular, the confirmation of elements is based on experts' opinion and…

  20. An Intelligent Information Retrieval Approach Based on Two Degrees of Uncertainty Fuzzy Ontology

    Directory of Open Access Journals (Sweden)

    Maryam Hourali

    2011-01-01

    Full Text Available In spite of the voluminous studies in the field of intelligent retrieval systems, effective retrieving of information has been remained an important unsolved problem. Implementations of different conceptual knowledge in the information retrieval process such as ontology have been considered as a solution to enhance the quality of results. Furthermore, the conceptual formalism supported by typical ontology may not be sufficient to represent uncertainty information due to the lack of clear-cut boundaries between concepts of the domains. To tackle this type of problems, one possible solution is to insert fuzzy logic into ontology construction process. In this article, a novel approach for fuzzy ontology generation with two uncertainty degrees is proposed. Hence, by implementing linguistic variables, uncertainty level in domain's concepts (Software Maintenance Engineering (SME domain has been modeled, and ontology relations have been modeled by fuzzy theory consequently. Then, we combined these uncertain models and proposed a new ontology with two degrees of uncertainty both in concept expression and relation expression. The generated fuzzy ontology was implemented for expansion of initial user's queries in SME domain. Experimental results showed that the proposed model has better overall retrieval performance comparing to keyword-based or crisp ontology-based retrieval systems.

  1. Applying fuzzy analytic network process in quality function deployment model

    Directory of Open Access Journals (Sweden)

    Mohammad Ali Afsharkazemi

    2012-08-01

    Full Text Available In this paper, we propose an empirical study of QFD implementation when fuzzy numbers are used to handle the uncertainty associated with different components of the proposed model. We implement fuzzy analytical network to find the relative importance of various criteria and using fuzzy numbers we calculate the relative importance of these factors. The proposed model of this paper uses fuzzy matrix and house of quality to study the products development in QFD and also the second phase i.e. part deployment. In most researches, the primary objective is only on CRs to implement the quality function deployment and some other criteria such as production costs, manufacturing costs etc were disregarded. The results of using fuzzy analysis network process based on the QFD model in Daroupat packaging company to develop PVDC show that the most important indexes are being waterproof, resistant pill packages, and production cost. In addition, the PVDC coating is the most important index in terms of company experts’ point of view.

  2. A Fuzzy Semantic Information Retrieval System for Transactional Applications

    OpenAIRE

    A O Ajayi; H A Soriyan; G A Aderounmu

    2009-01-01

    In this paper, we present an information retrieval system based on the concept of fuzzy logic to relate vague and uncertain objects with un-sharp boundaries. The simple but comprehensive user interface of the system permits the entering of uncertain specifications in query forms. The system was modelled and simulated in a Matlab environment; its implementation was carried out using Borland C++ Builder. The result of the performance measure of the system using precision and recall rates is enc...

  3. HOSPITAL SITE SELECTION USING TWO-STAGE FUZZY MULTI-CRITERIA DECISION MAKING PROCESS

    Directory of Open Access Journals (Sweden)

    Ali Soltani

    2011-06-01

    Full Text Available Site selection for sitting of urban activities/facilities is one of the crucial policy-related decisions taken by urban planners and policy makers. The process of site selection is inherently complicated. A careless site imposes exorbitant costs on city budget and damages the environment inevitably. Nowadays, multi-attributes decision making approaches are suggested to use to improve precision of decision making and reduce surplus side effects. Two well-known techniques, analytical hierarchal process and analytical network process are among multi-criteria decision making systems which can easily be consistent with both quantitative and qualitative criteria. These are also developed to be fuzzy analytical hierarchal process and fuzzy analytical network process systems which are capable of accommodating inherent uncertainty and vagueness in multi-criteria decision-making. This paper reports the process and results of a hospital site selection within the Region 5 of Shiraz metropolitan area, Iran using integrated fuzzy analytical network process systems with Geographic Information System (GIS. The weights of the alternatives were calculated using fuzzy analytical network process. Then a sensitivity analysis was conducted to measure the elasticity of a decision in regards to different criteria. This study contributes to planning practice by suggesting a more comprehensive decision making tool for site selection.

  4. HOSPITAL SITE SELECTION USING TWO-STAGE FUZZY MULTI-CRITERIA DECISION MAKING PROCESS

    Directory of Open Access Journals (Sweden)

    Ali Soltani

    2011-01-01

    Full Text Available Site selection for sitting of urban activities/facilities is one of the crucial policy-related decisions taken by urban planners and policy makers. The process of site selection is inherently complicated. A careless site imposes exorbitant costs on city budget and damages the environment inevitably. Nowadays, multi-attributes decision making approaches are suggested to use to improve precision of decision making and reduce surplus side effects. Two well-known techniques, analytical hierarchal process and analytical network process are among multi-criteria decision making systems which can easily be consistent with both quantitative and qualitative criteria. These are also developed to be fuzzy analytical hierarchal process and fuzzy analytical network process systems which are capable of accommodating inherent uncertainty and vagueness in multi-criteria decision-making. This paper reports the process and results of a hospital site selection within the Region 5 of Shiraz metropolitan area, Iran using integrated fuzzy analytical network process systems with Geographic Information System (GIS. The weights of the alternatives were calculated using fuzzy analytical network process. Then a sensitivity analysis was conducted to measure the elasticity of a decision in regards to different criteria. This study contributes to planning practice by suggesting a more comprehensive decision making tool for site selection.

  5. Fuzzy assessment of health information system users' security awareness.

    Science.gov (United States)

    Aydın, Özlem Müge; Chouseinoglou, Oumout

    2013-12-01

    Health information systems (HIS) are a specific area of information systems (IS), where critical patient data is stored and quality health service is only realized with the correct use and efficient dissemination of this data to health workers. Therefore, a balance needs to be established between the levels of security and flow of information on HIS. Instead of implementing higher levels and further mechanisms of control to increase the security of HIS, it is preferable to deal with the arguably weakest link on HIS chain with respect to security: HIS users. In order to provide solutions and approaches for transforming users to the first line of defense in HIS but also to employ capable and appropriate candidates from the pool of newly graduated students, it is important to assess and evaluate the security awareness levels and characteristics of these existing and future users. This study aims to provide a new perspective to understand the phenomenon of security awareness of HIS users with the use of fuzzy analysis, and to assess the present situation of current and future HIS users of a leading medical and educational institution of Turkey, with respect to their security characteristics based on four different security scales. The results of the fuzzy analysis, the guide on how to implement this fuzzy analysis to any health institution and how to read and interpret these results, together with the possible implications of these results to the organization are provided.

  6. Sustainable energy planning decision using the intuitionistic fuzzy analytic hierarchy process: choosing energy technology in Malaysia

    Science.gov (United States)

    Abdullah, Lazim; Najib, Liana

    2016-04-01

    Energy consumption for developing countries is sharply increasing due to the higher economic growth due to industrialisation along with population growth and urbanisation. The increasing demand of energy leads to global energy crisis. Selecting the best energy technology and conservation requires both quantitative and qualitative evaluation criteria. The fuzzy set-based approach is one of the well-known theories to handle fuzziness, uncertainty in decision-making and vagueness of information. This paper proposes a new method of intuitionistic fuzzy analytic hierarchy process (IF-AHP) to deal with the uncertainty in decision-making. The new IF-AHP is applied to establish a preference in the sustainable energy planning decision-making problem. Three decision-makers attached with Malaysian government agencies were interviewed to provide linguistic judgement prior to analysing with the new IF-AHP. Nuclear energy has been decided as the best alternative in energy planning which provides the highest weight among all the seven alternatives.

  7. Fuzzy social choice models explaining the government formation process

    CERN Document Server

    C Casey, Peter; A Goodman, Carly; Pook, Kelly Nelson; N Mordeson, John; J Wierman, Mark; D Clark, Terry

    2014-01-01

    This book explores the extent to which fuzzy set logic can overcome some of the shortcomings of public choice theory, particularly its inability to provide adequate predictive power in empirical studies. Especially in the case of social preferences, public choice theory has failed to produce the set of alternatives from which collective choices are made.  The book presents empirical findings achieved by the authors in their efforts to predict the outcome of government formation processes in European parliamentary and semi-presidential systems.  Using data from the Comparative Manifesto Project (CMP), the authors propose a new approach that reinterprets error in the coding of CMP data as ambiguity in the actual political positions of parties on the policy dimensions being coded. The range of this error establishes parties’ fuzzy preferences. The set of possible outcomes in the process of government formation is then calculated on the basis of both the fuzzy Pareto set and the fuzzy maximal set, and the pre...

  8. Fuzzy Mutual Information Based min-Redundancy and Max-Relevance Heterogeneous Feature Selection

    Directory of Open Access Journals (Sweden)

    Daren Yu

    2011-08-01

    Full Text Available Feature selection is an important preprocessing step in pattern classification and machine learning, and mutual information is widely used to measure relevance between features and decision. However, it is difficult to directly calculate relevance between continuous or fuzzy features using mutual information. In this paper we introduce the fuzzy information entropy and fuzzy mutual information for computing relevance between numerical or fuzzy features and decision. The relationship between fuzzy information entropy and differential entropy is also discussed. Moreover, we combine fuzzy mutual information with qmin-Redundancy-Max-Relevanceq, qMax-Dependencyq and min-Redundancy-Max-Dependencyq algorithms. The performance and stability of the proposed algorithms are tested on benchmark data sets. Experimental results show the proposed algorithms are effective and stable.

  9. Application of fuzzy neural network technologies in management of transport and logistics processes in Arctic

    Science.gov (United States)

    Levchenko, N. G.; Glushkov, S. V.; Sobolevskaya, E. Yu; Orlov, A. P.

    2018-05-01

    The method of modeling the transport and logistics process using fuzzy neural network technologies has been considered. The analysis of the implemented fuzzy neural network model of the information management system of transnational multimodal transportation of the process showed the expediency of applying this method to the management of transport and logistics processes in the Arctic and Subarctic conditions. The modular architecture of this model can be expanded by incorporating additional modules, since the working conditions in the Arctic and the subarctic themselves will present more and more realistic tasks. The architecture allows increasing the information management system, without affecting the system or the method itself. The model has a wide range of application possibilities, including: analysis of the situation and behavior of interacting elements; dynamic monitoring and diagnostics of management processes; simulation of real events and processes; prediction and prevention of critical situations.

  10. A Fuzzy Semantic Information Retrieval System for Transactional Applications

    Directory of Open Access Journals (Sweden)

    A O Ajayi

    2009-09-01

    Full Text Available In this paper, we present an information retrieval system based on the concept of fuzzy logic to relate vague and uncertain objects with un-sharp boundaries. The simple but comprehensive user interface of the system permits the entering of uncertain specifications in query forms. The system was modelled and simulated in a Matlab environment; its implementation was carried out using Borland C++ Builder. The result of the performance measure of the system using precision and recall rates is encouraging. Similarly, the smaller amount of more precise information retrieved by the system will positively impact the response time perceived by the users.

  11. FuzzyFusion: an application architecture for multisource information fusion

    Science.gov (United States)

    Fox, Kevin L.; Henning, Ronda R.

    2009-04-01

    The correlation of information from disparate sources has long been an issue in data fusion research. Traditional data fusion addresses the correlation of information from sources as diverse as single-purpose sensors to all-source multi-media information. Information system vulnerability information is similar in its diversity of sources and content, and in the desire to draw a meaningful conclusion, namely, the security posture of the system under inspection. FuzzyFusionTM, A data fusion model that is being applied to the computer network operations domain is presented. This model has been successfully prototyped in an applied research environment and represents a next generation assurance tool for system and network security.

  12. Image Processing for Binarization Enhancement via Fuzzy Reasoning

    Science.gov (United States)

    Dominguez, Jesus A. (Inventor)

    2009-01-01

    A technique for enhancing a gray-scale image to improve conversions of the image to binary employs fuzzy reasoning. In the technique, pixels in the image are analyzed by comparing the pixel's gray scale value, which is indicative of its relative brightness, to the values of pixels immediately surrounding the selected pixel. The degree to which each pixel in the image differs in value from the values of surrounding pixels is employed as the variable in a fuzzy reasoning-based analysis that determines an appropriate amount by which the selected pixel's value should be adjusted to reduce vagueness and ambiguity in the image and improve retention of information during binarization of the enhanced gray-scale image.

  13. COMPARISION OF FUZZY PERT APPROACHES IN MACHINE PRODUCTION PROCESS

    Directory of Open Access Journals (Sweden)

    İRFAN ERTUĞRUL

    2013-06-01

    Full Text Available In traditional PERT (Program Evaluation and Review Technique activity durations are represented as crisp numbers and assumed that they are drawn from beta distribution. However, in real life the duration of the activities are usually difficult to estimate precisely.  In order to overcome this difficulty, there are studies in the literature that combine fuzzy set theory and PERT method. In this study, two fuzzy PERT approaches proposed by different authors are employed to find the degrees of criticality of each path in the network and comparison of these two methods is also given. Furthermore, by the help of these methods the criticality of the activities in the marble machine production process of a company that manufactures machinery is determined and results are compared.

  14. A Model for the Development of Hospital Beds Using Fuzzy Analytical Hierarchy Process (Fuzzy AHP).

    Science.gov (United States)

    Ravangard, Ramin; Bahadori, Mohammadkarim; Raadabadi, Mehdi; Teymourzadeh, Ehsan; Alimomohammadzadeh, Khalil; Mehrabian, Fardin

    2017-11-01

    This study aimed to identify and prioritize factors affecting the development of military hospital beds and provide a model using fuzzy analytical hierarchy process (Fuzzy AHP). This applied study was conducted in 2016 in Iran using a mixed method. The sample included experts in the field of military health care system. The MAXQDA 10.0 and Expert Choice 10.0 software were used for analyzing the collected data. Geographic situation, demographic status, economic status, health status, health care centers and organizations, financial and human resources, laws and regulations and by-laws, and the military nature of service recipients had effects on the development of military hospital beds. The military nature of service recipients (S=0.249) and economic status (S=0.040) received the highest and lowest priorities, respectively. Providing direct health care services to the military forces in order to maintain their dignity, and according to its effects in the crisis, as well as the necessity for maintaining the security of the armed forces, and the hospital beds per capita based on the existing laws, regulations and bylaws are of utmost importance.

  15. A fuzzy mathematics model for radioactive waste characterization by process knowledge

    International Nuclear Information System (INIS)

    Smith, M.; Stevens, S.; Elam, K.; Vrba, J.

    1994-01-01

    Fuzzy mathematics and fuzzy logic are means for making decisions that can integrate complicated combinations of hard and soft factors and produce mathematically validated results that can be independently verified. In this particular application, several sources of information regarding the waste stream have been compiled, including facility operating records, other waste generated from the facility in the past, laboratory analysis results, and interviews with facility personnel. A fuzzy mathematics model is used to interrelate these various sources of information and arrive at a defensible estimate of the contaminant concentration in the final waste product. The model accounts for the separate process knowledge-based contaminant concentrations by providing a weighted averaging technique to incorporate information from the various sources. Reliability estimates are provided for each of the component pieces of information and combined using the model into an estimate that provides a near-probabilistic value for contaminant concentration. The speadsheet accounts for the estimated uncertainty in the concentration on the basis of open-quotes reliability curves,close quotes which are derived from personal process knowledge as well as limited independent measurements

  16. City Sustainable Development Evaluation Based on Hesitant Multiplicative Fuzzy Information

    Directory of Open Access Journals (Sweden)

    Xiaorong He

    2017-01-01

    Full Text Available Sustainable development evaluation is the basis of city sustainable development research, and effective evaluation is the foundation for guiding the formulation and implementation of sustainable development strategy. In this paper, we provided a new city sustainable development evaluation method called hesitant multiplicative fuzzy TODIM (HMF-TODIM. The main advantage of this method is that it can deal with the subjective preference information of the decision-makers. The comparison study of existing methods and HMF-TODIM is also carried out. Additionally, real case analysis is presented to show the validity and superiority of the proposed method. Research results in this paper can provide useful information for the construction of sustainable cities.

  17. Optimal Selection Method of Process Patents for Technology Transfer Using Fuzzy Linguistic Computing

    Directory of Open Access Journals (Sweden)

    Gangfeng Wang

    2014-01-01

    Full Text Available Under the open innovation paradigm, technology transfer of process patents is one of the most important mechanisms for manufacturing companies to implement process innovation and enhance the competitive edge. To achieve promising technology transfers, we need to evaluate the feasibility of process patents and optimally select the most appropriate patent according to the actual manufacturing situation. Hence, this paper proposes an optimal selection method of process patents using multiple criteria decision-making and 2-tuple fuzzy linguistic computing to avoid information loss during the processes of evaluation integration. An evaluation index system for technology transfer feasibility of process patents is designed initially. Then, fuzzy linguistic computing approach is applied to aggregate the evaluations of criteria weights for each criterion and corresponding subcriteria. Furthermore, performance ratings for subcriteria and fuzzy aggregated ratings of criteria are calculated. Thus, we obtain the overall technology transfer feasibility of patent alternatives. Finally, a case study of aeroengine turbine manufacturing is presented to demonstrate the applicability of the proposed method.

  18. Fuzzy sets on step of planning of experiment for organization and management of construction processes

    Directory of Open Access Journals (Sweden)

    Lapidus Azariy

    2016-01-01

    Full Text Available In this article, problems of mathematical modeling and experiment planning of the organization and management of construction. The authors designated the basic restrictions and the difficulties in this field. Concluded that the planning of research experiment is possible in the information sphere with using of heuristic, graphical, mathematical models, as well as neural networks and genetic algorithms. The authors note the need for use of expert information in the case of the formalization of quality parameters. The article presented an overview of the translation methods of qualitative information into mathematical language. Comparison of methods the qualimetry of USSR scientists, the analytic hierarchy process and fuzzy set theory were performed. The benefits of the latter for interpretation of qualitative parameters were identified. The authors have given many examples of application fuzzy sets for formalization of organizational factors of construction processes. Finally, there conclusion was made about progressiveness and effectiveness of fuzzy set theory to describe the qualitative parameters of organization and management of construction.

  19. Total Quality Management of Information System for Quality Assessment of Pesantren Using Fuzzy-SERVQUAL

    Science.gov (United States)

    Faizah, Arbiati; Syafei, Wahyul Amien; Isnanto, R. Rizal

    2018-02-01

    This research proposed a model combining an approach of Total Quality Management (TQM) and Fuzzy method of Service Quality (SERVQUAL) to asses service quality. TQM implementation was as quality management orienting on customer's satisfaction by involving all stakeholders. SERVQUAL model was used to measure quality service based on five dimensions such as tangible, reliability, responsiveness, assurance, and empathy. Fuzzy set theory was to accommodate subjectivity and ambiguity of quality assessment. Input data consisted of indicator data and quality assessment aspect. Input data was, then, processed to be service quality assessment questionnaires of Pesantren by using Fuzzy method to get service quality score. This process consisted of some steps as follows : inputting dimension and questionnaire data to data base system, filling questionnaire through system, then, system calculated fuzzification, defuzzification, gap of quality expected and received by service receivers, and calculating each dimension rating showing quality refinement priority. Rating of each quality dimension was, then, displayed at dashboard system to enable users to see information. From system having been built, it could be known that tangible dimension had the highest gap, -0.399, thus it needs to be prioritized and gets evaluation and refinement action soon.

  20. Dependent Space and Attribute Reduction on Fuzzy Information System

    Directory of Open Access Journals (Sweden)

    Shu Chang

    2017-01-01

    Full Text Available From equivalence relation RBδ on discourse domain U, we can derive equivalence relation Rδ on the attribute set A. From equivalence relation Rδ on discourse domain A, we can derive a congruence relation on the attribute power set P(A and establish an object dependent space. And then,we discuss the reduction method of fuzzy information system on object dependent space. At last ,the example in this paper demonstrates the feasibility and effectiveness of the reduction method based on the congruence relation Tδ providing an insight into the link between equivalence relation and congruence relation of dependent spaces in the rough set. In this way, the paper can provide powerful theoritical support to the combined using of reduction method, so it is of certain practical value.

  1. NEURO-FUZZY MODELLING OF BLENDING PROCESS IN CEMENT PLANT

    Directory of Open Access Journals (Sweden)

    Dauda Olarotimi Araromi

    2015-11-01

    Full Text Available The profitability of a cement plant depends largely on the efficient operation of the blending stage, therefore, there is a need to control the process at the blending stage in order to maintain the chemical composition of the raw mix near or at the desired value with minimum variance despite variation in the raw material composition. In this work, neuro-fuzzy model is developed for a dynamic behaviour of the system to predict the total carbonate content in the raw mix at different clay feed rates. The data used for parameter estimation and model validation was obtained from one of the cement plants in Nigeria. The data was pre-processed to remove outliers and filtered using smoothening technique in order to reveal its dynamic nature. Autoregressive exogenous (ARX model was developed for comparison purpose. ARX model gave high root mean square error (RMSE of 5.408 and 4.0199 for training and validation respectively. Poor fit resulting from ARX model is an indication of nonlinear nature of the process. However, both visual and statistical analyses on neuro-fuzzy (ANFIS model gave a far better result. RMSE of training and validation are 0.28167 and 0.7436 respectively, and the sum of square error (SSE and R-square are 39.6692 and 0.9969 respectively. All these are an indication of good performance of ANFIS model. This model can be used for control design of the process.

  2. 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

  3. Bayesian image processing of data from fuzzy pattern sources

    International Nuclear Information System (INIS)

    Liang, Z.; Hart, H.

    1986-01-01

    In some radioisotopic organ image applications, a priori or supplementary source information may exist and can be characterized in terms of probability density functions P (phi) of the source elements {phi/sub j/} = phi (where phi/sub j/ (j = 1,2,..α) is the estimated average photon emission in voxel j per unit time at t = 0). For example, in cardiac imaging studies it is possible to evaluate the radioisotope concentration of the blood filling the cardiac chambers independently as a function of time by peripheral measurement. The blood concentration information in effect serves to limit amplitude uncertainty to the chamber boundary voxels and thus reduces the extent of amplitude ambiguities in the overall cardiac imaging reconstruction. The a priori or supplementary information may more generally be spatial, amplitude-dependent probability distributions P(phi), fuzzy patterns superimposed upon a background

  4. Road Sign Recognition with Fuzzy Adaptive Pre-Processing Models

    Science.gov (United States)

    Lin, Chien-Chuan; Wang, Ming-Shi

    2012-01-01

    A road sign recognition system based on adaptive image pre-processing models using two fuzzy inference schemes has been proposed. The first fuzzy inference scheme is to check the changes of the light illumination and rich red color of a frame image by the checking areas. The other is to check the variance of vehicle's speed and angle of steering wheel to select an adaptive size and position of the detection area. The Adaboost classifier was employed to detect the road sign candidates from an image and the support vector machine technique was employed to recognize the content of the road sign candidates. The prohibitory and warning road traffic signs are the processing targets in this research. The detection rate in the detection phase is 97.42%. In the recognition phase, the recognition rate is 93.04%. The total accuracy rate of the system is 92.47%. For video sequences, the best accuracy rate is 90.54%, and the average accuracy rate is 80.17%. The average computing time is 51.86 milliseconds per frame. The proposed system can not only overcome low illumination and rich red color around the road sign problems but also offer high detection rates and high computing performance. PMID:22778650

  5. 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.

  6. 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.

  7. A Fuzzy analytical hierarchy process approach in irrigation networks maintenance

    Science.gov (United States)

    Riza Permana, Angga; Rintis Hadiani, Rr.; Syafi'i

    2017-11-01

    Ponorogo Regency has 440 Irrigation Area with a total area of 17,950 Ha. Due to the limited budget and lack of maintenance cause decreased function on the irrigation. The aim of this study is to make an appropriate system to determine the indices weighted of the rank prioritization criteria for irrigation network maintenance using a fuzzy-based methodology. The criteria that are used such as the physical condition of irrigation networks, area of service, estimated maintenance cost, and efficiency of irrigation water distribution. 26 experts in the field of water resources in the Dinas Pekerjaan Umum were asked to fill out the questionnaire, and the result will be used as a benchmark to determine the rank of irrigation network maintenance priority. The results demonstrate that the physical condition of irrigation networks criterion (W1) = 0,279 has the greatest impact on the assessment process. The area of service (W2) = 0,270, efficiency of irrigation water distribution (W4) = 0,249, and estimated maintenance cost (W3) = 0,202 criteria rank next in effectiveness, respectively. The proposed methodology deals with uncertainty and vague data using triangular fuzzy numbers, and, moreover, it provides a comprehensive decision-making technique to assess maintenance priority on irrigation network.

  8. How Uncertain Information on Service Capacity Influences the Intermodal Routing Decision: A Fuzzy Programming Perspective

    Directory of Open Access Journals (Sweden)

    Yan Sun

    2018-01-01

    Full Text Available Capacity uncertainty is a common issue in the transportation planning field. However, few studies discuss the intermodal routing problem with service capacity uncertainty. Based on our previous study on the intermodal routing under deterministic capacity consideration, we systematically explore how service capacity uncertainty influences the intermodal routing decision. First of all, we adopt trapezoidal fuzzy numbers to describe the uncertain information of the service capacity, and further transform the deterministic capacity constraint into a fuzzy chance constraint based on fuzzy credibility measure. We then integrate such fuzzy chance constraint into the mixed-integer linear programming (MILP model proposed in our previous study to develop a fuzzy chance-constrained programming model. To enable the improved model to be effectively programmed in the standard mathematical programming software and solved by exact solution algorithms, a crisp equivalent linear reformulation of the fuzzy chance constraint is generated. Finally, we modify the empirical case presented in our previous study by replacing the deterministic service capacities with trapezoidal fuzzy ones. Using the modified empirical case, we utilize sensitivity analysis and fuzzy simulation to analyze the influence of service capacity uncertainty on the intermodal routing decision, and summarize some interesting insights that are helpful for decision makers.

  9. A fuzzy model for processing and monitoring vital signs in ICU patients

    Directory of Open Access Journals (Sweden)

    Valentim Ricardo AM

    2011-08-01

    Full Text Available Abstract Background The area of the hospital automation has been the subject of much research, addressing relevant issues which can be automated, such as: management and control (electronic medical records, scheduling appointments, hospitalization, among others; communication (tracking patients, staff and materials, development of medical, hospital and laboratory equipment; monitoring (patients, staff and materials; and aid to medical diagnosis (according to each speciality. Methods In this context, this paper presents a Fuzzy model for helping medical diagnosis of Intensive Care Unit (ICU patients and their vital signs monitored through a multiparameter heart screen. Intelligent systems techniques were used in the data acquisition and processing (sorting, transforming, among others it into useful information, conducting pre-diagnosis and providing, when necessary, alert signs to the medical staff. Conclusions The use of fuzzy logic turned to the medical area can be very useful if seen as a tool to assist specialists in this area. This paper presented a fuzzy model able to monitor and classify the condition of the vital signs of hospitalized patients, sending alerts according to the pre-diagnosis done helping the medical diagnosis.

  10. Entropy Based Feature Selection for Fuzzy Set-Valued Information Systems

    Science.gov (United States)

    Ahmed, Waseem; Sufyan Beg, M. M.; Ahmad, Tanvir

    2018-06-01

    In Set-valued Information Systems (SIS), several objects contain more than one value for some attributes. Tolerance relation used for handling SIS sometimes leads to loss of certain information. To surmount this problem, fuzzy rough model was introduced. However, in some cases, SIS may contain some real or continuous set-values. Therefore, the existing fuzzy rough model for handling Information system with fuzzy set-values needs some changes. In this paper, Fuzzy Set-valued Information System (FSIS) is proposed and fuzzy similarity relation for FSIS is defined. Yager's relative conditional entropy was studied to find the significance measure of a candidate attribute of FSIS. Later, using these significance values, three greedy forward algorithms are discussed for finding the reduct and relative reduct for the proposed FSIS. An experiment was conducted on a sample population of the real dataset and a comparison of classification accuracies of the proposed FSIS with the existing SIS and single-valued Fuzzy Information Systems was made, which demonstrated the effectiveness of proposed FSIS.

  11. Supervisory System and Multivariable Control Applying Weighted Fuzzy-PID Logic in an Alcoholic Fermentation Process

    Directory of Open Access Journals (Sweden)

    Márcio Mendonça

    2015-10-01

    Full Text Available In this work, it is analyzed a multivariate system control of an alcoholic fermentation process with no minimum phase. The control is made with PID classic controllers associated with a supervisory system based on Fuzzy Systems. The Fuzzy system, a priori, send set-points to PID controllers, but also adds protection functions, such as if the biomass valued is at zero or very close. The Fuzzy controller changes the campaign to prevent or mitigate the paralyzation of the process. Three control architectures based on Fuzzy Control Systems are presented and compared in performance with classic control in different campaigns. The third architecture, in particular, adds an adaptive function. A brief summary of Fuzzy theory and correlated works will be presented. And, finally simulations results, conclusions and future works end the article.

  12. Hybrid Multicriteria Group Decision Making Method for Information System Project Selection Based on Intuitionistic Fuzzy Theory

    Directory of Open Access Journals (Sweden)

    Jian Guo

    2013-01-01

    Full Text Available Information system (IS project selection is of critical importance to every organization in dynamic competing environment. The aim of this paper is to develop a hybrid multicriteria group decision making approach based on intuitionistic fuzzy theory for IS project selection. The decision makers’ assessment information can be expressed in the form of real numbers, interval-valued numbers, linguistic variables, and intuitionistic fuzzy numbers (IFNs. All these evaluation pieces of information can be transformed to the form of IFNs. Intuitionistic fuzzy weighted averaging (IFWA operator is utilized to aggregate individual opinions of decision makers into a group opinion. Intuitionistic fuzzy entropy is used to obtain the entropy weights of the criteria. TOPSIS method combined with intuitionistic fuzzy set is proposed to select appropriate IS project in group decision making environment. Finally, a numerical example for information system projects selection is given to illustrate application of hybrid multi-criteria group decision making (MCGDM method based on intuitionistic fuzzy theory and TOPSIS method.

  13. Logika Fuzzy untuk Audit Sistem Informasi

    Directory of Open Access Journals (Sweden)

    Hari Setiabudi Husni

    2013-06-01

    Full Text Available The aim of this research is to study and introduce fuzzy logic into audit information system. Fuzzy logic is already adopted in other field of study. It helps decision process that incorporates subjective information and transforms it to scientific objective information which is more accepted. This research implements simulation scenario to see how fuzzy logic concept should be used in audit information process. The result shows that there is a possible concept of fuzzy logic that can be used for helping auditor in making objective decision in audit information system process. More researches needed to further explore the fuzzy logic concept such as creating the system of fuzzy logic and build application that can be used for daily information system audit process

  14. Combining geographic information system, multicriteria evaluation techniques and fuzzy logic in siting MSW landfills

    Science.gov (United States)

    Gemitzi, Alexandra; Tsihrintzis, Vassilios A.; Voudrias, Evangelos; Petalas, Christos; Stravodimos, George

    2007-01-01

    This study presents a methodology for siting municipal solid waste landfills, coupling geographic information systems (GIS), fuzzy logic, and multicriteria evaluation techniques. Both exclusionary and non-exclusionary criteria are used. Factors, i.e., non-exclusionary criteria, are divided in two distinct groups which do not have the same level of trade off. The first group comprises factors related to the physical environment, which cannot be expressed in terms of monetary cost and, therefore, they do not easily trade off. The second group includes those factors related to human activities, i.e., socioeconomic factors, which can be expressed as financial cost, thus showing a high level of trade off. GIS are used for geographic data acquisition and processing. The analytical hierarchy process (AHP) is the multicriteria evaluation technique used, enhanced with fuzzy factor standardization. Besides assigning weights to factors through the AHP, control over the level of risk and trade off in the siting process is achieved through a second set of weights, i.e., order weights, applied to factors in each factor group, on a pixel-by-pixel basis, thus taking into account the local site characteristics. The method has been applied to Evros prefecture (NE Greece), an area of approximately 4,000 km2. The siting methodology results in two intermediate suitability maps, one related to environmental and the other to socioeconomic criteria. Combination of the two intermediate maps results in the final composite suitability map for landfill siting.

  15. Fuzzy Verification of Lower Dimensional Information in a Numerical Simulation of Sea Ice

    Science.gov (United States)

    Sulsky, D.; Levy, G.

    2010-12-01

    Ideally, a verification and validation scheme should be able to evaluate and incorporate lower dimensional features (e.g., discontinuities) contained within a bulk simulation even when not directly observed or represented by model variables. Nonetheless, lower dimensional features are often ignored. Conversely, models that resolve such features and the associated physics well, yet imprecisely are penalized by traditional validation schemes. This can lead to (perceived or real) poor model performance and predictability and can become deleterious in model improvements when observations are sparse, fuzzy, or irregular. We present novel algorithms and a general framework for using information from available satellite data through fuzzy verification that efficiently and effectively remedy the known problems mentioned above. As a proof of concept, we use a sea-ice model with remotely sensed observations of leads in a one-step initialization cycle. Using the new scheme in a sixteen day simulation experiment introduces model skill (against persistence) several days earlier than in the control run, improves the overall model skill and delays its drop off at later stages of the simulation. Although sea-ice models are currently a weak link in climate models, the appropriate choice of data to use, and the fuzzy verification and evaluation of a system’s skill in reproducing lower dimensional features are important beyond the initial application to sea ice. Our strategy and framework for fuzzy verification, selective use of information, and feature extraction could be extended globally and to other disciplines. It can be incorporated in and complement existing verification and validation schemes, increasing their computational efficiency and the information they use. It can be used for model development and improvements, upscaling/downscaling models, and for modeling processes not directly represented by model variables or direct observations. Finally, if successful, it can

  16. A Novel Fuzzy Algorithm to Introduce New Variables in the Drug Supply Decision-Making Process in Medicine

    Directory of Open Access Journals (Sweden)

    Jose M. Gonzalez-Cava

    2018-01-01

    Full Text Available One of the main challenges in medicine is to guarantee an appropriate drug supply according to the real needs of patients. Closed-loop strategies have been widely used to develop automatic solutions based on feedback variables. However, when the variable of interest cannot be directly measured or there is a lack of knowledge behind the process, it turns into a difficult issue to solve. In this research, a novel algorithm to approach this problem is presented. The main objective of this study is to provide a new general algorithm capable of determining the influence of a certain clinical variable in the decision making process for drug supply and then defining an automatic system able to guide the process considering this information. Thus, this new technique will provide a way to validate a given physiological signal as a feedback variable for drug titration. In addition, the result of the algorithm in terms of fuzzy rules and membership functions will define a fuzzy-based decision system for the drug delivery process. The method proposed is based on a Fuzzy Inference System whose structure is obtained through a decision tree algorithm. A four-step methodology is then developed: data collection, preprocessing, Fuzzy Inference System generation, and the validation of results. To test this methodology, the analgesia control scenario was analysed. Specifically, the viability of the Analgesia Nociception Index (ANI as a guiding variable for the analgesic process during surgical interventions was studied. Real data was obtained from fifteen patients undergoing cholecystectomy surgery.

  17. 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.).

  18. A Study on the Application of Fuzzy Information Seeded Region Growing in Brain MRI Tissue Segmentation

    Directory of Open Access Journals (Sweden)

    Chuin-Mu Wang

    2014-01-01

    Full Text Available After long-term clinical trials, MRI has been proven to be used in humans harmlessly, and it is popularly used in medical diagnosis. Although MR is highly sensitive, it provides abundant organization information. Therefore, how to transform the multi-spectral images which is easier to be used for doctor’s clinical diagnosis. In this thesis, the fuzzy bidirectional edge detection method is used to solve conventional SRG problem of growing order in the initial seed stages. In order to overcome the problems of the different regions, although it is the same Euclidean distance for region growing and merging process stages, we present the peak detection method to improve them. The standard deviation target generation process (SDTGP is applied to guarantee the regions merging process does not cause over- or undersegmentation. Experimental results reveal that FISRG segments a multispectral MR image much more effectively than FAST and K-means.

  19. Some applications of fuzzy sets and the analytical hierarchy process to decision making

    OpenAIRE

    Castro, Alberto Rosas

    1984-01-01

    Approved for public release; distribution unlimited This thesis examines the use of fuzzy set theory and the analytic hierarchy process in decision making. It begins by reviewing the insight of psychologists, social scientists and computer scientists to the decision making process. The Operations Research- Systems Analysis approach is discussed followed by a presentation of the basis of fuzzy set theory and the analytic hierarchy process. Two applications of these meth...

  20. Improved hybridization of Fuzzy Analytic Hierarchy Process (FAHP) algorithm with Fuzzy Multiple Attribute Decision Making - Simple Additive Weighting (FMADM-SAW)

    Science.gov (United States)

    Zaiwani, B. E.; Zarlis, M.; Efendi, S.

    2018-03-01

    In this research, the improvement of hybridization algorithm of Fuzzy Analytic Hierarchy Process (FAHP) with Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) in selecting the best bank chief inspector based on several qualitative and quantitative criteria with various priorities. To improve the performance of the above research, FAHP algorithm hybridization with Fuzzy Multiple Attribute Decision Making - Simple Additive Weighting (FMADM-SAW) algorithm was adopted, which applied FAHP algorithm to the weighting process and SAW for the ranking process to determine the promotion of employee at a government institution. The result of improvement of the average value of Efficiency Rate (ER) is 85.24%, which means that this research has succeeded in improving the previous research that is equal to 77.82%. Keywords: Ranking and Selection, Fuzzy AHP, Fuzzy TOPSIS, FMADM-SAW.

  1. Fuzzy-trace theory: dual processes in memory, reasoning, and cognitive neuroscience.

    Science.gov (United States)

    Brainerd, C J; Reyna, V F

    2001-01-01

    Fuzzy-trace theory has evolved in response to counterintuitive data on how memory development influences the development of reasoning. The two traditional perspectives on memory-reasoning relations--the necessity and constructivist hypotheses--stipulate that the accuracy of children's memory for problem information and the accuracy of their reasoning are closely intertwined, albeit for different reasons. However, contrary to necessity, correlational and experimental dissociations have been found between children's memory for problem information that is determinative in solving certain problems and their solutions of those problems. In these same tasks, age changes in memory for problem information appear to be dissociated from age changes in reasoning. Contrary to constructivism, correlational and experimental dissociations also have been found between children's performance on memory tests for actual experience and memory tests for the meaning of experience. As in memory-reasoning studies, age changes in one type of memory performance do not seem to be closely connected to age changes in the other type of performance. Subsequent experiments have led to dual-process accounts in both the memory and reasoning spheres. The account of memory development features four other principles: parallel verbatim-gist storage, dissociated verbatim-gist retrieval, memorial bases of conscious recollection, and identity/similarity processes. The account of the development of reasoning features three principles: gist extraction, fuzzy-to-verbatim continua, and fuzzy-processing preferences. The fuzzy-processing preference is a particularly important notion because it implies that gist-based intuitive reasoning often suffices to deliver "logical" solutions and that such reasoning confers multiple cognitive advantages that enhance accuracy. The explanation of memory-reasoning dissociations in cognitive development then falls out of fuzzy-trace theory's dual-process models of memory and

  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. HYBRID SYSTEM BASED FUZZY-PID CONTROL SCHEMES FOR UNPREDICTABLE PROCESS

    Directory of Open Access Journals (Sweden)

    M.K. Tan

    2011-07-01

    Full Text Available In general, the primary aim of polymerization industry is to enhance the process operation in order to obtain high quality and purity product. However, a sudden and large amount of heat will be released rapidly during the mixing process of two reactants, i.e. phenol and formalin due to its exothermic behavior. The unpredictable heat will cause deviation of process temperature and hence affect the quality of the product. Therefore, it is vital to control the process temperature during the polymerization. In the modern industry, fuzzy logic is commonly used to auto-tune PID controller to control the process temperature. However, this method needs an experienced operator to fine tune the fuzzy membership function and universe of discourse via trial and error approach. Hence, the setting of fuzzy inference system might not be accurate due to the human errors. Besides that, control of the process can be challenging due to the rapid changes in the plant parameters which will increase the process complexity. This paper proposes an optimization scheme using hybrid of Q-learning (QL and genetic algorithm (GA to optimize the fuzzy membership function in order to allow the conventional fuzzy-PID controller to control the process temperature more effectively. The performances of the proposed optimization scheme are compared with the existing fuzzy-PID scheme. The results show that the proposed optimization scheme is able to control the process temperature more effectively even if disturbance is introduced.

  4. A GA-P algorithm to automatically formulate extended Boolean queries for a fuzzy information retrieval system

    OpenAIRE

    Cordón García, Oscar; Moya Anegón, Félix de; Zarco Fernández, Carmen

    2000-01-01

    [ES] Although the fuzzy retrieval model constitutes a powerful extension of the boolean one, being able to deal with the imprecision and subjectivity existing in the Information Retrieval process, users are not usually able to express their query requirements in the form of an extended boolean query including weights. To solve this problem, different tools to assist the user in the query formulation have been proposed. In this paper, the genetic algorithm-programming technique is considered t...

  5. Application of fuzzy fault tree analysis based on modified fuzzy AHP and fuzzy TOPSIS for fire and explosion in the process industry.

    Science.gov (United States)

    Yazdi, Mohammad; Korhan, Orhan; Daneshvar, Sahand

    2018-05-09

    This study aimed at establishing fault tree analysis (FTA) using expert opinion to compute the probability of an event. To find the probability of the top event (TE), all probabilities of the basic events (BEs) should be available when the FTA is drawn. In this case, employing expert judgment can be used as an alternative to failure data in an awkward situation. The fuzzy analytical hierarchy process as a standard technique is used to give a specific weight to each expert, and fuzzy set theory is engaged for aggregating expert opinion. In this regard, the probability of BEs will be computed and, consequently, the probability of the TE obtained using Boolean algebra. Additionally, to reduce the probability of the TE in terms of three parameters (safety consequences, cost and benefit), the importance measurement technique and modified TOPSIS was employed. The effectiveness of the proposed approach is demonstrated with a real-life case study.

  6. 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.

  7. Supplier Selection for Food Industry: A Combination of Taguchi Loss Function and Fuzzy Analytical Hierarchy Process

    OpenAIRE

    Renna Magdalena

    2012-01-01

    Supplier selection is an important part of supply chain management process by which firms identify, evaluate, and establish contracts with suppliers. Deciding the right supplier can be a complex task. As such, various criteria must be taken into account to choose the best supplier. This study focused on the supply in the packaging division of a food industry in Denpasar-Bali. A combination of Taguchi Loss Function and fuzzy-AHP (Analytical Hierarchy Process Fuzzy Linear Programming) was used ...

  8. Design issues of a reinforcement-based self-learning fuzzy controller for petrochemical process control

    Science.gov (United States)

    Yen, John; Wang, Haojin; Daugherity, Walter C.

    1992-01-01

    Fuzzy logic controllers have some often-cited advantages over conventional techniques such as PID control, including easier implementation, accommodation to natural language, and the ability to cover a wider range of operating conditions. One major obstacle that hinders the broader application of fuzzy logic controllers is the lack of a systematic way to develop and modify their rules; as a result the creation and modification of fuzzy rules often depends on trial and error or pure experimentation. One of the proposed approaches to address this issue is a self-learning fuzzy logic controller (SFLC) that uses reinforcement learning techniques to learn the desirability of states and to adjust the consequent part of its fuzzy control rules accordingly. Due to the different dynamics of the controlled processes, the performance of a self-learning fuzzy controller is highly contingent on its design. The design issue has not received sufficient attention. The issues related to the design of a SFLC for application to a petrochemical process are discussed, and its performance is compared with that of a PID and a self-tuning fuzzy logic controller.

  9. Study of Research and Development Processes through Fuzzy Super FRM Model and Optimization Solutions

    Directory of Open Access Journals (Sweden)

    Flavius Aurelian Sârbu

    2015-01-01

    Full Text Available The aim of this study is to measure resources for R&D (research and development at the regional level in Romania and also obtain primary data that will be important in making the right decisions to increase competitiveness and development based on an economic knowledge. As our motivation, we would like to emphasize that by the use of Super Fuzzy FRM model we want to determine the state of R&D processes at regional level using a mean different from the statistical survey, while by the two optimization methods we mean to provide optimization solutions for the R&D actions of the enterprises. Therefore to fulfill the above mentioned aim in this application-oriented paper we decided to use a questionnaire and for the interpretation of the results the Super Fuzzy FRM model, representing the main novelty of our paper, as this theory provides a formalism based on matrix calculus, which allows processing of large volumes of information and also delivers results difficult or impossible to see, through statistical processing. Furthermore another novelty of the paper represents the optimization solutions submitted in this work, given for the situation when the sales price is variable, and the quantity sold is constant in time and for the reverse situation.

  10. Using fuzzy fractal features of digital images for the material surface analisys

    Science.gov (United States)

    Privezentsev, D. G.; Zhiznyakov, A. L.; Astafiev, A. V.; Pugin, E. V.

    2018-01-01

    Edge detection is an important task in image processing. There are a lot of approaches in this area: Sobel, Canny operators and others. One of the perspective techniques in image processing is the use of fuzzy logic and fuzzy sets theory. They allow us to increase processing quality by representing information in its fuzzy form. Most of the existing fuzzy image processing methods switch to fuzzy sets on very late stages, so this leads to some useful information loss. In this paper, a novel method of edge detection based on fuzzy image representation and fuzzy pixels is proposed. With this approach, we convert the image to fuzzy form on the first step. Different approaches to this conversion are described. Several membership functions for fuzzy pixel description and requirements for their form and view are given. A novel approach to edge detection based on Sobel operator and fuzzy image representation is proposed. Experimental testing of developed method was performed on remote sensing images.

  11. Supercritical boiler material selection using fuzzy analytic network process

    Directory of Open Access Journals (Sweden)

    Saikat Ranjan Maity

    2012-08-01

    Full Text Available The recent development of world is being adversely affected by the scarcity of power and energy. To survive in the next generation, it is thus necessary to explore the non-conventional energy sources and efficiently consume the available sources. For efficient exploitation of the existing energy sources, a great scope lies in the use of Rankin cycle-based thermal power plants. Today, the gross efficiency of Rankin cycle-based thermal power plants is less than 28% which has been increased up to 40% with reheating and regenerative cycles. But, it can be further improved up to 47% by using supercritical power plant technology. Supercritical power plants use supercritical boilers which are able to withstand a very high temperature (650-720˚C and pressure (22.1 MPa while producing superheated steam. The thermal efficiency of a supercritical boiler greatly depends on the material of its different components. The supercritical boiler material should possess high creep rupture strength, high thermal conductivity, low thermal expansion, high specific heat and very high temperature withstandability. This paper considers a list of seven supercritical boiler materials whose performance is evaluated based on seven pivotal criteria. Given the intricacy and difficulty of this supercritical boiler material selection problem having interactions and interdependencies between different criteria, this paper applies fuzzy analytic network process to select the most appropriate material for a supercritical boiler. Rene 41 is the best supercritical boiler material, whereas, Haynes 230 is the worst preferred choice.

  12. A method of groundwater quality assessment based on fuzzy network-CANFIS and geographic information system (GIS)

    Science.gov (United States)

    Gholami, V.; Khaleghi, M. R.; Sebghati, M.

    2017-11-01

    The process of water quality testing is money/time-consuming, quite important and difficult stage for routine measurements. Therefore, use of models has become commonplace in simulating water quality. In this study, the coactive neuro-fuzzy inference system (CANFIS) was used to simulate groundwater quality. Further, geographic information system (GIS) was used as the pre-processor and post-processor tool to demonstrate spatial variation of groundwater quality. All important factors were quantified and groundwater quality index (GWQI) was developed. The proposed model was trained and validated by taking a case study of Mazandaran Plain located in northern part of Iran. The factors affecting groundwater quality were the input variables for the simulation, whereas GWQI index was the output. The developed model was validated to simulate groundwater quality. Network validation was performed via comparison between the estimated and actual GWQI values. In GIS, the study area was separated to raster format in the pixel dimensions of 1 km and also by incorporation of input data layers of the Fuzzy Network-CANFIS model; the geo-referenced layers of the effective factors in groundwater quality were earned. Therefore, numeric values of each pixel with geographical coordinates were entered to the Fuzzy Network-CANFIS model and thus simulation of groundwater quality was accessed in the study area. Finally, the simulated GWQI indices using the Fuzzy Network-CANFIS model were entered into GIS, and hence groundwater quality map (raster layer) based on the results of the network simulation was earned. The study's results confirm the high efficiency of incorporation of neuro-fuzzy techniques and GIS. It is also worth noting that the general quality of the groundwater in the most studied plain is fairly low.

  13. Search and selection hotel system in Surabaya based on geographic information system (GIS) with fuzzy logic

    Science.gov (United States)

    Purbandini, Taufik

    2016-03-01

    Surabaya is a metropolitan city in Indonesia. When the visitor has an interest in Surabaya for several days, then the visitor was looking for lodging that is closest to the interests of making it more efficient and practical. It was not a waste of time for the businessman because of congestion and so we need full information about the hotel as an inn during a stay in Surabaya began name, address of the hotel, the hotel's website, the distance from the hotel to the destination until the display of the map along the route with the help of Google Maps. This system was designed using fuzzy logic which aims to assist the user in making decisions. Design of hotel search and selection system was done through four stages. The first phase was the collection of data and as the factors that influence the decision-making along with the limit values of these factors. Factors that influence covers a distance of the hotel, the price of hotel rooms, and hotel reviews. The second stage was the processing of data and information by creating membership functions. The third stage was the analysis of systems with fuzzy logic. The steps were performed in systems analysis, namely fuzzification, inference using Mamdani, and defuzzification. The last stage was the design and construction of the system. Designing the system using use case diagrams and activity diagram to describe any process that occurs. Development system includes system implementation and evaluation systems. Implementation of mobile with Android-based system so that these applications were user friendly.

  14. A high performance, ad-hoc, fuzzy query processing system for relational databases

    Science.gov (United States)

    Mansfield, William H., Jr.; Fleischman, Robert M.

    1992-01-01

    Database queries involving imprecise or fuzzy predicates are currently an evolving area of academic and industrial research. Such queries place severe stress on the indexing and I/O subsystems of conventional database environments since they involve the search of large numbers of records. The Datacycle architecture and research prototype is a database environment that uses filtering technology to perform an efficient, exhaustive search of an entire database. It has recently been modified to include fuzzy predicates in its query processing. The approach obviates the need for complex index structures, provides unlimited query throughput, permits the use of ad-hoc fuzzy membership functions, and provides a deterministic response time largely independent of query complexity and load. This paper describes the Datacycle prototype implementation of fuzzy queries and some recent performance results.

  15. Selecting the best rayon in customer’s perspective using fuzzy analytic hierarchy process

    Science.gov (United States)

    Sonjaya, E. G.; Paulus, E.; Hidayat, A.

    2018-03-01

    Annually, the best Rayon selection is conducted by the assessment team of PT.PLN (Persero) Cirebon with the goal to increase the spirit of company members in providing an improved service for customers. However, there is a problem in multiple criteria decision making in this case, which is the importance intensity of each criterion in the selection are often assessed subjectively. To solve this problem, Fuzzy Analytical Hierarchy Process are used to cover AHP scale deficiency in the form of ‘crisp’ numbers. So, it should be considered to use Fuzzy logic approach to handle uncertainty. Fuzzy approach, especially triangular fuzzy number towards AHP scale, are expected to minimize the handling of subjective input, which then will make a more objective result. Thus, this research was conducted to help the management or assessment team in the selection of the best Rayon with a more objective selection in according to the company criteria.

  16. Modeling of Activated Sludge Process Using Sequential Adaptive Neuro-fuzzy Inference System

    Directory of Open Access Journals (Sweden)

    Mahsa Vajedi

    2014-10-01

    Full Text Available In this study, an adaptive neuro-fuzzy inference system (ANFIS has been applied to model activated sludge wastewater treatment process of Mobin petrochemical company. The correlation coefficients between the input variables and the output variable were calculated to determine the input with the highest influence on the output (the quality of the outlet flow in order to compare three neuro-fuzzy structures with different number of parameters. The predictions of the neuro-fuzzy models were compared with those of multilayer artificial neural network models with similar structure. The comparison indicated that both methods resulted in flexible, robust and effective models for the activated sludge system. Moreover, the root mean square of the error for neuro-fuzzy and neural network models were 5.14 and 6.59, respectively, which means the former is the superior method.

  17. Intelligent Technique for Signal Processing to Identify the Brain Disorder for Epilepsy Captures Using Fuzzy Systems

    Directory of Open Access Journals (Sweden)

    Gurumurthy Sasikumar

    2016-01-01

    Full Text Available The new direction of understand the signal that is created from the brain organization is one of the main chores in the brain signal processing. Amid all the neurological disorders the human brain epilepsy is measured as one of the extreme prevalent and then programmed artificial intelligence detection technique is an essential due to the crooked and unpredictable nature of happening of epileptic seizures. We proposed an Improved Fuzzy firefly algorithm, which would enhance the classification of the brain signal efficiently with minimum iteration. An important bunching technique created on fuzzy logic is the Fuzzy C means. Together in the feature domain with the spatial domain the features gained after multichannel EEG signals remained combined by means of fuzzy algorithms. And for better precision segmentation process the firefly algorithm is applied to optimize the Fuzzy C-means membership function. Simultaneously for the efficient clustering method the convergence criteria are set. On the whole the proposed technique yields more accurate results and that gives an edge over other techniques. This proposed algorithm result compared with other algorithms like fuzzy c means algorithm and PSO algorithm.

  18. Classification and Quality Evaluation of Tobacco Leaves Based on Image Processing and Fuzzy Comprehensive Evaluation

    Science.gov (United States)

    Zhang, Fan; Zhang, Xinhong

    2011-01-01

    Most of classification, quality evaluation or grading of the flue-cured tobacco leaves are manually operated, which relies on the judgmental experience of experts, and inevitably limited by personal, physical and environmental factors. The classification and the quality evaluation are therefore subjective and experientially based. In this paper, an automatic classification method of tobacco leaves based on the digital image processing and the fuzzy sets theory is presented. A grading system based on image processing techniques was developed for automatically inspecting and grading flue-cured tobacco leaves. This system uses machine vision for the extraction and analysis of color, size, shape and surface texture. Fuzzy comprehensive evaluation provides a high level of confidence in decision making based on the fuzzy logic. The neural network is used to estimate and forecast the membership function of the features of tobacco leaves in the fuzzy sets. The experimental results of the two-level fuzzy comprehensive evaluation (FCE) show that the accuracy rate of classification is about 94% for the trained tobacco leaves, and the accuracy rate of the non-trained tobacco leaves is about 72%. We believe that the fuzzy comprehensive evaluation is a viable way for the automatic classification and quality evaluation of the tobacco leaves. PMID:22163744

  19. Management of Uncertainty by Statistical Process Control and a Genetic Tuned Fuzzy System

    Directory of Open Access Journals (Sweden)

    Stephan Birle

    2016-01-01

    Full Text Available In food industry, bioprocesses like fermentation often are a crucial part of the manufacturing process and decisive for the final product quality. In general, they are characterized by highly nonlinear dynamics and uncertainties that make it difficult to control these processes by the use of traditional control techniques. In this context, fuzzy logic controllers offer quite a straightforward way to control processes that are affected by nonlinear behavior and uncertain process knowledge. However, in order to maintain process safety and product quality it is necessary to specify the controller performance and to tune the controller parameters. In this work, an approach is presented to establish an intelligent control system for oxidoreductive yeast propagation as a representative process biased by the aforementioned uncertainties. The presented approach is based on statistical process control and fuzzy logic feedback control. As the cognitive uncertainty among different experts about the limits that define the control performance as still acceptable may differ a lot, a data-driven design method is performed. Based upon a historic data pool statistical process corridors are derived for the controller inputs control error and change in control error. This approach follows the hypothesis that if the control performance criteria stay within predefined statistical boundaries, the final process state meets the required quality definition. In order to keep the process on its optimal growth trajectory (model based reference trajectory a fuzzy logic controller is used that alternates the process temperature. Additionally, in order to stay within the process corridors, a genetic algorithm was applied to tune the input and output fuzzy sets of a preliminarily parameterized fuzzy controller. The presented experimental results show that the genetic tuned fuzzy controller is able to keep the process within its allowed limits. The average absolute error to the

  20. Neuro-fuzzy model for evaluating the performance of processes ...

    Indian Academy of Sciences (India)

    CHIDOZIE CHUKWUEMEKA NWOBI-OKOYE

    2017-11-16

    Nov 16, 2017 ... In this work an Adaptive Neuro-Fuzzy Inference System (ANFIS) was used to model the periodic performance of ... Since the .... The investigation hubs are a local brewing company ..... Industrial Engineers, Systems Engineers, Operations ... responsibility the overall management of the new system lies.

  1. Hesitant triangular fuzzy information aggregation operators based on Bonferroni means and their application to multiple attribute decision making.

    Science.gov (United States)

    Wang, Chunyong; Li, Qingguo; Zhou, Xiaoqiang; Yang, Tian

    2014-01-01

    We investigate the multiple attribute decision-making (MADM) problems with hesitant triangular fuzzy information. Firstly, definition and some operational laws of hesitant triangular fuzzy elements are introduced. Then, we develop some hesitant triangular fuzzy aggregation operators based on Bonferroni means and discuss their basic properties. Some existing operators can be viewed as their special cases. Next, we apply the proposed operators to deal with multiple attribute decision-making problems under hesitant triangular fuzzy environment. Finally, an illustrative example is given to show the developed method and demonstrate its practicality and effectiveness.

  2. FUZZY ANALYTICAL HIERARCHY PROCESS (FAHP PADA PENERIMA BANTUAN STIMULAN PERUMAHAN SWADAYA

    Directory of Open Access Journals (Sweden)

    Fathul Hadi

    2016-04-01

    Full Text Available Assistance a stimulant self built housing (ASSH is facilities the government of social assistance to the community low income. But, the agency to different selection community recipient assistance. And maybe wrong about recipient assistance. A method of Fuzzy AHP is one of the methods rangking and this method better description decision to recipient assistance. Of the calculation on than 60 data recipients chosen 20 data recipients. And is found 10 different data from the agency data because alternatives value is 0.92. A method of Fuzzy AHP can be used in the determination of recipient assistance a stimulant self built housing. Keywords : ASSH, Fuzzy AHP, The Support System Decision Bantuan Stimulan Perumahan Swadaya (BSPS adalah fasilitas pemerintah berupa bantuan sosial kepada masyarakat berpenghasilan rendah. Namun, pemerintah masih kesulitan dalam menyeleksi masyarakat yang berhak mendapatkan bantuan. Dan sering terjadi kesalahan dalam menentukan penerima bantuan, seperti bantuan diberikan kepada penerima yang tidak layak mendapatkan bantuan. Metode Fuzzy Analytical Hierarchy Process merupakan salah satu metode perangkingan dan dengan metode ini dianggap lebih baik dalam mendeskripsikan keputusan yang samar-samar dalam menentukan penerima bantuan. Dari Hasil Perhitungan dari 60 data calon penerima dipilih 20 data penerima. Dan didapat 10 data yang berbeda dari data dinas dikarenakan nilai alternatifnya yaitu 0.92. Metode Fuzzy AHP dapat digunakan dalam penentuan penerima bantuan stimulan perumahan swadaya. Kata kunci : BSPS, Fuzzy AHP, Sistem Pendukung Keputusan

  3. Genetic Learning of Fuzzy Expert Systems for Decision Support in the Automated Process of Wooden Boards Cutting

    Directory of Open Access Journals (Sweden)

    Yaroslav MATSYSHYN

    2014-03-01

    Full Text Available Sawing solid wood (lumber, wooden boards into blanks is an important technological operation, which has significant influence on the efficiency of the woodworking industry as a whole. Selecting a rational variant of lumber cutting is a complex multicriteria problem with many stochastic factors, characterized by incomplete information and fuzzy attributes. About this property by currently used automatic optimizing cross-cut saw is not always rational use of wood raw material. And since the optimization algorithms of these saw functions as a “black box”, their improvement is not possible. Therefore topical the task of developing a new approach to the optimal cross-cutting that takes into account stochastic properties of wood as a material from biological origin. Here we propose a new approach to the problem of lumber optimal cutting in the conditions of uncertainty of lumber quantity and fuzziness lengths of defect-free areas. To account for these conditions, we applied the methods of fuzzy sets theory and used a genetic algorithm to simulate the process of human learning in the implementation the technological operation. Thus, the rules of behavior with yet another defect-free area is defined in fuzzy expert system that can be configured to perform specific production tasks using genetic algorithm. The author's implementation of the genetic algorithm is used to set up the parameters of fuzzy expert system. Working capacity of the developed system verified on simulated and real-world data. Implementation of this approach will make it suitable for the control of automated or fully automatic optimizing cross cutting of solid wood.

  4. Fuzzy-rule-based Adaptive Resource Control for Information Sharing in P2P Networks

    Science.gov (United States)

    Wu, Zhengping; Wu, Hao

    With more and more peer-to-peer (P2P) technologies available for online collaboration and information sharing, people can launch more and more collaborative work in online social networks with friends, colleagues, and even strangers. Without face-to-face interactions, the question of who can be trusted and then share information with becomes a big concern of a user in these online social networks. This paper introduces an adaptive control service using fuzzy logic in preference definition for P2P information sharing control, and designs a novel decision-making mechanism using formal fuzzy rules and reasoning mechanisms adjusting P2P information sharing status following individual users' preferences. Applications of this adaptive control service into different information sharing environments show that this service can provide a convenient and accurate P2P information sharing control for individual users in P2P networks.

  5. Fuzzy methods in decision making process - A particular approach in manufacturing systems

    Science.gov (United States)

    Coroiu, A. M.

    2015-11-01

    We are living in a competitive environment, so we can see and understand that the most of manufacturing firms do the best in order to accomplish meeting demand, increasing quality, decreasing costs, and delivery rate. In present a stake point of interest is represented by the development of fuzzy technology. A particular approach for this is represented through the development of methodologies to enhance the ability to managed complicated optimization and decision making aspects involving non-probabilistic uncertainty with the reason to understand, development, and practice the fuzzy technologies to be used in fields such as economic, engineering, management, and societal problems. Fuzzy analysis represents a method for solving problems which are related to uncertainty and vagueness; it is used in multiple areas, such as engineering and has applications in decision making problems, planning and production. As a definition for decision making process we can use the next one: result of mental processes based upon cognitive process with a main role in the selection of a course of action among several alternatives. Every process of decision making can be represented as a result of a final choice and the output can be represented as an action or as an opinion of choice. Different types of uncertainty can be discovered in a wide variety of optimization and decision making problems related to planning and operation of power systems and subsystems. The mixture of the uncertainty factor in the construction of different models serves for increasing their adequacy and, as a result, the reliability and factual efficiency of decisions based on their analysis. Another definition of decision making process which came to illustrate and sustain the necessity of using fuzzy method: the decision making is an approach of choosing a strategy among many different projects in order to achieve some purposes and is formulated as three different models: high risk decision, usual risk

  6. Fuzzy tree automata and syntactic pattern recognition.

    Science.gov (United States)

    Lee, E T

    1982-04-01

    An approach of representing patterns by trees and processing these trees by fuzzy tree automata is described. Fuzzy tree automata are defined and investigated. The results include that the class of fuzzy root-to-frontier recognizable ¿-trees is closed under intersection, union, and complementation. Thus, the class of fuzzy root-to-frontier recognizable ¿-trees forms a Boolean algebra. Fuzzy tree automata are applied to processing fuzzy tree representation of patterns based on syntactic pattern recognition. The grade of acceptance is defined and investigated. Quantitative measures of ``approximate isosceles triangle,'' ``approximate elongated isosceles triangle,'' ``approximate rectangle,'' and ``approximate cross'' are defined and used in the illustrative examples of this approach. By using these quantitative measures, a house, a house with high roof, and a church are also presented as illustrative examples. In addition, three fuzzy tree automata are constructed which have the capability of processing the fuzzy tree representations of ``fuzzy houses,'' ``houses with high roofs,'' and ``fuzzy churches,'' respectively. The results may have useful applications in pattern recognition, image processing, artificial intelligence, pattern database design and processing, image science, and pictorial information systems.

  7. Pythagorean fuzzy analytic hierarchy process to multi-criteria decision making

    Science.gov (United States)

    Mohd, Wan Rosanisah Wan; Abdullah, Lazim

    2017-11-01

    A numerous approaches have been proposed in the literature to determine the criteria of weight. The weight of criteria is very significant in the process of decision making. One of the outstanding approaches that used to determine weight of criteria is analytic hierarchy process (AHP). This method involves decision makers (DMs) to evaluate the decision to form the pair-wise comparison between criteria and alternatives. In classical AHP, the linguistic variable of pairwise comparison is presented in terms of crisp value. However, this method is not appropriate to present the real situation of the problems because it involved the uncertainty in linguistic judgment. For this reason, AHP has been extended by incorporating the Pythagorean fuzzy sets. In addition, no one has found in the literature proposed how to determine the weight of criteria using AHP under Pythagorean fuzzy sets. In order to solve the MCDM problem, the Pythagorean fuzzy analytic hierarchy process is proposed to determine the criteria weight of the evaluation criteria. Using the linguistic variables, pairwise comparison for evaluation criteria are made to the weights of criteria using Pythagorean fuzzy numbers (PFNs). The proposed method is implemented in the evaluation problem in order to demonstrate its applicability. This study shows that the proposed method provides us with a useful way and a new direction in solving MCDM problems with Pythagorean fuzzy context.

  8. GIS-based flood risk model evaluated by Fuzzy Analytic Hierarchy Process (FAHP)

    Science.gov (United States)

    Sukcharoen, Tharapong; Weng, Jingnong; Teetat, Charoenkalunyuta

    2016-10-01

    Over the last 2-3 decades, the economy of many countries around the world has been developed rapidly but it was unbalanced development because of expecting on economic growth only. Meanwhile it lacked of effective planning in the use of natural resources. This can significantly induce climate change which is major cause of natural disaster. Hereby, Thailand has also suffered from natural disaster for ages. Especially, the flood which is most hazardous disaster in Thailand can annually result in the great loss of life and property, environment and economy. Since the flood management of country is inadequate efficiency. It is unable to support the flood analysis comprehensively. This paper applied Geographic Information System and Multi-Criteria Decision Making to create flood risk model at regional scale. Angthong province in Thailand was used as the study area. In practical process, Fuzzy logic technique has been used to improve specialist's assessment by implementing with Fuzzy membership because human decision is flawed under uncertainty then AHP technique was processed orderly. The hierarchy structure in this paper was categorized the spatial flood factors into two levels as following: 6 criteria (Meteorology, Geology, Topography, Hydrology, Human and Flood history) and 8 factors (Average Rainfall, Distance from Stream, Soil drainage capability, Slope, Elevation, Land use, Distance from road and Flooded area in the past). The validity of the pair-wise comparison in AHP was shown as C.R. value which indicated that the specialist judgment was reasonably consistent. FAHP computation result has shown that the first priority of criteria was Meteorology. In addition, the Rainfall was the most influencing factor for flooding. Finally, the output was displayed in thematic map of Angthong province with flood risk level processed by GIS tools. The map was classified into: High Risk, Moderate Risk and Low Risk (13.20%, 75.58%, and 11.22% of total area).

  9. Performance of Globally Linearized Controller and Two Region Fuzzy Logic Controller on a Nonlinear Process

    Directory of Open Access Journals (Sweden)

    N. Jaya

    2008-10-01

    Full Text Available In this work, a design and implementation of a Conventional PI controller, single region fuzzy logic controller, two region fuzzy logic controller and Globally Linearized Controller (GLC for a two capacity interacting nonlinear process is carried out. The performance of this process using single region FLC, two region FLC and GLC are compared with the performance of conventional PI controller about an operating point of 50 %. It has been observed that GLC and two region FLC provides better performance. Further, this procedure is also validated by real time experimentation using dSPACE.

  10. Fuzzy Coordinated PI Controller: Application to the Real-Time Pressure Control Process

    Directory of Open Access Journals (Sweden)

    N. Kanagaraj

    2008-01-01

    Full Text Available This paper presents the real-time implementation of a fuzzy coordinated classical PI control scheme for controlling the pressure in a pilot pressure tank system. The fuzzy system has been designed to track the variation parameters in a feedback loop and tune the classical controller to achieve a better control action for load disturbances and set point changes. The error and process inputs are chosen as the inputs of fuzzy system to tune the conventional PI controller according to the process condition. This online conventional controller tuning technique will reduce the human involvement in controller tuning and increase the operating range of the conventional controller. The proposed control algorithm is experimentally implemented for the real-time pressure control of a pilot air tank system and validated using a high-speed 32-bit ARM7 embedded microcontroller board (ATMEL AT91M55800A. To demonstrate the performance of the fuzzy coordinated PI control scheme, results are compared with a classical PI and PI-type fuzzy control method. It is observed that the proposed controller structure is able to quickly track the parameter variation and perform better in load disturbances and also for set point changes.

  11. Supplier Selection for Food Industry: A Combination of Taguchi Loss Function and Fuzzy Analytical Hierarchy Process

    Directory of Open Access Journals (Sweden)

    Renna Magdalena

    2012-09-01

    Full Text Available Supplier selection is an important part of supply chain management process by which firms identify, evaluate, and establish contracts with suppliers. Deciding the right supplier can be a complex task. As such, various criteria must be taken into account to choose the best supplier. This study focused on the supply in the packaging division of a food industry in Denpasar-Bali. A combination of Taguchi Loss Function and fuzzy-AHP (Analytical Hierarchy Process Fuzzy Linear Programming was used to determine the best supplier. In this analysis, several suppliers’ criteria were considered, namely quality, delivery, completeness, quality loss and environmental management. By maximizing the suppliers’ performances based on each criterion and aggregating the suppliers’ performances based on the overall criteria, the best supplier was determined. Keywords: supplier selection, taguchi loss function, AHP, fuzzy linear programming,environment

  12. Determination of Optimal Opening Scheme for Electromagnetic Loop Networks Based on Fuzzy Analytic Hierarchy Process

    Directory of Open Access Journals (Sweden)

    Yang Li

    2016-01-01

    Full Text Available Studying optimization and decision for opening electromagnetic loop networks plays an important role in planning and operation of power grids. First, the basic principle of fuzzy analytic hierarchy process (FAHP is introduced, and then an improved FAHP-based scheme evaluation method is proposed for decoupling electromagnetic loop networks based on a set of indicators reflecting the performance of the candidate schemes. The proposed method combines the advantages of analytic hierarchy process (AHP and fuzzy comprehensive evaluation. On the one hand, AHP effectively combines qualitative and quantitative analysis to ensure the rationality of the evaluation model; on the other hand, the judgment matrix and qualitative indicators are expressed with trapezoidal fuzzy numbers to make decision-making more realistic. The effectiveness of the proposed method is validated by the application results on the real power system of Liaoning province of China.

  13. Methods of information processing

    Energy Technology Data Exchange (ETDEWEB)

    Kosarev, Yu G; Gusev, V D

    1978-01-01

    Works are presented on automation systems for editing and publishing operations by methods of processing symbol information and information contained in training selection (ranking of objectives by promise, classification algorithm of tones and noise). The book will be of interest to specialists in the automation of processing textural information, programming, and pattern recognition.

  14. Fuzzy control with random delays using invariant cones and its application to control of energy processes in microelectromechanical motion devices

    Energy Technology Data Exchange (ETDEWEB)

    Sinha, A.S.C. [Purdue Univ., Indianapolis, IN (United States). Dept. of Electrical Engineering; Lyshevski, S. [Rochester Inst. of Technology, NY (United States)

    2005-05-01

    In this paper, a class of microelectromechanical systems described by nonlinear differential equations with random delays is examined. Robust fuzzy controllers are designed to control the energy conversion processes with the ultimate objective to guarantee optimal achievable performance. The fuzzy rule base used consists of a collection of r fuzzy IF-THEN rules defined as a function of the conditional variable. The method of the theory of cones and Lyapunov functionals is used to design a class of local fuzzy control laws. A verifiably sufficient condition for stochastic stability of fuzzy stochastic microelectromechanical systems is given. As an example, we have considered the design of a fuzzy control law for an electrostatic micromotor. (author)

  15. Fuzzy control with random delays using invariant cones and its application to control of energy processes in microelectromechanical motion devices

    International Nuclear Information System (INIS)

    Sinha, A.S.C.; Lyshevski, S.

    2005-01-01

    In this paper, a class of microelectromechanical systems described by nonlinear differential equations with random delays is examined. Robust fuzzy controllers are designed to control the energy conversion processes with the ultimate objective to guarantee optimal achievable performance. The fuzzy rule base used consists of a collection of r fuzzy IF-THEN rules defined as a function of the conditional variable. The method of the theory of cones and Lyapunov functionals is used to design a class of local fuzzy control laws. A verifiably sufficient condition for stochastic stability of fuzzy stochastic microelectromechanical systems is given. As an example, we have considered the design of a fuzzy control law for an electrostatic micromotor

  16. 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

  17. Query Processing and Interlinking of Fuzzy Object-Oriented Database

    OpenAIRE

    Shweta Dwivedi; Santosh Kumar

    2017-01-01

    Due to the many limitation and poor data handling in the existing relational database, the software professional and researchers moves towards the object-oriented database which has much better capability to handling the real and complex real world data i.e. clear and crisp data and also have the capability to perform some huge and complex queries in an effective manner. On the other hand, a new approach in database is introduced named as Fuzzy Object-Oriented Database (FOOD); it has all the ...

  18. Natural Information Processing Systems

    OpenAIRE

    John Sweller; Susan Sweller

    2006-01-01

    Natural information processing systems such as biological evolution and human cognition organize information used to govern the activities of natural entities. When dealing with biologically secondary information, these systems can be specified by five common principles that we propose underlie natural information processing systems. The principles equate: (1) human long-term memory with a genome; (2) learning from other humans with biological reproduction; (3) problem solving through random ...

  19. FUZZY LOGIC CONTROLLER AS MODELING TOOL FOR THE BURNING PROCESS OF A CEMENT PRODUCTION PLANT

    Directory of Open Access Journals (Sweden)

    P.B. Osofisan

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT: A comprehensive optimisation of the cement production process presents a problem since the input variables as well as the output variables are non-linear, interdependent and contain uncertainties. To arrive at a solution, a Fuzzy Logic controller has been designed to achieve a well-defined relationship between the main and vital variables through the instrumentality of a Fuzzy Model. The Fuzzy Logic controller has been simulated on a digital computer using MATLAB 5.0 Fuzzy Logic Tool Box, using data from a local cement production plant.

    AFRIKAANSE OPSOMMING: Die omvattende optimisering van 'n proses wat sement vervaardig, word beskryf deur nie-linieêre inset- en uitsetveranderlikes wat onderling afhanklik is, en ook van onsekere aard is. Om 'n optimum oplossing te verkry, word 'n Wasigheidsmodel gebruik. Die model word getoets deur gebruik te maak van die MATLAB 5.0 Fuzzy Logic Tool Box en data vanaf 'n lokale sementvervaardigingsaanleg.

  20. Quantum information processing

    National Research Council Canada - National Science Library

    Leuchs, Gerd; Beth, Thomas

    2003-01-01

    ... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.5 SimulationofHamiltonians... References... 1 1 1 3 5 8 10 2 Quantum Information Processing and Error Correction with Jump Codes (G. Alber, M. Mussinger...

  1. Application of ANNs approach for solving fully fuzzy polynomials system

    Directory of Open Access Journals (Sweden)

    R. Novin

    2017-11-01

    Full Text Available In processing indecisive or unclear information, the advantages of fuzzy logic and neurocomputing disciplines should be taken into account and combined by fuzzy neural networks. The current research intends to present a fuzzy modeling method using multi-layer fuzzy neural networks for solving a fully fuzzy polynomials system. To clarify the point, it is necessary to inform that a supervised gradient descent-based learning law is employed. The feasibility of the method is examined using computer simulations on a numerical example. The experimental results obtained from the investigation of the proposed method are valid and delivers very good approximation results.

  2. Hybrid Metaheuristics for Solving a Fuzzy Single Batch-Processing Machine Scheduling Problem

    Directory of Open Access Journals (Sweden)

    S. Molla-Alizadeh-Zavardehi

    2014-01-01

    Full Text Available This paper deals with a problem of minimizing total weighted tardiness of jobs in a real-world single batch-processing machine (SBPM scheduling in the presence of fuzzy due date. In this paper, first a fuzzy mixed integer linear programming model is developed. Then, due to the complexity of the problem, which is NP-hard, we design two hybrid metaheuristics called GA-VNS and VNS-SA applying the advantages of genetic algorithm (GA, variable neighborhood search (VNS, and simulated annealing (SA frameworks. Besides, we propose three fuzzy earliest due date heuristics to solve the given problem. Through computational experiments with several random test problems, a robust calibration is applied on the parameters. Finally, computational results on different-scale test problems are presented to compare the proposed algorithms.

  3. Optimal operation planning of radioactive waste processing system by fuzzy theory

    International Nuclear Information System (INIS)

    Yang, Jin Yeong; Lee, Kun Jai

    2000-01-01

    This study is concerned with the applications of linear goal programming and fuzzy theory to the analysis of management and operational problems in the radioactive processing system (RWPS). The developed model is validated and verified using actual data obtained from the RWPS at Kyoto University in Japan. The solution by goal programming and fuzzy theory would show the optimal operation point which is to maximize the total treatable radioactive waste volume and minimize the released radioactivity of liquid waste even under the restricted resources. (orig.)

  4. The Use of Fuzzy Cognitive Maps in Analyzing and Implementation of ITIL Processes

    OpenAIRE

    Zarrazvand, Hamid; Shojafar, Mohammad

    2012-01-01

    Information Technology Infrastructure Library (ITIL) is series of best practices that helps Information technology Organizations to provide Information technology (IT) services for their customers with better performances and quality. This article is looking for a way to implement ITIL in an organization and also using Fuzzy Cognitive Maps (FCM) to model the problem for better understanding of environment. ITIL helps to improve the performance of IT services in order to gain business objectiv...

  5. A Fuzzy Knowledge Representation Model for Student Performance Assessment

    DEFF Research Database (Denmark)

    Badie, Farshad

    Knowledge representation models based on Fuzzy Description Logics (DLs) can provide a foundation for reasoning in intelligent learning environments. While basic DLs are suitable for expressing crisp concepts and binary relationships, Fuzzy DLs are capable of processing degrees of truth/completene......Knowledge representation models based on Fuzzy Description Logics (DLs) can provide a foundation for reasoning in intelligent learning environments. While basic DLs are suitable for expressing crisp concepts and binary relationships, Fuzzy DLs are capable of processing degrees of truth....../completeness about vague or imprecise information. This paper tackles the issue of representing fuzzy classes using OWL2 in a dataset describing Performance Assessment Results of Students (PARS)....

  6. Hybrid quantum information processing

    Energy Technology Data Exchange (ETDEWEB)

    Furusawa, Akira [Department of Applied Physics, School of Engineering, The University of Tokyo (Japan)

    2014-12-04

    I will briefly explain the definition and advantage of hybrid quantum information processing, which is hybridization of qubit and continuous-variable technologies. The final goal would be realization of universal gate sets both for qubit and continuous-variable quantum information processing with the hybrid technologies. For that purpose, qubit teleportation with a continuousvariable teleporter is one of the most important ingredients.

  7. Dual Processes in Decision Making and Developmental Neuroscience: A Fuzzy-Trace Model

    Science.gov (United States)

    Reyna, Valerie F.; Brainerd, Charles J.

    2011-01-01

    From Piaget to the present, traditional and dual-process theories have predicted improvement in reasoning from childhood to adulthood, and improvement has been observed. However, developmental reversals--that reasoning biases emerge with development--have also been observed in a growing list of paradigms. We explain how fuzzy-trace theory predicts…

  8. An Application of Fuzzy Analytic Hierarchy Process (FAHP) for Evaluating Students' Project

    Science.gov (United States)

    Çebi, Ayça; Karal, Hasan

    2017-01-01

    In recent years, artificial intelligence applications for understanding the human thinking process and transferring it to virtual environments come into prominence. The fuzzy logic which paves the way for modeling human behaviors and expressing even vague concepts mathematically, and is also regarded as an artificial intelligence technique has…

  9. An Assessment Model of National Grants of University Based on Fuzzy Analytic Hierarchy Process

    Directory of Open Access Journals (Sweden)

    Xia Yang

    2016-01-01

    Full Text Available How to assess kinds of grants scientifically, effectively and regularly is an important topic for the funding workers to study. According to the national grants’ basic conditions, an assessment model is established on the basis of fuzzy analytic hierarchy process. And Finally an example is given to illustrate the scientificalness and operability of this model.

  10. Application of Fuzzy Sets in an Expert System For Technological Process Management

    Directory of Open Access Journals (Sweden)

    Filip Tošenovský

    2011-12-01

    Full Text Available The paper is preoccupied with application of an expert system in the management of a process with one input and one output, using the fuzzy set theory. It resolves the problem of formalization of a verbal description of the process management coupled with the use of process operator’s experience. The procedure that calculates regulatory intervention in the process is presented and accompanied by graphical illustrations.

  11. Management of Uncertainty by Statistical Process Control and a Genetic Tuned Fuzzy System

    OpenAIRE

    Birle, Stephan;Hussein, Mohamed Ahmed;Becker, Thomas

    2017-01-01

    In food industry, bioprocesses like fermentation often are a crucial part of the manufacturing process and decisive for the final product quality. In general, they are characterized by highly nonlinear dynamics and uncertainties that make it difficult to control these processes by the use of traditional control techniques. In this context, fuzzy logic controllers offer quite a straightforward way to control processes that are affected by nonlinear behavior and uncertain process knowledge. How...

  12. An approach for environmental risk assessment of engineered nanomaterials using Analytical Hierarchy Process (AHP) and fuzzy inference rules.

    Science.gov (United States)

    Topuz, Emel; van Gestel, Cornelis A M

    2016-01-01

    The usage of Engineered Nanoparticles (ENPs) in consumer products is relatively new and there is a need to conduct environmental risk assessment (ERA) to evaluate their impacts on the environment. However, alternative approaches are required for ERA of ENPs because of the huge gap in data and knowledge compared to conventional pollutants and their unique properties that make it difficult to apply existing approaches. This study aims to propose an ERA approach for ENPs by integrating Analytical Hierarchy Process (AHP) and fuzzy inference models which provide a systematic evaluation of risk factors and reducing uncertainty about the data and information, respectively. Risk is assumed to be the combination of occurrence likelihood, exposure potential and toxic effects in the environment. A hierarchy was established to evaluate the sub factors of these components. Evaluation was made with fuzzy numbers to reduce uncertainty and incorporate the expert judgements. Overall score of each component was combined with fuzzy inference rules by using expert judgements. Proposed approach reports the risk class and its membership degree such as Minor (0.7). Therefore, results are precise and helpful to determine the risk management strategies. Moreover, priority weights calculated by comparing the risk factors based on their importance for the risk enable users to understand which factor is effective on the risk. Proposed approach was applied for Ag (two nanoparticles with different coating) and TiO2 nanoparticles for different case studies. Results verified the proposed benefits of the approach. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. Multicriteria Personnel Selection by the Modified Fuzzy VIKOR Method

    Directory of Open Access Journals (Sweden)

    Rasim M. Alguliyev

    2015-01-01

    Full Text Available Personnel evaluation is an important process in human resource management. The multicriteria nature and the presence of both qualitative and quantitative factors make it considerably more complex. In this study, a fuzzy hybrid multicriteria decision-making (MCDM model is proposed to personnel evaluation. This model solves personnel evaluation problem in a fuzzy environment where both criteria and weights could be fuzzy sets. The triangular fuzzy numbers are used to evaluate the suitability of personnel and the approximate reasoning of linguistic values. For evaluation, we have selected five information culture criteria. The weights of the criteria were calculated using worst-case method. After that, modified fuzzy VIKOR is proposed to rank the alternatives. The outcome of this research is ranking and selecting best alternative with the help of fuzzy VIKOR and modified fuzzy VIKOR techniques. A comparative analysis of results by fuzzy VIKOR and modified fuzzy VIKOR methods is presented. Experiments showed that the proposed modified fuzzy VIKOR method has some advantages over fuzzy VIKOR method. Firstly, from a computational complexity point of view, the presented model is effective. Secondly, compared to fuzzy VIKOR method, it has high acceptable advantage compared to fuzzy VIKOR method.

  14. Scientific information processing procedures

    Directory of Open Access Journals (Sweden)

    García, Maylin

    2013-07-01

    Full Text Available The paper systematizes several theoretical view-points on scientific information processing skill. It decomposes the processing skills into sub-skills. Several methods such analysis, synthesis, induction, deduction, document analysis were used to build up a theoretical framework. Interviews and survey to professional being trained and a case study was carried out to evaluate the results. All professional in the sample improved their performance in scientific information processing.

  15. 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.

  16. A new intuitionistic fuzzy rule-based decision-making system for an operating system process scheduler.

    Science.gov (United States)

    Butt, Muhammad Arif; Akram, Muhammad

    2016-01-01

    We present a new intuitionistic fuzzy rule-based decision-making system based on intuitionistic fuzzy sets for a process scheduler of a batch operating system. Our proposed intuitionistic fuzzy scheduling algorithm, inputs the nice value and burst time of all available processes in the ready queue, intuitionistically fuzzify the input values, triggers appropriate rules of our intuitionistic fuzzy inference engine and finally calculates the dynamic priority (dp) of all the processes in the ready queue. Once the dp of every process is calculated the ready queue is sorted in decreasing order of dp of every process. The process with maximum dp value is sent to the central processing unit for execution. Finally, we show complete working of our algorithm on two different data sets and give comparisons with some standard non-preemptive process schedulers.

  17. Quantum Information Processing

    CERN Document Server

    Leuchs, Gerd

    2005-01-01

    Quantum processing and communication is emerging as a challenging technique at the beginning of the new millennium. This is an up-to-date insight into the current research of quantum superposition, entanglement, and the quantum measurement process - the key ingredients of quantum information processing. The authors further address quantum protocols and algorithms. Complementary to similar programmes in other countries and at the European level, the German Research Foundation (DFG) started a focused research program on quantum information in 1999. The contributions - written by leading experts - bring together the latest results in quantum information as well as addressing all the relevant questions

  18. 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.

  19. 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...

  20. A Fuzzy Expression Way for Air Quality Index with More Comprehensive Information

    Directory of Open Access Journals (Sweden)

    Yujie Wang

    2017-01-01

    Full Text Available The Air Quality Index (AQI is an evaluating indicator for the atmospheric environment released by various environmental monitoring centers to communicate the present air quality status to the public, which is calculated by the aid of the monitored concentrations of six common air pollutants and relevant computational formulae. Considering that the historical data of daily overall AQI illustrated by the traditional expression way merely contain limited information about the original data, this paper puts forward a more concrete and intuitive way to express the air quality in the past day. By analyzing the data concerning individual air quality indices of pollutants gathered from five cities of China for six consecutive months and conducting the curve fitting, each sub-index is recommended to be set as a Gaussian fuzzy number. Accordingly, taking advantage of the novel operational law for fuzzy numbers, the fuzzy distribution and membership function of the daily overall AQI can be deduced immediately, which as a reference contributes to the users acquiring the information more intuitively and facilitates making plans or decisions. Subsequently, a case study taking Shanghai as a background is conducted to elaborate the application of the proposed approach. Furthermore, the line chart reflecting the overall air quality status in a past period is depicted, based on which an example of selecting a tourist destination is given to demonstrate its utilization.

  1. Improving the anesthetic process by a fuzzy rule based medical decision system.

    Science.gov (United States)

    Mendez, Juan Albino; Leon, Ana; Marrero, Ayoze; Gonzalez-Cava, Jose M; Reboso, Jose Antonio; Estevez, Jose Ignacio; Gomez-Gonzalez, José F

    2018-01-01

    The main objective of this research is the design and implementation of a new fuzzy logic tool for automatic drug delivery in patients undergoing general anesthesia. The aim is to adjust the drug dose to the real patient needs using heuristic knowledge provided by clinicians. A two-level computer decision system is proposed. The idea is to release the clinician from routine tasks so that he can focus on other variables of the patient. The controller uses the Bispectral Index (BIS) to assess the hypnotic state of the patient. Fuzzy controller was included in a closed-loop system to reach the BIS target and reject disturbances. BIS was measured using a BIS VISTA monitor, a device capable of calculating the hypnosis level of the patient through EEG information. An infusion pump with propofol 1% is used to supply the drug to the patient. The inputs to the fuzzy inference system are BIS error and BIS rate. The output is infusion rate increment. The mapping of the input information and the appropriate output is given by a rule-base based on knowledge of clinicians. To evaluate the performance of the fuzzy closed-loop system proposed, an observational study was carried out. Eighty one patients scheduled for ambulatory surgery were randomly distributed in 2 groups: one group using a fuzzy logic based closed-loop system (FCL) to automate the administration of propofol (42 cases); the second group using manual delivering of the drug (39 cases). In both groups, the BIS target was 50. The FCL, designed with intuitive logic rules based on the clinician experience, performed satisfactorily and outperformed the manual administration in patients in terms of accuracy through the maintenance stage. Copyright © 2018 Elsevier B.V. All rights reserved.

  2. Green Suppliers Performance Evaluation in Belt and Road Using Fuzzy Weighted Average with Social Media Information

    Directory of Open Access Journals (Sweden)

    Kuo-Ping Lin

    2017-12-01

    Full Text Available A decision model for selecting a suitable supplier is a key to reducing the environmental impact in green supply chain management for high-tech companies. Traditional fuzzy weight average (FWA adopts linguistic variable to determine weight by experts. However, the weights of FWA have not considered the public voice, meaning the viewpoints of consumers in green supply chain management. This paper focuses on developing a novel decision model for green supplier selection in the One Belt and One Road (OBOR initiative through a fuzzy weighted average approach with social media. The proposed decision model uses the membership grade of the criteria and sub-criteria and its relative weights, which consider the volume of social media, to establish an analysis matrix of green supplier selection. Then, the proposed fuzzy weighted average approach is considered as an aggregating tool to calculate a synthetic score for each green supplier in the Belt and Road initiative. The final score of the green supplier is ordered by a non-fuzzy performance value ranking method to help the consumer make a decision. A case of green supplier selection in the light-emitting diode (LED industry is used to demonstrate the proposed decision model. The findings demonstrate (1 the consumer’s main concerns are the “Quality” and “Green products” in LED industry, hence, the ranking of suitable supplier in FWA with social media information model obtained the difference result with tradition FWA; (2 OBOR in the LED industry is not fervently discussed in searches of Google and Twitter; and (3 the FWA with social media information could objectively analyze the green supplier selection because the novel model considers the viewpoints of the consumer.

  3. Incorporation of negative rules and evolution of a fuzzy controller for yeast fermentation process.

    Science.gov (United States)

    Birle, Stephan; Hussein, Mohamed Ahmed; Becker, Thomas

    2016-08-01

    The control of bioprocesses can be very challenging due to the fact that these kinds of processes are highly affected by various sources of uncertainty like the intrinsic behavior of the used microorganisms. Due to the reason that these kinds of process uncertainties are not directly measureable in most cases, the overall control is either done manually because of the experience of the operator or intelligent expert systems are applied, e.g., on the basis of fuzzy logic theory. In the latter case, however, the control concept is mainly represented by using merely positive rules, e.g., "If A then do B". As this is not straightforward with respect to the semantics of the human decision-making process that also includes negative experience in form of constraints or prohibitions, the incorporation of negative rules for process control based on fuzzy logic is emphasized. In this work, an approach of fuzzy logic control of the yeast propagation process based on a combination of positive and negative rules is presented. The process is guided along a reference trajectory for yeast cell concentration by alternating the process temperature. The incorporation of negative rules leads to a much more stable and accurate control of the process as the root mean squared error of reference trajectory and system response could be reduced by an average of 62.8 % compared to the controller using only positive rules.

  4. Evaluating water management strategies in watersheds by new hybrid Fuzzy Analytical Network Process (FANP) methods

    Science.gov (United States)

    RazaviToosi, S. L.; Samani, J. M. V.

    2016-03-01

    Watersheds are considered as hydrological units. Their other important aspects such as economic, social and environmental functions play crucial roles in sustainable development. The objective of this work is to develop methodologies to prioritize watersheds by considering different development strategies in environmental, social and economic sectors. This ranking could play a significant role in management to assign the most critical watersheds where by employing water management strategies, best condition changes are expected to be accomplished. Due to complex relations among different criteria, two new hybrid fuzzy ANP (Analytical Network Process) algorithms, fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and fuzzy max-min set methods are used to provide more flexible and accurate decision model. Five watersheds in Iran named Oroomeyeh, Atrak, Sefidrood, Namak and Zayandehrood are considered as alternatives. Based on long term development goals, 38 water management strategies are defined as subcriteria in 10 clusters. The main advantage of the proposed methods is its ability to overcome uncertainty. This task is accomplished by using fuzzy numbers in all steps of the algorithms. To validate the proposed method, the final results were compared with those obtained from the ANP algorithm and the Spearman rank correlation coefficient is applied to find the similarity in the different ranking methods. Finally, the sensitivity analysis was conducted to investigate the influence of cluster weights on the final ranking.

  5. Process optimization of citric acid production from aspergillus niger using fuzzy logic design

    International Nuclear Information System (INIS)

    Ali, S.; Haq, I.U.

    2014-01-01

    The inherent non-linearity of citric acid fermentation from Aspergillus niger renders its control difficult, so there is a need to fine-tune the bioreactor performance for maximum production of citric acid in batch culture. For this, fuzzy logic is becoming a popular tool to handle non-linearity of a batch process. The present manuscript deals with fuzzy logic control of citric acid accretion by A. niger in a stirred tank reactor using blackstrap sugarcane molasses as a basal fermentation medium. The customary batches were termed as 'control' while those under fuzzy logic were 'experimental'. The performance of fuzzy logic control of stirred tank reactor was found to be very encouraging for enhanced production of citric acid. The comparison of kinetic parameters showed improved citrate synthase ability of experimental culture (Yp/x = 7.042 g/g). When the culture grown on 150 g/l carbohydrates was monitored for Qp, Qs and Yp/s, there was significant enhancement in these variables over the control. Specific productivity of culture (qp = 0.070 g/g cells/h) was several fold increased. The enthalpy (HD = 70.5 kJ/mol) and entropy of activation (S = -144 J/mol/K) of enzyme for citric acid biosynthesis, free energies for transition state formation and substrate binding for sucrose hydrolysis of experimental were substantially improved. (author)

  6. MUNICIPAL LANDFILL SITE SELECTION FOR ISFAHAN CITY BY USE OF FUZZY LOGIC AND ANALYTIC HIERARCHY PROCESS

    Directory of Open Access Journals (Sweden)

    A. Afzali

    2011-09-01

    Full Text Available Selecting the most suitable site for landfill can avoid any ecological and socio-economical effects. The increase in industrial and economical development along with the increase of population growth in Isfahan city generates tremendous amount of solid waste within the region. Factors such as the scarcity of land, life span of landfill, and environmental considerations warrant that the scientific and fundamental studies are carried in selecting the suitability of a landfill site. The analysis of spatial data and consideration of regulations, and accepted criteria are part of the important elements in the site selection. The present study presents a multi criteria evaluation method using GIS technique for landfill suitability site evaluation. The Analytic Hierarchy Process (AHP was used for weighing the information layers. By using the fuzzy logic method (classification of suitable areas in the range of 0 to 255 byte scale the superposing of the information layers related to topography, soil, water table, sensitive ecosystems, land use and geology maps was performed in the study. Only after omission of inappropriate areas, the suitability examination of the residue areas was accomplished. The application of the present method in Isfahan city shows approximately 5% of the south east and north east parts of the study area with the value of more than 220 byte scale, which are suitable for landfill establishment.

  7. Fuzzy logic and its possibility using in automation of small-scale hydroelectric power plants regulation

    International Nuclear Information System (INIS)

    Puskajler, J.

    2004-01-01

    The paper explains how can computer understand and process inaccurate (indefinite) information. It is processing of terms like e.g. 'around in the middle of month' or 'not too big'. Fuzzy logic, fuzzy sets, operations with them, fuzzy rules and using of linguistics variables are explained. The possibilities of application of fuzzy systems in automation of regulation of small-scale hydro power plants are discussed. (author)

  8. Prediction on sunspot activity based on fuzzy information granulation and support vector machine

    Science.gov (United States)

    Peng, Lingling; Yan, Haisheng; Yang, Zhigang

    2018-04-01

    In order to analyze the range of sunspots, a combined prediction method of forecasting the fluctuation range of sunspots based on fuzzy information granulation (FIG) and support vector machine (SVM) was put forward. Firstly, employing the FIG to granulate sample data and extract va)alid information of each window, namely the minimum value, the general average value and the maximum value of each window. Secondly, forecasting model is built respectively with SVM and then cross method is used to optimize these parameters. Finally, the fluctuation range of sunspots is forecasted with the optimized SVM model. Case study demonstrates that the model have high accuracy and can effectively predict the fluctuation of sunspots.

  9. Fuzzy modeling with spatial information for geographic problems

    CERN Document Server

    Petry, Frederick E; Cobb, Maria A

    2005-01-01

    The capabilities of modern technology are rapidly increasing, spurred on to a large extent by the tremendous advances in communications and computing. Automated vehicles and global wireless connections are some examples of these advances. In order to take advantage of such enhanced capabilities, our need to model and manipulate our knowledge of the geophysical world, using compatible representations, is also rapidly increasing. In response to this one fundamental issue of great concern in modern geographical research is how to most effectively capture the physical world around us in systems like geographical information systems (GIS). Making this task even more challenging is the fact that uncertainty plays a pervasive role in the representation, analysis and use of geospatial information. The types of uncertainty that appear in geospatial information systems are not the just simple randomness of observation, as in weather data, but are manifested in many other forms including imprecision, incompleteness and ...

  10. Molecular processors: from qubits to fuzzy logic.

    Science.gov (United States)

    Gentili, Pier Luigi

    2011-03-14

    Single molecules or their assemblies are information processing devices. Herein it is demonstrated how it is possible to process different types of logic through molecules. As long as decoherent effects are maintained far away from a pure quantum mechanical system, quantum logic can be processed. If the collapse of superimposed or entangled wavefunctions is unavoidable, molecules can still be used to process either crisp (binary or multi-valued) or fuzzy logic. The way for implementing fuzzy inference engines is declared and it is supported by the examples of molecular fuzzy logic systems devised so far. Fuzzy logic is drawing attention in the field of artificial intelligence, because it models human reasoning quite well. This ability may be due to some structural analogies between a fuzzy logic system and the human nervous system. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. PREFACE: Quantum information processing

    Science.gov (United States)

    Briggs, Andrew; Ferry, David; Stoneham, Marshall

    2006-05-01

    Microelectronics and the classical information technologies transformed the physics of semiconductors. Photonics has given optical materials a new direction. Quantum information technologies, we believe, will have immense impact on condensed matter physics. The novel systems of quantum information processing need to be designed and made. Their behaviours must be manipulated in ways that are intrinsically quantal and generally nanoscale. Both in this special issue and in previous issues (see e.g., Spiller T P and Munro W J 2006 J. Phys.: Condens. Matter 18 V1-10) we see the emergence of new ideas that link the fundamentals of science to the pragmatism of market-led industry. We hope these papers will be followed by many others on quantum information processing in the Journal of Physics: Condensed Matter.

  12. 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...

  13. Automatic two- and three-dimensional mesh generation based on fuzzy knowledge processing

    Science.gov (United States)

    Yagawa, G.; Yoshimura, S.; Soneda, N.; Nakao, K.

    1992-09-01

    This paper describes the development of a novel automatic FEM mesh generation algorithm based on the fuzzy knowledge processing technique. A number of local nodal patterns are stored in a nodal pattern database of the mesh generation system. These nodal patterns are determined a priori based on certain theories or past experience of experts of FEM analyses. For example, such human experts can determine certain nodal patterns suitable for stress concentration analyses of cracks, corners, holes and so on. Each nodal pattern possesses a membership function and a procedure of node placement according to this function. In the cases of the nodal patterns for stress concentration regions, the membership function which is utilized in the fuzzy knowledge processing has two meanings, i.e. the “closeness” of nodal location to each stress concentration field as well as “nodal density”. This is attributed to the fact that a denser nodal pattern is required near a stress concentration field. What a user has to do in a practical mesh generation process are to choose several local nodal patterns properly and to designate the maximum nodal density of each pattern. After those simple operations by the user, the system places the chosen nodal patterns automatically in an analysis domain and on its boundary, and connects them smoothly by the fuzzy knowledge processing technique. Then triangular or tetrahedral elements are generated by means of the advancing front method. The key issue of the present algorithm is an easy control of complex two- or three-dimensional nodal density distribution by means of the fuzzy knowledge processing technique. To demonstrate fundamental performances of the present algorithm, a prototype system was constructed with one of object-oriented languages, Smalltalk-80 on a 32-bit microcomputer, Macintosh II. The mesh generation of several two- and three-dimensional domains with cracks, holes and junctions was presented as examples.

  14. Physics as Information Processing

    International Nuclear Information System (INIS)

    D'Ariano, Giacomo Mauro

    2011-01-01

    I review some recent advances in foundational research at Pavia QUIT group. The general idea is that there is only Quantum Theory without quantization rules, and the whole Physics - including space-time and relativity - is emergent from the quantum-information processing. And since Quantum Theory itself is axiomatized solely on informational principles, the whole Physics must be reformulated in information-theoretical terms: this is the It from bit of J. A. Wheeler.The review is divided into four parts: a) the informational axiomatization of Quantum Theory; b) how space-time and relativistic covariance emerge from quantum computation; c) what is the information-theoretical meaning of inertial mass and of (ℎ/2π), and how the quantum field emerges; d) an observational consequence of the new quantum field theory: a mass-dependent refraction index of vacuum. I will conclude with the research lines that will follow in the immediate future.

  15. Optimization of the Fermentation Process in a Brewery with a Fuzzy Logic Controller

    Directory of Open Access Journals (Sweden)

    Philip B. OSOFISAN

    2007-08-01

    Full Text Available In this research work, the fermentation process in a Brewery will be optimized, with the application of Fuzzy Logic Controller (FLC. Fermentation is controlled by regulating the temperature, the oxygen content and the pitch rate; but the temperature plays a dominant role in the optimization of the fermentation process. For our case study (Guinness Nigeria Plc the optimal fermentation temperature is 16ºC, so the FLC has been designed to maintain this temperature. The designed FLC can also be applied to maintain any other optimal fermentation temperature e.g. 20ºC. These two cases have been investigated. The FLC has been stimulated on a digital computer using MATLAB 5.0 Fuzzy Logic Tool Box.

  16. Fuzzy Pruning Based LS-SVM Modeling Development for a Fermentation Process

    Directory of Open Access Journals (Sweden)

    Weili Xiong

    2014-01-01

    Full Text Available Due to the complexity and uncertainty of microbial fermentation processes, data coming from the plants often contain some outliers. However, these data may be treated as the normal support vectors, which always deteriorate the performance of soft sensor modeling. Since the outliers also contaminate the correlation structure of the least square support vector machine (LS-SVM, the fuzzy pruning method is provided to deal with the problem. Furthermore, by assigning different fuzzy membership scores to data samples, the sensitivity of the model to the outliers can be reduced greatly. The effectiveness and efficiency of the proposed approach are demonstrated through two numerical examples as well as a simulator case of penicillin fermentation process.

  17. FUZZY REGRESSION MODEL TO PREDICT THE BEAD GEOMETRY IN THE ROBOTIC WELDING PROCESS

    Institute of Scientific and Technical Information of China (English)

    B.S. Sung; I.S. Kim; Y. Xue; H.H. Kim; Y.H. Cha

    2007-01-01

    Recently, there has been a rapid development in computer technology, which has in turn led todevelop the fully robotic welding system using artificial intelligence (AI) technology. However, therobotic welding system has not been achieved due to difficulties of the mathematical model andsensor technologies. The possibilities of the fuzzy regression method to predict the bead geometry,such as bead width, bead height, bead penetration and bead area in the robotic GMA (gas metalarc) welding process is presented. The approach, a well-known method to deal with the problemswith a high degree of fuzziness, is used to build the relationship between four process variablesand the four quality characteristics, respectively. Using these models, the proper prediction of theprocess variables for obtaining the optimal bead geometry can be determined.

  18. Fuzzy linguistic hedges for the selection of manufacturing process for prosthetic sockets

    Directory of Open Access Journals (Sweden)

    Richa Pandey

    2014-08-01

    Full Text Available In this paper, a comparison is presented between two prime methods of producing prosthetic sockets by using the fuzzy linguistic hedges approach on the qualitative feedback of Indian prosthetic users. Recent trends indicate that the Indian manufacturers have tried to adopt the newer technologies like reverse engineering (RE approach to achieve the desired goals. However, the satisfaction of the user is of utmost importance for the unique and customized products for rehabilitation. In order to analyze the effectiveness of the manufacturing approaches, user case studies are taken, based on the linguistic feedbacks, and a comparative study is conducted. Thirteen users from four different manufacturing units are taken for study and sockets made by conventional as well as RE are experimented. Fuzzy membership functions are constructed using the linguistic hedges based on the user feedbacks. An analytical hierarchy process (AHP is applied to arrive at a decision to select the manufacturing process for user satisfaction and manufacturing excellence.

  19. The environmental evaluation of substation based on the fuzzy analytic hierarchy process

    Science.gov (United States)

    Qian, Wenxiao; Zuo, Xiujiang; Chen, Yuandong; Ye, Ming; Fang, Zhankai; Yang, Fan

    2018-02-01

    This paper studies on the different influences on the environment of the substations and puts forward an index system of environmental protection through the fuzzy analytic hierarchy process. A comprehensive environmental evaluation on a substation is carried out through investigation and measurement of the current environmental factors, and the statistical data has validated the effectiveness and feasibility of this evaluation index system. The results indicate that the proposed model has high efficiency.

  20. 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...

  1. Modeling entrepreneurial decision-making process using concepts from fuzzy set theory

    OpenAIRE

    Khefacha, Islem; Belkacem, Lotfi

    2015-01-01

    Entrepreneurship and entrepreneurial culture are receiving an increased amount of attention in both academic research and practice. The different fields of study have focused on the analysis of the characteristics of potential entrepreneurs and the firm-creation process. In this paper, we develop and test an economic-psychological model of factors that influence individuals' intentions to go into business. We introduce a new measure of entrepreneurial intention based on the logic fuzzy techni...

  2. Information Processing of Trauma.

    Science.gov (United States)

    Hartman, Carol R.; Burgess, Ann W.

    1993-01-01

    This paper presents a neuropsychosocial model of information processing to explain a victimization experience, specifically child sexual abuse. It surveys the relation of sensation, perception, and cognition as a systematic way to provide a framework for studying human behavior and describing human response to traumatic events. (Author/JDD)

  3. Information services and information processing

    Science.gov (United States)

    1975-01-01

    Attempts made to design and extend space system capabilities are reported. Special attention was given to establishing user needs for information or services which might be provided by space systems. Data given do not attempt to detail scientific, technical, or economic bases for the needs expressed by the users.

  4. Determination of Biological Treatability Processes of Textile Wastewater and Implementation of a Fuzzy Logic Model

    Directory of Open Access Journals (Sweden)

    Harun Akif Kabuk

    2015-01-01

    Full Text Available This study investigated the biological treatability of textile wastewater. For this purpose, a membrane bioreactor (MBR was utilized for biological treatment after the ozonation process. Due to the refractory organic contents of textile wastewater that has a low biodegradability capacity, ozonation was implemented as an advanced oxidation process prior to the MBR system to increase the biodegradability of the wastewater. Textile wastewater, oxidized by ozonation, was fed to the MBR at different hydraulic retention times (HRT. During the process, color, chemical oxygen demand (COD, and biochemical oxygen demand (BOD removal efficiencies were monitored for 24-hour, 12-hour, 6-hour, and 3-hour retention times. Under these conditions, 94% color, 65% COD, and 55% BOD removal efficiencies were obtained in the MBR system. The experimental outputs were modeled with multiple linear regressions (MLR and fuzzy logic. MLR results suggested that color removal is more related to COD removal relative to BOD removal. A surface map of this issue was prepared with a fuzzy logic model. Furthermore, fuzzy logic was employed to the whole modeling of the biological system treatment. Determination coefficients for COD, BOD, and color removal efficiencies were 0.96, 0.97, and 0.92, respectively.

  5. Real-time process signal validation based on neuro-fuzzy and possibilistic approach

    International Nuclear Information System (INIS)

    Figedy, S.; Fantoni, P.F.; Hoffmann, M.

    2001-01-01

    Real-time process signal validation is an application field where the use of fuzzy logic and Artificial Neural Networks can improve the diagnostics of faulty sensors and the identification of outliers in a robust and reliable way. This study implements a fuzzy and possibilistic clustering algorithm to classify the operating region where the validation process is to be performed. The possibilistic approach allows a fast detection of unforeseen plant conditions. Specialized Artificial Neural Networks are used, one for each fuzzy cluster. This offers two main advantages: the accuracy and generalization capability is increased compared to the case of a single network working in the entire operating region, and the ability to identify abnormal conditions, where the system is not capable to operate with a satisfactory accuracy, is improved. This system analyzes the signals, which are e.g. the readings of process monitoring sensors, computes their expected values and alerts if real values are deviated from the expected ones more than limits allow. The reliability level of the current analysis is also produced. This model has been tested on a simulated data from the PWR type of a nuclear power plant, to monitor safety-related reactor variables over the entire power-flow operating map and were installed in real conditions of BWR nuclear reactor. (Authors)

  6. Determining Suitable Places for Saffron Planting Using Fuzzy Hierarchical Analysis Process in the City of Torbat Heydarieh

    Directory of Open Access Journals (Sweden)

    Mahdieh Rashid Sorkhabadi

    2016-01-01

    Full Text Available The city of Torbat Heydarieh located in the central Khorasan is the largest producer of saffron in the world. According to the influence of various environmental factors on the growth and yield of saffron, the process of assessing land ratio for its cultivation requires the use of various detailed spatial and descriptive pieces of information. In this study, first the conditions of cultivating saffron have been studied in detail and suitable regions for planting saffron have been identified using maps of elevation, slope, soil characteristics, water and some climatic factors influencing the cultivation of saffron including effective threshold temperature, rainfall and sunshine hours. For this purpose, Fuzzy Analytical Hierarchy Process (FAHP method was applied and modeling and spatial analysis were carried out using Arc GIS software environment based on the lands of the city of Torbat Heydarieh which were evaluated for their suitability for cultivation of saffron. It is worth noting that the final map showed that 43 percent of the central parts of Torbat Heydarieh have the highest potential for saffron cultivation. To evaluate the results and ensure the accuracy of the final map data, plant functions and crop qualities were compared with obtained data from final maps and the accuracy of the results was confirmed that shows the effectiveness of Fuzzy Analytical Hierarchy Process (FAHP method  in assessing the potential of lands for saffron cultivation.

  7. 区间直觉模糊信息系统中的信息粒度%Information granularity in interval-valued intuitionistic fuzzy information systems

    Institute of Scientific and Technical Information of China (English)

    杨伟萍; 林梦雷

    2012-01-01

    Interval-valued intuitionistic fuzzy information system is able to be more comprehensively, detailedly and visually depict and characterize the decision-making information than the general information system, so reaseaching its research uncertainty is of great importance. With the help of information granularity, this paper characterized the uncertainty of the interval-valued intuitionistic fuzzy information system. It constructed intersection, union, subtraction and complement four operators among granular structures, introduced three new partial order relations in interval-valued intuitionistic fuzzy information systems and established the relationships among them. It defined an interval-valued inluitionistic fuzzy information granularity and an axiomatic approach to interval-valued intuitionistic fuzzy information granularity in interval-valued intuitionistic fuzzy information systems. Finally, it investigated the properties of interval-valued intuitionistic fuzzy information granularity.%区间直觉模糊信息系统比一般信息系统更能全面、细致、直观地描述和刻画决策信息,对其进行不确定性研究具有重要的意义.利用信息粒度对区间直觉模糊信息系统的不确定性进行了刻画,给出了区间直觉模糊粒度结构的交、并、差、补等四种运算.提出了区间直觉模糊粒度结构上的三种偏序关系,并建立了它们之间的联系.定义了区间直觉模糊信息粒度和区间直觉模糊信息粒度的公理化,并研究它们的性质.

  8. Risk management in medical product development process using traditional FMEA and fuzzy linguistic approach: a case study

    Science.gov (United States)

    Kirkire, Milind Shrikant; Rane, Santosh B.; Jadhav, Jagdish Rajaram

    2015-12-01

    Medical product development (MPD) process is highly multidisciplinary in nature, which increases the complexity and the associated risks. Managing the risks during MPD process is very crucial. The objective of this research is to explore risks during MPD in a dental product manufacturing company and propose a model for risk mitigation during MPD process to minimize failure events. A case study approach is employed. The existing MPD process is mapped with five phases of the customized phase gate process. The activities during each phase of development and risks associated with each activity are identified and categorized based on the source of occurrence. The risks are analyzed using traditional Failure mode and effect analysis (FMEA) and fuzzy FMEA. The results of two methods when compared show that fuzzy approach avoids the duplication of RPNs and helps more to convert cognition of experts into information to get values of risk factors. The critical, moderate, low level and negligible risks are identified based on criticality; risk treatments and mitigation model are proposed. During initial phases of MPD, the risks are less severe, but as the process progresses the severity of risks goes on increasing. The MPD process should be critically designed and simulated to minimize the number of risk events and their severity. To successfully develop the products/devices within the manufacturing companies, the process risk management is very essential. A systematic approach to manage risks during MPD process will lead to the development of medical products with expected quality and reliability. This is the first research of its kind having focus on MPD process risks and its management. The methodology adopted in this paper will help the developers, managers and researchers to have a competitive edge over the other companies by managing the risks during the development process.

  9. 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

  10. 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)

  11. Introduction to information processing

    CERN Document Server

    Dietel, Harvey M

    2014-01-01

    An Introduction to Information Processing provides an informal introduction to the computer field. This book introduces computer hardware, which is the actual computing equipment.Organized into three parts encompassing 12 chapters, this book begins with an overview of the evolution of personal computing and includes detailed case studies on two of the most essential personal computers for the 1980s, namely, the IBM Personal Computer and Apple's Macintosh. This text then traces the evolution of modern computing systems from the earliest mechanical calculating devices to microchips. Other chapte

  12. Integrasi Taguchi Loss Function dengan Fuzzy Analytical Hierarchy Process dalam Pemilih Pemasok

    Directory of Open Access Journals (Sweden)

    Ahmad S. Indrapriyatna

    2011-01-01

    Full Text Available One important issue in the line production is the selection of the company's best supplier. Various criteria should be considered for determining the best supplier. Answering to that challenge, we apply Taguchi loss function- Analytical Hierarchy Process Fuzzy-Linear Programming (Taguchi loss function-Fuzzy AHP to find out the best supplier. Moreover, we also consider multiple criteria, i.e., goods’ completeness, quality, delivery, and quality loss in that analysis. By maximizing the suppliers’ performances based on each criterion and aggregated the suppliers’ performances based on the overall criteria, we selected the best one. Applying this method for selecting the best pressure gauge’s supplier in PT. Coca Cola Bottling Indonesia Central Sumatera (PT. CCBICS, we found out that among three suppliers, the second supplier is the best one.

  13. Using fuzzy analytical hierarchy process (AHP to evaluate web development platform

    Directory of Open Access Journals (Sweden)

    Ahmad Sarfaraz

    2012-01-01

    Full Text Available Web development is plays an important role on business plans and people's lives. One of the key decisions in which both short-term and long-term success of the project depends is choosing the right development platform. Its criticality can be judged by the fact that once a platform is chosen, one has to live with it throughout the software development life cycle. The entire shape of the project depends on the language, operating system, tools, frameworks etc., in short the web development platform chosen. In addition, choosing the right platform is a multi criteria decision making (MCDM problem. We propose a fuzzy analytical hierarchy process model to solve the MCDM problem. We try to tap the real-life modeling potential of fuzzy logic and conjugate it with the commonly used powerful AHP modeling method.

  14. Sugeno-Fuzzy Expert System Modeling for Quality Prediction of Non-Contact Machining Process

    Science.gov (United States)

    Sivaraos; Khalim, A. Z.; Salleh, M. S.; Sivakumar, D.; Kadirgama, K.

    2018-03-01

    Modeling can be categorised into four main domains: prediction, optimisation, estimation and calibration. In this paper, the Takagi-Sugeno-Kang (TSK) fuzzy logic method is examined as a prediction modelling method to investigate the taper quality of laser lathing, which seeks to replace traditional lathe machines with 3D laser lathing in order to achieve the desired cylindrical shape of stock materials. Three design parameters were selected: feed rate, cutting speed and depth of cut. A total of twenty-four experiments were conducted with eight sequential runs and replicated three times. The results were found to be 99% of accuracy rate of the TSK fuzzy predictive model, which suggests that the model is a suitable and practical method for non-linear laser lathing process.

  15. Information processing for aerospace structural health monitoring

    Science.gov (United States)

    Lichtenwalner, Peter F.; White, Edward V.; Baumann, Erwin W.

    1998-06-01

    Structural health monitoring (SHM) technology provides a means to significantly reduce life cycle of aerospace vehicles by eliminating unnecessary inspections, minimizing inspection complexity, and providing accurate diagnostics and prognostics to support vehicle life extension. In order to accomplish this, a comprehensive SHM system will need to acquire data from a wide variety of diverse sensors including strain gages, accelerometers, acoustic emission sensors, crack growth gages, corrosion sensors, and piezoelectric transducers. Significant amounts of computer processing will then be required to convert this raw sensor data into meaningful information which indicates both the diagnostics of the current structural integrity as well as the prognostics necessary for planning and managing the future health of the structure in a cost effective manner. This paper provides a description of the key types of information processing technologies required in an effective SHM system. These include artificial intelligence techniques such as neural networks, expert systems, and fuzzy logic for nonlinear modeling, pattern recognition, and complex decision making; signal processing techniques such as Fourier and wavelet transforms for spectral analysis and feature extraction; statistical algorithms for optimal detection, estimation, prediction, and fusion; and a wide variety of other algorithms for data analysis and visualization. The intent of this paper is to provide an overview of the role of information processing for SHM, discuss various technologies which can contribute to accomplishing this role, and present some example applications of information processing for SHM implemented at the Boeing Company.

  16. Model of cholera dissemination using geographic information systems and fuzzy clustering means: case study, Chabahar, Iran.

    Science.gov (United States)

    Pezeshki, Z; Tafazzoli-Shadpour, M; Mansourian, A; Eshrati, B; Omidi, E; Nejadqoli, I

    2012-10-01

    Cholera is spread by drinking water or eating food that is contaminated by bacteria, and is related to climate changes. Several epidemics have occurred in Iran, the most recent of which was in 2005 with 1133 cases and 12 deaths. This study investigated the incidence of cholera over a 10-year period in Chabahar district, a region with one of the highest incidence rates of cholera in Iran. Descriptive retrospective study on data of patients with Eltor and NAG cholera reported to the Iranian Centre of Disease Control between 1997 and 2006. Data on the prevalence of cholera were gathered through a surveillance system, and a spatial database was developed using geographic information systems (GIS) to describe the relation of spatial and climate variables to cholera incidences. Fuzzy clustering (fuzzy C) method and statistical analysis based on logistic regression were used to develop a model of cholera dissemination. The variables were demographic characteristics, specifications of cholera infection, climate conditions and some geographical parameters. The incidence of cholera was found to be significantly related to higher temperature and humidity, lower precipitation, shorter distance to the eastern border of Iran and local health centres, and longer distance to the district health centre. The fuzzy C means algorithm showed that clusters were geographically distributed in distinct regions. In order to plan, manage and monitor any public health programme, GIS provide ideal platforms for the convergence of disease-specific information, analysis and computation of new data for statistical analysis. Copyright © 2012 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

  17. 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

  18. 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

  19. Influence of the Migration Process on the Learning Performances of Fuzzy Knowledge Bases

    DEFF Research Database (Denmark)

    Akrout, Khaled; Baron, Luc; Balazinski, Marek

    2007-01-01

    This paper presents the influence of the process of migration between populations in GENO-FLOU, which is an environment of learning of fuzzy knowledge bases by genetic algorithms. Initially the algorithm did not use the process of migration. For the learning, the algorithm uses a hybrid coding......, binary for the base of rules and real for the data base. This hybrid coding used with a set of specialized operators of reproduction proven to be an effective environment of learning. Simulations were made in this environment by adding a process of migration. While varying the number of populations...

  20. 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...

  1. Fuzzy logic for plant-wide control of biological wastewater treatment process including greenhouse gas emissions.

    Science.gov (United States)

    Santín, I; Barbu, M; Pedret, C; Vilanova, R

    2018-06-01

    The application of control strategies is increasingly used in wastewater treatment plants with the aim of improving effluent quality and reducing operating costs. Due to concerns about the progressive growth of greenhouse gas emissions (GHG), these are also currently being evaluated in wastewater treatment plants. The present article proposes a fuzzy controller for plant-wide control of the biological wastewater treatment process. Its design is based on 14 inputs and 6 outputs in order to reduce GHG emissions, nutrient concentration in the effluent and operational costs. The article explains and shows the effect of each one of the inputs and outputs of the fuzzy controller, as well as the relationship between them. Benchmark Simulation Model no 2 Gas is used for testing the proposed control strategy. The results of simulation results show that the fuzzy controller is able to reduce GHG emissions while improving, at the same time, the common criteria of effluent quality and operational costs. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  2. Information-processing genes

    International Nuclear Information System (INIS)

    Tahir Shah, K.

    1995-01-01

    There are an estimated 100,000 genes in the human genome of which 97% is non-coding. On the other hand, bacteria have little or no non-coding DNA. Non-coding region includes introns, ALU sequences, satellite DNA, and other segments not expressed as proteins. Why it exists? Why nature has kept non-coding during the long evolutionary period if it has no role in the development of complex life forms? Does complexity of a species somehow correlated to the existence of apparently useless sequences? What kind of capability is encoded within such nucleotide sequences that is a necessary, but not a sufficient condition for the evolution of complex life forms, keeping in mind the C-value paradox and the omnipresence of non-coding segments in higher eurkaryotes and also in many archea and prokaryotes. The physico-chemical description of biological processes is hardware oriented and does not highlight algorithmic or information processing aspect. However, an algorithm without its hardware implementation is useless as much as hardware without its capability to run an algorithm. The nature and type of computation an information-processing hardware can perform depends only on its algorithm and the architecture that reflects the algorithm. Given that enormously difficult tasks such as high fidelity replication, transcription, editing and regulation are all achieved within a long linear sequence, it is natural to think that some parts of a genome are involved is these tasks. If some complex algorithms are encoded with these parts, then it is natural to think that non-coding regions contain processing-information algorithms. A comparison between well-known automatic sequences and sequences constructed out of motifs is found in all species proves the point: noncoding regions are a sort of ''hardwired'' programs, i.e., they are linear representations of information-processing machines. Thus in our model, a noncoding region, e.g., an intron contains a program (or equivalently, it is

  3. Fair fund distribution for a municipal incinerator using GIS-based fuzzy analytic hierarchy process.

    Science.gov (United States)

    Chang, Ni-Bin; Chang, Ying-Hsi; Chen, Ho-Wen

    2009-01-01

    Burning municipal solid waste (MSW) can generate energy and reduce the waste volume, which delivers benefits to society through resources conservation. But current practices by society are not sustainable because the associated environmental impacts of waste incineration on urbanized regions have been a long-standing concern in local communities. Public reluctance with regard to accepting the incinerators as typical utilities often results in an intensive debate concerning how much welfare is lost for those residents living in the vicinity of those incinerators. As the measure of welfare change with respect to environmental quality constraints nearby these incinerators remains critical, new arguments related to how to allocate the fair fund among affected communities became a focal point in environmental management. Given the fact that most County fair fund rules allow a great deal of flexibility for redistribution, little is known about what type of methodology may be a good fit to determine the distribution of such a fair fund under uncertainty. This paper purports to demonstrate a system-based approach that helps any fair fund distribution, which is made with respect to residents' possible claim for fair damages due to the installation of a new incinerator. Holding a case study using integrated geographic information system (GIS) and fuzzy analytic hierarchy process (FAHP) for finding out the most appropriate distribution strategy between two neighboring towns in Taipei County, Taiwan demonstrates the application potential. Participants in determining the use of a fair fund also follow a highly democratic procedure where all stakeholders involved eventually express a high level of satisfaction with the results facilitating the final decision making process. It ensures that plans for the distribution of such a fair fund were carefully thought out and justified with a multi-faceted nature that covers political, socio-economic, technical, environmental, public

  4. Fuzzy Risk Evaluation in Failure Mode and Effects Analysis Using a D Numbers Based Multi-Sensor Information Fusion Method.

    Science.gov (United States)

    Deng, Xinyang; Jiang, Wen

    2017-09-12

    Failure mode and effect analysis (FMEA) is a useful tool to define, identify, and eliminate potential failures or errors so as to improve the reliability of systems, designs, and products. Risk evaluation is an important issue in FMEA to determine the risk priorities of failure modes. There are some shortcomings in the traditional risk priority number (RPN) approach for risk evaluation in FMEA, and fuzzy risk evaluation has become an important research direction that attracts increasing attention. In this paper, the fuzzy risk evaluation in FMEA is studied from a perspective of multi-sensor information fusion. By considering the non-exclusiveness between the evaluations of fuzzy linguistic variables to failure modes, a novel model called D numbers is used to model the non-exclusive fuzzy evaluations. A D numbers based multi-sensor information fusion method is proposed to establish a new model for fuzzy risk evaluation in FMEA. An illustrative example is provided and examined using the proposed model and other existing method to show the effectiveness of the proposed model.

  5. Application of fuzzy C-Means Algorithm for Determining Field of Interest in Information System Study STTH Medan

    Science.gov (United States)

    Rahman Syahputra, Edy; Agustina Dalimunthe, Yulia; Irvan

    2017-12-01

    Many students are confused in choosing their own field of specialization, ultimately choosing areas of specialization that are incompatible with a variety of reasons such as just following a friend or because of the area of interest of many choices without knowing whether they have Competencies in the chosen field of interest. This research aims to apply Clustering method with Fuzzy C-means algorithm to classify students in the chosen interest field. The Fuzzy C-Means algorithm is one of the easiest and often used algorithms in data grouping techniques because it makes efficient estimates and does not require many parameters. Several studies have led to the conclusion that the Fuzzy C-Means algorithm can be used to group data based on certain attributes. In this research will be used Fuzzy C-Means algorithm to classify student data based on the value of core subjects in the selection of specialization field. This study also tested the accuracy of the Fuzzy C-Means algorithm in the determination of interest area. The study was conducted on the STT-Harapan Medan Information System Study program, and the object of research is the value of all students of STT-Harapan Medan Information System Study Program 2012. From this research, it is expected to get the specialization field, according to the students' ability based on the prerequisite principal value.

  6. Photonic Quantum Information Processing

    International Nuclear Information System (INIS)

    Walther, P.

    2012-01-01

    The advantage of the photon's mobility makes optical quantum system ideally suited for delegated quantum computation. I will present results for the realization for a measurement-based quantum network in a client-server environment, where quantum information is securely communicated and computed. Related to measurement-based quantum computing I will discuss a recent experiment showing that quantum discord can be used as resource for the remote state preparation, which might shine new light on the requirements for quantum-enhanced information processing. Finally, I will briefly review recent photonic quantum simulation experiments of four frustrated Heisenberg-interactions spins and present an outlook of feasible simulation experiments with more complex interactions or random walk structures. As outlook I will discuss the current status of new quantum technology for improving the scalability of photonic quantum systems by using superconducting single-photon detectors and tailored light-matter interactions. (author)

  7. Fuzzy analytical hierarchy process and GIS for predictive cu -au ...

    African Journals Online (AJOL)

    If you would like more information about how to print, save, and work with PDFs, Highwire Press provides a helpful Frequently Asked Questions about PDFs. Alternatively, you can download the PDF file directly to your computer, from where it can be opened using a PDF reader. To download the PDF, click the Download link ...

  8. Decision making using AHP (Analytic Hierarchy Process) and fuzzy set theory in waste management

    International Nuclear Information System (INIS)

    Chung, J.Y.; Lee, K.J.; Kim, C.D.

    1995-01-01

    The major problem is how to consider the differences in opinions, when many experts are involved in decision making process. This paper provides a simple general methodology to treat the differences in various opinions. The authors determined the grade of membership through the process of magnitude estimation derived from pairwise comparisons and AHP developed by Saaty. They used fuzzy set theory to consider the differences in opinions and obtain the priorities for each alternative. An example, which can be applied to radioactive waste management, also was presented. The result shows a good agreement with the results of averaging methods

  9. Advanced information processing system

    Science.gov (United States)

    Lala, J. H.

    1984-01-01

    Design and performance details of the advanced information processing system (AIPS) for fault and damage tolerant data processing on aircraft and spacecraft are presented. AIPS comprises several computers distributed throughout the vehicle and linked by a damage tolerant data bus. Most I/O functions are available to all the computers, which run in a TDMA mode. Each computer performs separate specific tasks in normal operation and assumes other tasks in degraded modes. Redundant software assures that all fault monitoring, logging and reporting are automated, together with control functions. Redundant duplex links and damage-spread limitation provide the fault tolerance. Details of an advanced design of a laboratory-scale proof-of-concept system are described, including functional operations.

  10. A biological inspired fuzzy adaptive window median filter (FAWMF) for enhancing DNA signal processing.

    Science.gov (United States)

    Ahmad, Muneer; Jung, Low Tan; Bhuiyan, Al-Amin

    2017-10-01

    Digital signal processing techniques commonly employ fixed length window filters to process the signal contents. DNA signals differ in characteristics from common digital signals since they carry nucleotides as contents. The nucleotides own genetic code context and fuzzy behaviors due to their special structure and order in DNA strand. Employing conventional fixed length window filters for DNA signal processing produce spectral leakage and hence results in signal noise. A biological context aware adaptive window filter is required to process the DNA signals. This paper introduces a biological inspired fuzzy adaptive window median filter (FAWMF) which computes the fuzzy membership strength of nucleotides in each slide of window and filters nucleotides based on median filtering with a combination of s-shaped and z-shaped filters. Since coding regions cause 3-base periodicity by an unbalanced nucleotides' distribution producing a relatively high bias for nucleotides' usage, such fundamental characteristic of nucleotides has been exploited in FAWMF to suppress the signal noise. Along with adaptive response of FAWMF, a strong correlation between median nucleotides and the Π shaped filter was observed which produced enhanced discrimination between coding and non-coding regions contrary to fixed length conventional window filters. The proposed FAWMF attains a significant enhancement in coding regions identification i.e. 40% to 125% as compared to other conventional window filters tested over more than 250 benchmarked and randomly taken DNA datasets of different organisms. This study proves that conventional fixed length window filters applied to DNA signals do not achieve significant results since the nucleotides carry genetic code context. The proposed FAWMF algorithm is adaptive and outperforms significantly to process DNA signal contents. The algorithm applied to variety of DNA datasets produced noteworthy discrimination between coding and non-coding regions contrary

  11. 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

  12. Simulation of Plant Physiological Process Using Fuzzy Variables

    Science.gov (United States)

    Daniel L. Schmoldt

    1991-01-01

    Qualitative modelling can help us understand and project effects of multiple stresses on trees. It is not practical to collect and correlate empirical data for all combinations of plant/environments and human/climate stresses, especially for mature trees in natural settings. Therefore, a mechanistic model was developed to describe ecophysiological processes. This model...

  13. Prioritization of watersheds in order to perform administrative measures using fuzzy analytic hierarchy process

    Directory of Open Access Journals (Sweden)

    Seyyed Abdolhossein Arami

    2017-01-01

    Full Text Available Prioritization of watersheds in order to perform administrative measures is necessary and inevitable. Determining areas of top priority for flood control projects is a managerial decision that should be approved by studies of physical, social and economic status of the region of interesrt and by assessing the outcomes of the past operations. Therefore, the aim of this research was to study morphological and physiographic characteristics, and to use geographic information systems (GIS and multi-criteria decision-making methods (MCDM, to identify the critical sub-basins which have the tendency to be destructed, in Galikesh watershed, Golestan province. This watershed is important, yet critical, in terms of land use change, erosion and flooding in the Golestan Province, Iran. In total, nine morphological parameters were used to prioritize sub-watersheds using fuzzy analytic hierarchy process (FAHP. The morphological parameters were by some means linked to watershed drainage system. Based on FAHP approach, sub-basins, as vulnerable zones, have been evaluated and cetegorized in five priority levels (very low, low, medium, high and very high levels. The results showed that 44.44% and 22.22% of sub-basins were categorized respectively under average, and high to very high levels, suggesting that the conservation and management measures are essential in order to maintain stability in the region. Thus, the FAHP technique is a practical and convenient method to show potential zones in order to implement effective management strategies, especially in areas where data availability is low and soil diversity is high. Finally, it can be said that without having to encounter high costs and a waste of time, sub-basins could be categorized by means of morphometric parameters in order to implement conservational measures to simutaneously conserve soil and the environment

  14. An Intelligent Complex Event Processing with D Numbers under Fuzzy Environment

    Directory of Open Access Journals (Sweden)

    Fuyuan Xiao

    2016-01-01

    Full Text Available Efficient matching of incoming mass events to persistent queries is fundamental to complex event processing systems. Event matching based on pattern rule is an important feature of complex event processing engine. However, the intrinsic uncertainty in pattern rules which are predecided by experts increases the difficulties of effective complex event processing. It inevitably involves various types of the intrinsic uncertainty, such as imprecision, fuzziness, and incompleteness, due to the inability of human beings subjective judgment. Nevertheless, D numbers is a new mathematic tool to model uncertainty, since it ignores the condition that elements on the frame must be mutually exclusive. To address the above issues, an intelligent complex event processing method with D numbers under fuzzy environment is proposed based on the Technique for Order Preferences by Similarity to an Ideal Solution (TOPSIS method. The novel method can fully support decision making in complex event processing systems. Finally, a numerical example is provided to evaluate the efficiency of the proposed method.

  15. Soft Sensor Modeling Based on Multiple Gaussian Process Regression and Fuzzy C-mean Clustering

    Directory of Open Access Journals (Sweden)

    Xianglin ZHU

    2014-06-01

    Full Text Available In order to overcome the difficulties of online measurement of some crucial biochemical variables in fermentation processes, a new soft sensor modeling method is presented based on the Gaussian process regression and fuzzy C-mean clustering. With the consideration that the typical fermentation process can be distributed into 4 phases including lag phase, exponential growth phase, stable phase and dead phase, the training samples are classified into 4 subcategories by using fuzzy C- mean clustering algorithm. For each sub-category, the samples are trained using the Gaussian process regression and the corresponding soft-sensing sub-model is established respectively. For a new sample, the membership between this sample and sub-models are computed based on the Euclidean distance, and then the prediction output of soft sensor is obtained using the weighting sum. Taking the Lysine fermentation as example, the simulation and experiment are carried out and the corresponding results show that the presented method achieves better fitting and generalization ability than radial basis function neutral network and single Gaussian process regression model.

  16. Fuzzy Genetic Algorithm Based on Principal Operation and Inequity Degree

    Science.gov (United States)

    Li, Fachao; Jin, Chenxia

    In this paper, starting from the structure of fuzzy information, by distinguishing principal indexes and assistant indexes, give comparison of fuzzy information on synthesizing effect and operation of fuzzy optimization on principal indexes transformation, further, propose axiom system of fuzzy inequity degree from essence of constraint, and give an instructive metric method; Then, combining genetic algorithm, give fuzzy optimization methods based on principal operation and inequity degree (denoted by BPO&ID-FGA, for short); Finally, consider its convergence using Markov chain theory and analyze its performance through an example. All these indicate, BPO&ID-FGA can not only effectively merge decision consciousness into the optimization process, but possess better global convergence, so it can be applied to many fuzzy optimization problems.

  17. Weather Information Processing

    Science.gov (United States)

    1991-01-01

    Science Communications International (SCI), formerly General Science Corporation, has developed several commercial products based upon experience acquired as a NASA Contractor. Among them are METPRO, a meteorological data acquisition and processing system, which has been widely used, RISKPRO, an environmental assessment system, and MAPPRO, a geographic information system. METPRO software is used to collect weather data from satellites, ground-based observation systems and radio weather broadcasts to generate weather maps, enabling potential disaster areas to receive advance warning. GSC's initial work for NASA Goddard Space Flight Center resulted in METPAK, a weather satellite data analysis system. METPAK led to the commercial METPRO system. The company also provides data to other government agencies, U.S. embassies and foreign countries.

  18. Fuzzy logic applications in engineering science

    CERN Document Server

    Harris, J

    2006-01-01

    Fuzzy logic is a relatively new concept in science applications. Hitherto, fuzzy logic has been a conceptual process applied in the field of risk management. Its potential applicability is much wider than that, however, and its particular suitability for expanding our understanding of processes and information in science and engineering in our post-modern world is only just beginning to be appreciated. Written as a companion text to the author's earlier volume "An Introduction to Fuzzy Logic Applications", the book is aimed at professional engineers and students and those with an interest in exploring the potential of fuzzy logic as an information processing kit with a wide variety of practical applications in the field of engineering science and develops themes and topics introduced in the author's earlier text.

  19. On the analytic hierarchy process and decision support based on fuzzy-linguistic preference structures

    DEFF Research Database (Denmark)

    Franco de los Rios, Camilo Andres

    2014-01-01

    , where experts value pairs of alternatives/criteria with words, making it essentially fuzzy under the view that words can be represented by fuzzy sets for their respective computation. Hence, reasoning with fuzzy logic is justified by the analytical framework that it offers to design the meaning of words...

  20. Dual Processes in Decision Making and Developmental Neuroscience: A Fuzzy-Trace Model.

    Science.gov (United States)

    Reyna, Valerie F; Brainerd, Charles J

    2011-09-01

    From Piaget to the present, traditional and dual-process theories have predicted improvement in reasoning from childhood to adulthood, and improvement has been observed. However, developmental reversals-that reasoning biases emerge with development -have also been observed in a growing list of paradigms. We explain how fuzzy-trace theory predicts both improvement and developmental reversals in reasoning and decision making. Drawing on research on logical and quantitative reasoning, as well as on risky decision making in the laboratory and in life, we illustrate how the same small set of theoretical principles apply to typical neurodevelopment, encompassing childhood, adolescence, and adulthood, and to neurological conditions such as autism and Alzheimer's disease. For example, framing effects-that risk preferences shift when the same decisions are phrases in terms of gains versus losses-emerge in early adolescence as gist-based intuition develops. In autistic individuals, who rely less on gist-based intuition and more on verbatim-based analysis, framing biases are attenuated (i.e., they outperform typically developing control subjects). In adults, simple manipulations based on fuzzy-trace theory can make framing effects appear and disappear depending on whether gist-based intuition or verbatim-based analysis is induced. These theoretical principles are summarized and integrated in a new mathematical model that specifies how dual modes of reasoning combine to produce predictable variability in performance. In particular, we show how the most popular and extensively studied model of decision making-prospect theory-can be derived from fuzzy-trace theory by combining analytical (verbatim-based) and intuitive (gist-based) processes.

  1. Dual Processes in Decision Making and Developmental Neuroscience: A Fuzzy-Trace Model

    Science.gov (United States)

    Reyna, Valerie F.; Brainerd, Charles J.

    2011-01-01

    From Piaget to the present, traditional and dual-process theories have predicted improvement in reasoning from childhood to adulthood, and improvement has been observed. However, developmental reversals—that reasoning biases emerge with development —have also been observed in a growing list of paradigms. We explain how fuzzy-trace theory predicts both improvement and developmental reversals in reasoning and decision making. Drawing on research on logical and quantitative reasoning, as well as on risky decision making in the laboratory and in life, we illustrate how the same small set of theoretical principles apply to typical neurodevelopment, encompassing childhood, adolescence, and adulthood, and to neurological conditions such as autism and Alzheimer's disease. For example, framing effects—that risk preferences shift when the same decisions are phrases in terms of gains versus losses—emerge in early adolescence as gist-based intuition develops. In autistic individuals, who rely less on gist-based intuition and more on verbatim-based analysis, framing biases are attenuated (i.e., they outperform typically developing control subjects). In adults, simple manipulations based on fuzzy-trace theory can make framing effects appear and disappear depending on whether gist-based intuition or verbatim-based analysis is induced. These theoretical principles are summarized and integrated in a new mathematical model that specifies how dual modes of reasoning combine to produce predictable variability in performance. In particular, we show how the most popular and extensively studied model of decision making—prospect theory—can be derived from fuzzy-trace theory by combining analytical (verbatim-based) and intuitive (gist-based) processes. PMID:22096268

  2. Automatic screening and classification of diabetic retinopathy and maculopathy using fuzzy image processing.

    Science.gov (United States)

    Rahim, Sarni Suhaila; Palade, Vasile; Shuttleworth, James; Jayne, Chrisina

    2016-12-01

    Digital retinal imaging is a challenging screening method for which effective, robust and cost-effective approaches are still to be developed. Regular screening for diabetic retinopathy and diabetic maculopathy diseases is necessary in order to identify the group at risk of visual impairment. This paper presents a novel automatic detection of diabetic retinopathy and maculopathy in eye fundus images by employing fuzzy image processing techniques. The paper first introduces the existing systems for diabetic retinopathy screening, with an emphasis on the maculopathy detection methods. The proposed medical decision support system consists of four parts, namely: image acquisition, image preprocessing including four retinal structures localisation, feature extraction and the classification of diabetic retinopathy and maculopathy. A combination of fuzzy image processing techniques, the Circular Hough Transform and several feature extraction methods are implemented in the proposed system. The paper also presents a novel technique for the macula region localisation in order to detect the maculopathy. In addition to the proposed detection system, the paper highlights a novel online dataset and it presents the dataset collection, the expert diagnosis process and the advantages of our online database compared to other public eye fundus image databases for diabetic retinopathy purposes.

  3. An Improved Version of Discrete Particle Swarm Optimization for Flexible Job Shop Scheduling Problem with Fuzzy Processing Time

    Directory of Open Access Journals (Sweden)

    Song Huang

    2016-01-01

    Full Text Available The fuzzy processing time occasionally exists in job shop scheduling problem of flexible manufacturing system. To deal with fuzzy processing time, fuzzy flexible job shop model was established in several papers and has attracted numerous researchers’ attention recently. In our research, an improved version of discrete particle swarm optimization (IDPSO is designed to solve flexible job shop scheduling problem with fuzzy processing time (FJSPF. In IDPSO, heuristic initial methods based on triangular fuzzy number are developed, and a combination of six initial methods is applied to initialize machine assignment and random method is used to initialize operation sequence. Then, some simple and effective discrete operators are employed to update particle’s position and generate new particles. In order to guide the particles effectively, we extend global best position to a set with several global best positions. Finally, experiments are designed to investigate the impact of four parameters in IDPSO by Taguchi method, and IDPSO is tested on five instances and compared with some state-of-the-art algorithms. The experimental results show that the proposed algorithm can obtain better solutions for FJSPF and is more competitive than the compared algorithms.

  4. Structuring heterogeneous biological information using fuzzy clustering of k-partite graphs

    Directory of Open Access Journals (Sweden)

    Theis Fabian J

    2010-10-01

    Full Text Available Abstract Background Extensive and automated data integration in bioinformatics facilitates the construction of large, complex biological networks. However, the challenge lies in the interpretation of these networks. While most research focuses on the unipartite or bipartite case, we address the more general but common situation of k-partite graphs. These graphs contain k different node types and links are only allowed between nodes of different types. In order to reveal their structural organization and describe the contained information in a more coarse-grained fashion, we ask how to detect clusters within each node type. Results Since entities in biological networks regularly have more than one function and hence participate in more than one cluster, we developed a k-partite graph partitioning algorithm that allows for overlapping (fuzzy clusters. It determines for each node a degree of membership to each cluster. Moreover, the algorithm estimates a weighted k-partite graph that connects the extracted clusters. Our method is fast and efficient, mimicking the multiplicative update rules commonly employed in algorithms for non-negative matrix factorization. It facilitates the decomposition of networks on a chosen scale and therefore allows for analysis and interpretation of structures on various resolution levels. Applying our algorithm to a tripartite disease-gene-protein complex network, we were able to structure this graph on a large scale into clusters that are functionally correlated and biologically meaningful. Locally, smaller clusters enabled reclassification or annotation of the clusters' elements. We exemplified this for the transcription factor MECP2. Conclusions In order to cope with the overwhelming amount of information available from biomedical literature, we need to tackle the challenge of finding structures in large networks with nodes of multiple types. To this end, we presented a novel fuzzy k-partite graph partitioning

  5. Assessing safety risk in electricity distribution processes using ET & BA improved technique and its ranking by VIKOR and TOPSIS models in fuzzy environment

    OpenAIRE

    S. Rahmani; M. Omidvari

    2016-01-01

    Introduction: Electrical industries are among high risk industries. The present study aimed to assess safety risk in electricity distribution processes using  ET&BA technique and also to compare with both VIKOR & TOPSIS methods in fuzzy environments.   Material and Methods: The present research is a descriptive study and ET&BA worksheet is the main data collection tool. Both Fuzzy TOPSIS and Fuzzy VIKOR methods were used for the worksheet analysis.   Result: Findi...

  6. Ecological Vulnerability Assessment Based on Fuzzy Analytical Method and Analytic Hierarchy Process in Yellow River Delta.

    Science.gov (United States)

    Wu, Chunsheng; Liu, Gaohuan; Huang, Chong; Liu, Qingsheng; Guan, Xudong

    2018-04-25

    The Yellow River Delta (YRD), located in Yellow River estuary, is characterized by rich ecological system types, and provides habitats or migration stations for wild birds, all of which makes the delta an ecological barrier or ecotone for inland areas. Nevertheless, the abundant natural resources of YRD have brought huge challenges to the area, and frequent human activities and natural disasters have damaged the ecological systems seriously, and certain ecological functions have been threatened. Therefore, it is necessary to determine the status of the ecological environment based on scientific methods, which can provide scientifically robust data for the managers or stakeholders to adopt timely ecological protection measures. The aim of this study was to obtain the spatial distribution of the ecological vulnerability (EV) in YRD based on 21 indicators selected from underwater status, soil condition, land use, landform, vegetation cover, meteorological conditions, ocean influence, and social economy. In addition, the fuzzy analytic hierarchy process (FAHP) method was used to obtain the weights of the selected indicators, and a fuzzy logic model was constructed to obtain the result. The result showed that the spatial distribution of the EV grades was regular, while the fuzzy membership of EV decreased gradually from the coastline to inland area, especially around the river crossing, where it had the lowest EV. Along the coastline, the dikes had an obviously protective effect for the inner area, while the EV was higher in the area where no dikes were built. This result also showed that the soil condition and groundwater status were highly related to the EV spatially, with the correlation coefficients −0.55 and −0.74 respectively, and human activities had exerted considerable pressure on the ecological environment.

  7. Mamdani-Fuzzy Modeling Approach for Quality Prediction of Non-Linear Laser Lathing Process

    Science.gov (United States)

    Sivaraos; Khalim, A. Z.; Salleh, M. S.; Sivakumar, D.; Kadirgama, K.

    2018-03-01

    Lathing is a process to fashioning stock materials into desired cylindrical shapes which usually performed by traditional lathe machine. But, the recent rapid advancements in engineering materials and precision demand gives a great challenge to the traditional method. The main drawback of conventional lathe is its mechanical contact which brings to the undesirable tool wear, heat affected zone, finishing, and dimensional accuracy especially taper quality in machining of stock with high length to diameter ratio. Therefore, a novel approach has been devised to investigate in transforming a 2D flatbed CO2 laser cutting machine into 3D laser lathing capability as an alternative solution. Three significant design parameters were selected for this experiment, namely cutting speed, spinning speed, and depth of cut. Total of 24 experiments were performed with eight (8) sequential runs where they were then replicated three (3) times. The experimental results were then used to establish Mamdani - Fuzzy predictive model where it yields the accuracy of more than 95%. Thus, the proposed Mamdani - Fuzzy modelling approach is found very much suitable and practical for quality prediction of non-linear laser lathing process for cylindrical stocks of 10mm diameter.

  8. Performance comparison of optimal fractional order hybrid fuzzy PID controllers for handling oscillatory fractional order processes with dead time.

    Science.gov (United States)

    Das, Saptarshi; Pan, Indranil; Das, Shantanu

    2013-07-01

    Fuzzy logic based PID controllers have been studied in this paper, considering several combinations of hybrid controllers by grouping the proportional, integral and derivative actions with fuzzy inferencing in different forms. Fractional order (FO) rate of error signal and FO integral of control signal have been used in the design of a family of decomposed hybrid FO fuzzy PID controllers. The input and output scaling factors (SF) along with the integro-differential operators are tuned with real coded genetic algorithm (GA) to produce optimum closed loop performance by simultaneous consideration of the control loop error index and the control signal. Three different classes of fractional order oscillatory processes with various levels of relative dominance between time constant and time delay have been used to test the comparative merits of the proposed family of hybrid fractional order fuzzy PID controllers. Performance comparison of the different FO fuzzy PID controller structures has been done in terms of optimal set-point tracking, load disturbance rejection and minimal variation of manipulated variable or smaller actuator requirement etc. In addition, multi-objective Non-dominated Sorting Genetic Algorithm (NSGA-II) has been used to study the Pareto optimal trade-offs between the set point tracking and control signal, and the set point tracking and load disturbance performance for each of the controller structure to handle the three different types of processes. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  9. "Fuzzy stuff"

    DEFF Research Database (Denmark)

    Christensen, Line Hjorth

    "Fuzzy stuff". Exploring the displacement of the design sketch. What kind of knowledge can historical sketches reveal when they have outplayed their primary instrumental function in the design process and are moved into a museum collection? What are the rational benefits of ‘archival displacement...

  10. Chebyshev polynomial functions based locally recurrent neuro-fuzzy information system for prediction of financial and energy market data

    Directory of Open Access Journals (Sweden)

    A.K. Parida

    2016-09-01

    Full Text Available In this paper Chebyshev polynomial functions based locally recurrent neuro-fuzzy information system is presented for the prediction and analysis of financial and electrical energy market data. The normally used TSK-type feedforward fuzzy neural network is unable to take the full advantage of the use of the linear fuzzy rule base in accurate input–output mapping and hence the consequent part of the rule base is made nonlinear using polynomial or arithmetic basis functions. Further the Chebyshev polynomial functions provide an expanded nonlinear transformation to the input space thereby increasing its dimension for capturing the nonlinearities and chaotic variations in financial or energy market data streams. Also the locally recurrent neuro-fuzzy information system (LRNFIS includes feedback loops both at the firing strength layer and the output layer to allow signal flow both in forward and backward directions, thereby making the LRNFIS mimic a dynamic system that provides fast convergence and accuracy in predicting time series fluctuations. Instead of using forward and backward least mean square (FBLMS learning algorithm, an improved Firefly-Harmony search (IFFHS learning algorithm is used to estimate the parameters of the consequent part and feedback loop parameters for better stability and convergence. Several real world financial and energy market time series databases are used for performance validation of the proposed LRNFIS model.

  11. Prioritizing the barriers to achieve sustainable consumption and production trends in supply chains using fuzzy Analytical Hierarchy Process

    DEFF Research Database (Denmark)

    Mangla, Sachin Kumar; Govindan, Kannan; Luthra, Sunil

    2017-01-01

    Currently, production systems and consumption patterns are based on conventional courses of action and utilize methods and technologies that are generally not sustainable. As a result, Sustainable Consumption and Production (SCP) is becoming an important means by which business organizations...... and production trends in a supply chain context. In this work, firstly, 30 barriers related to implementing SCP trends in supply chain are recognized. These barriers are derived from a literature survey and from field and industrial experts' inputs. Secondly, an operational model is suggested using the fuzzy...... Analytical Hierarchy Process to prioritize the identified barriers with the goal of improving overall performance. The fuzzy Analytical Hierarchy Process helps determine the priority of concerns of the identified barriers under fuzzy surroundings. Inputs in this work are based upon an ancillary auto...

  12. Parameterization of a fuzzy classifier for the diagnosis of an industrial process

    International Nuclear Information System (INIS)

    Toscano, R.; Lyonnet, P.

    2002-01-01

    The aim of this paper is to present a classifier based on a fuzzy inference system. For this classifier, we propose a parameterization method, which is not necessarily based on an iterative training. This approach can be seen as a pre-parameterization, which allows the determination of the rules base and the parameters of the membership functions. We also present a continuous and derivable version of the previous classifier and suggest an iterative learning algorithm based on a gradient method. An example using the learning basis IRIS, which is a benchmark for classification problems, is presented showing the performances of this classifier. Finally this classifier is applied to the diagnosis of a DC motor showing the utility of this method. However in many cases the total knowledge necessary to the synthesis of the fuzzy diagnosis system (FDS) is not, in general, directly available. It must be extracted from an often-considerable mass of information. For this reason, a general methodology for the design of a FDS is presented and illustrated on a non-linear plant

  13. 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.

  14. Fuzzy logic and information fusion to commemorate the 70th birthday of Professor Gaspar Mayor

    CERN Document Server

    Sastre, Joan

    2016-01-01

    This book offers a timely report on key theories and applications of soft-computing. Written in honour of Professor Gaspar Mayor on his 70th birthday, it primarily focuses on areas related to his research, including fuzzy binary operators, aggregation functions, multi-distances, and fuzzy consensus/decision models. It also discusses a number of interesting applications such as the implementation of fuzzy mathematical morphology based on Mayor-Torrens t-norms. Importantly, the different chapters, authored by leading experts, present novel results and offer new perspectives on different aspects of Mayor’s research. The book also includes an overview of evolutionary fuzzy systems, a topic that is not one of Mayor’s main areas of interest, and a final chapter written by the Spanish pioneer in fuzzy logic, Professor E. Trillas. Computer and decision scientists, knowledge engineers and mathematicians alike will find here an authoritative overview of key soft-computing concepts and techniques.

  15. Smart Spectrometer for Distributed Fuzzy Control

    OpenAIRE

    Benoit, Eric; Foulloy, Laurent

    2009-01-01

    Document rédigé sous FrameMaker (pas sous Latex); International audience; If the main use of colour measurement is the metrology, it is now possible to find industrial control applications which uses this information. Using colour in process control leads to specific problems where human perception has to be replaced by colour sensors. This paper relies on the fuzzy representation of colours that can be taken into account by fuzzy controllers. If smart sensors already include intelligent func...

  16. Fuzzy Analytic Hierarchy Process-based Chinese Resident Best Fitness Behavior Method Research.

    Science.gov (United States)

    Wang, Dapeng; Zhang, Lan

    2015-01-01

    With explosive development in Chinese economy and science and technology, people's pursuit of health becomes more and more intense, therefore Chinese resident sports fitness activities have been rapidly developed. However, different fitness events popularity degrees and effects on body energy consumption are different, so bases on this, the paper researches on fitness behaviors and gets Chinese residents sports fitness behaviors exercise guide, which provides guidance for propelling to national fitness plan's implementation and improving Chinese resident fitness scientization. The paper starts from the perspective of energy consumption, it mainly adopts experience method, determines Chinese resident favorite sports fitness event energy consumption through observing all kinds of fitness behaviors energy consumption, and applies fuzzy analytic hierarchy process to make evaluation on bicycle riding, shadowboxing practicing, swimming, rope skipping, jogging, running, aerobics these seven fitness events. By calculating fuzzy rate model's membership and comparing their sizes, it gets fitness behaviors that are more helpful for resident health, more effective and popular. Finally, it gets conclusions that swimming is a best exercise mode and its membership is the highest. Besides, the memberships of running, rope skipping and shadowboxing practicing are also relative higher. It should go in for bodybuilding by synthesizing above several kinds of fitness events according to different physical conditions; different living conditions so that can better achieve the purpose of fitness exercises.

  17. Fuzzy rule-based model for optimum orientation of solar panels using satellite image processing

    International Nuclear Information System (INIS)

    Zaher, A; Thiery, F; Grieu, S; Traoré, A; N’goran, Y

    2017-01-01

    In solar energy converting systems, a particular attention is paid to the orientation of solar collectors in order to optimize the overall system efficiency. In this context, the collectors can be fixed or oriented by a continuous solar tracking system. The proposed approach is based on METEOSAT images processing in order to detect the cloud coverage and its duration. These two parameters are treated by a fuzzy inference system deciding the optimal position of the solar panel. In fact, three weather cases can be considered: clear, partly covered or overcast sky. In the first case, the direct sunlight is more important than the diffuse radiation, thus the panel is always pointed towards the sun. In the overcast case, the solar beam is close to zero and the panel is placed horizontally to receive the diffuse radiation. Under partly covered conditions, the fuzzy inference system decides which of the previous positions is more efficient. The proposed approach is implemented using experimental prototype located in Perpignan (France). On a period of 17 months, the results are very satisfactory, with power gains of up to 23 % compared to the collectors oriented by a continuous solar tracking. (paper)

  18. Implementation of Real-Time Machining Process Control Based on Fuzzy Logic in a New STEP-NC Compatible System

    Directory of Open Access Journals (Sweden)

    Po Hu

    2016-01-01

    Full Text Available Implementing real-time machining process control at shop floor has great significance on raising the efficiency and quality of product manufacturing. A framework and implementation methods of real-time machining process control based on STEP-NC are presented in this paper. Data model compatible with ISO 14649 standard is built to transfer high-level real-time machining process control information between CAPP systems and CNC systems, in which EXPRESS language is used to define new STEP-NC entities. Methods for implementing real-time machining process control at shop floor are studied and realized on an open STEP-NC controller, which is developed using object-oriented, multithread, and shared memory technologies conjunctively. Cutting force at specific direction of machining feature in side mill is chosen to be controlled object, and a fuzzy control algorithm with self-adjusting factor is designed and embedded in the software CNC kernel of STEP-NC controller. Experiments are carried out to verify the proposed framework, STEP-NC data model, and implementation methods for real-time machining process control. The results of experiments prove that real-time machining process control tasks can be interpreted and executed correctly by the STEP-NC controller at shop floor, in which actual cutting force is kept around ideal value, whether axial cutting depth changes suddenly or continuously.

  19. 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.

  20. Sustainable energy planning decision using the intuitionistic fuzzy analytic hierarchy process: choosing energy technology in Malaysia: necessary modifications

    Science.gov (United States)

    Al-Qudaimi, Abdullah; Kumar, Amit

    2018-05-01

    Recently, Abdullah and Najib (International Journal of Sustainable Energy 35(4): 360-377, 2016) proposed an intuitionistic fuzzy analytic hierarchy process to deal with uncertainty in decision-making and applied it to establish preference in the sustainable energy planning decision-making of Malaysia. This work may attract the researchers of other countries to choose energy technology for their countries. However, after a deep study of the published paper (International Journal of Sustainable Energy 35(4): 362-377, 2016), it is noticed that the expression used by Abdullah and Najib in Step 6 of their proposed method for evaluating the intuitionistic fuzzy entropy of each aggregate of each row of intuitionistic fuzzy matrix is not valid. Therefore, it is not genuine to use the method proposed by Abdullah and Najib for solving real-life problems. The aim of this paper was to suggest the required necessary modifications for resolving the flaws of the Abdullah and Najib method.

  1. French speaking meetings on fuzzy logic and its applications

    International Nuclear Information System (INIS)

    2000-01-01

    The LFA conferences are devoted to the presentation of the most recent works about the fuzzy sets theory and its possible applications to fuzzy control, classification, pattern recognition, data processing, decision making, reasoning, image processing and interpretation, fusion of informations, artificial intelligence and information management systems. Among the 39 articles reported in this book, one concerns the processing of NMR images in nuclear medicine and has been selected for Inis. (J.S.)

  2. Closeness Degree-Based Hesitant Trapezoidal Fuzzy Multicriteria Decision Making Method for Evaluating Green Suppliers with Qualitative Information

    Directory of Open Access Journals (Sweden)

    Xiaolu Zhang

    2018-01-01

    Full Text Available The aim of this study is to develop a new closeness degree-based hesitant trapezoidal fuzzy (HTrF multicriteria decision making (MCDM approach for identifying the most appropriate green suppliers in food supply chain involving uncertain qualitative evaluation information. The uniqueness of the proposed HTrF MCDM method is the consideration of uncertain qualitative information represented by flexible linguistic expressions based on HTrF values and the construction of compromise solution with the revised closeness degree. The revised closeness degree can make sure that the most appropriate solution has the shortest distance from the HTrF positive ideal solution and the farthest distance from the HTrF negative ideal solution, simultaneously. This proposed HTrF MCDM technique not only offers a simple and efficient decision support tool to aid the food firms for identifying the optimal suppliers in food supply chain but also can enable the managers of food firms to better understand the complete evaluation and decision processes. In addition, this study provides a novel defuzzification technique to manage the HTrF weights values of main-criteria and subcriteria, respectively.

  3. Conceptual models of information processing

    Science.gov (United States)

    Stewart, L. J.

    1983-01-01

    The conceptual information processing issues are examined. Human information processing is defined as an active cognitive process that is analogous to a system. It is the flow and transformation of information within a human. The human is viewed as an active information seeker who is constantly receiving, processing, and acting upon the surrounding environmental stimuli. Human information processing models are conceptual representations of cognitive behaviors. Models of information processing are useful in representing the different theoretical positions and in attempting to define the limits and capabilities of human memory. It is concluded that an understanding of conceptual human information processing models and their applications to systems design leads to a better human factors approach.

  4. Controlling the process of composting farm biomass with the use of fuzzy logic

    Energy Technology Data Exchange (ETDEWEB)

    Neugebauer, M. [Warmia and Mazury Univ., Olsztyn (Poland)

    2010-07-01

    The process of composting organic waste produces organic fertilizer. The main phases of composting include the mesophilic and thermophilic stages followed by cooling down and maturing. The thermophilic phase involves a relatively high temperature, from 45 to 80 degrees C and carbon dioxide emission. Extending this phase of the composting process may reduce the entire process time and the amount of methane produced. The process can be controlled by adjusting the amount of air supplied to the compost heap and controlling the temperature in the bed or oxygen content in the air leaving the heap. Precise control would help optimize the composting process in terms of heat reception, duration of the process and the temperature inside the bed. Excess heat could be put to use elsewhere, such as warming the substrate in a greenhouse. However, overheating the heap reduces the amount of thermophilic microorganisms and may actually reduce the compost temperature, thus slow down or even stop the thermophilic phase of the composting process. A literature survey focused on complex non-linear processes has shown that systems based on fuzzy logic are effective in controlling the process.

  5. Integrating Physical and Topographic Information Into a Fuzzy Scheme to Map Flooded Area by SAR

    Directory of Open Access Journals (Sweden)

    Flavia Macina

    2008-07-01

    Full Text Available A flood mapping procedure based on a fuzzy sets theory has been developed. The method is based on the integration of Synthetic Aperture Radar (SAR measurements with additional data on the inundated area, such as a land cover map and a digital elevation model (DEM. The information on land cover has allowed us to account for both specular reflection, typical of open water, and double bounce backscattering, typical of forested and urban areas. DEM has been exploited to include simple hydraulic considerations on the dependence of inundation probability on surface characteristics. Contextual information has been taken into account too. The proposed algorithm has been tested on a flood occurred in Italy on November 1994. A pair of ERS-1 images, collected before and after (three days later the flood, has been used. The results have been compared with the data provided by a ground survey carried out when the flood reached its maximum extension. Despite the temporal mismatch between the survey and the post-inundation SAR image, the comparison has yielded encouraging results, with the 87% of the pixels correctly classified as inundated.

  6. Integrating Physical and Topographic Information Into a Fuzzy Scheme to Map Flooded Area by SAR.

    Science.gov (United States)

    Pierdicca, Nazzareno; Chini, Marco; Pulvirenti, Luca; Macina, Flavia

    2008-07-10

    A flood mapping procedure based on a fuzzy sets theory has been developed. The method is based on the integration of Synthetic Aperture Radar (SAR) measurements with additional data on the inundated area, such as a land cover map and a digital elevation model (DEM). The information on land cover has allowed us to account for both specular reflection, typical of open water, and double bounce backscattering, typical of forested and urban areas. DEM has been exploited to include simple hydraulic considerations on the dependence of inundation probability on surface characteristics. Contextual information has been taken into account too. The proposed algorithm has been tested on a flood occurred in Italy on November 1994. A pair of ERS-1 images, collected before and after (three days later) the flood, has been used. The results have been compared with the data provided by a ground survey carried out when the flood reached its maximum extension. Despite the temporal mismatch between the survey and the post-inundation SAR image, the comparison has yielded encouraging results, with the 87% of the pixels correctly classified as inundated.

  7. A Novel Group Decision-Making Method Based on Sensor Data and Fuzzy Information.

    Science.gov (United States)

    Bai, Yu-Ting; Zhang, Bai-Hai; Wang, Xiao-Yi; Jin, Xue-Bo; Xu, Ji-Ping; Su, Ting-Li; Wang, Zhao-Yang

    2016-10-28

    Algal bloom is a typical phenomenon of the eutrophication of rivers and lakes and makes the water dirty and smelly. It is a serious threat to water security and public health. Most scholars studying solutions for this pollution have studied the principles of remediation approaches, but few have studied the decision-making and selection of the approaches. Existing research uses simplex decision-making information which is highly subjective and uses little of the data from water quality sensors. To utilize these data and solve the rational decision-making problem, a novel group decision-making method is proposed using the sensor data with fuzzy evaluation information. Firstly, the optimal similarity aggregation model of group opinions is built based on the modified similarity measurement of Vague values. Secondly, the approaches' ability to improve the water quality indexes is expressed using Vague evaluation methods. Thirdly, the water quality sensor data are analyzed to match the features of the alternative approaches with grey relational degrees. This allows the best remediation approach to be selected to meet the current water status. Finally, the selection model is applied to the remediation of algal bloom in lakes. The results show this method's rationality and feasibility when using different data from different sources.

  8. A Novel Group Decision-Making Method Based on Sensor Data and Fuzzy Information

    Directory of Open Access Journals (Sweden)

    Yu-Ting Bai

    2016-10-01

    Full Text Available Algal bloom is a typical phenomenon of the eutrophication of rivers and lakes and makes the water dirty and smelly. It is a serious threat to water security and public health. Most scholars studying solutions for this pollution have studied the principles of remediation approaches, but few have studied the decision-making and selection of the approaches. Existing research uses simplex decision-making information which is highly subjective and uses little of the data from water quality sensors. To utilize these data and solve the rational decision-making problem, a novel group decision-making method is proposed using the sensor data with fuzzy evaluation information. Firstly, the optimal similarity aggregation model of group opinions is built based on the modified similarity measurement of Vague values. Secondly, the approaches’ ability to improve the water quality indexes is expressed using Vague evaluation methods. Thirdly, the water quality sensor data are analyzed to match the features of the alternative approaches with grey relational degrees. This allows the best remediation approach to be selected to meet the current water status. Finally, the selection model is applied to the remediation of algal bloom in lakes. The results show this method’s rationality and feasibility when using different data from different sources.

  9. Information Processing Research.

    Science.gov (United States)

    1986-09-01

    business form in which information is entered by filling in blanks, or circling alternatives. The fields of the form cor- respond to the various pieces...power. Parallelism, rather than raw speed of the computing elements, seems to be the way that the 4-15 MACHINE INTELIGENCE brain gets such jobs done...MACHINE INTELIGENCE all intelligent systems. The purpose of this paper is to characterize the weak methods and to explain how and why they arise in

  10. Industrial Information Processing

    DEFF Research Database (Denmark)

    Svensson, Carsten

    2002-01-01

    This paper demonstrates, how cross-functional business processes may be aligned with product specification systems in an intra-organizational environment by integrating planning systems and expert systems, thereby providing an end-to-end integrated and an automated solution to the “build-to-order...

  11. 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

  12. 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

  13. Mental Status Documentation: Information Quality and Data Processes.

    Science.gov (United States)

    Weir, Charlene; Gibson, Bryan; Taft, Teresa; Slager, Stacey; Lewis, Lacey; Staggers, Nancy

    2016-01-01

    Delirium is a fluctuating disturbance of cognition and/or consciousness associated with poor outcomes. Caring for patients with delirium requires integration of disparate information across clinicians, settings and time. The goal of this project was to characterize the information processes involved in nurses' assessment, documentation, decisionmaking and communication regarding patients' mental status in the inpatient setting. VA nurse managers of medical wards (n=18) were systematically selected across the US. A semi-structured telephone interview focused on current assessment, documentation, and communication processes, as well as clinical and administrative decision-making was conducted, audio-recorded and transcribed. A thematic analytic approach was used. Five themes emerged: 1) Fuzzy Concepts, 2) Grey Data, 3) Process Variability 4) Context is Critical and 5) Goal Conflict. This project describes the vague and variable information processes related to delirium and mental status that undermine effective risk, prevention, identification, communication and mitigation of harm.

  14. A Fuzzy Neural Network Based on Non-Euclidean Distance Clustering for Quality Index Model in Slashing Process

    Directory of Open Access Journals (Sweden)

    Yuxian Zhang

    2015-01-01

    Full Text Available The quality index model in slashing process is difficult to build by reason of the outliers and noise data from original data. To the above problem, a fuzzy neural network based on non-Euclidean distance clustering is proposed in which the input space is partitioned into many local regions by the fuzzy clustering based on non-Euclidean distance so that the computation complexity is decreased, and fuzzy rule number is determined by validity function based on both the separation and the compactness among clusterings. Then, the premise parameters and consequent parameters are trained by hybrid learning algorithm. The parameters identification is realized; meanwhile the convergence condition of consequent parameters is obtained by Lyapunov function. Finally, the proposed method is applied to build the quality index model in slashing process in which the experimental data come from the actual slashing process. The experiment results show that the proposed fuzzy neural network for quality index model has lower computation complexity and faster convergence time, comparing with GP-FNN, BPNN, and RBFNN.

  15. Interfirm collaboration in the Fuzzy Front-End of the innovation process

    DEFF Research Database (Denmark)

    Jørgensen, Jacob Høj; Goduscheit, René Chester; Bergenholtz, Carsten

    , marketing, sales. The focus of this paper is on collaboration where innovation is the main part of the collaborative effort. Innovation refers to the research and development (R&D) activity devoted to increasing scientific or technical knowledge and the application of that knowledge to the creation of new...... and tendencies in formal R&D partnering relations. This paper, however, focuses on collaboration between independent companies prior to such formal agreements as joint ventures or other contractual agreements. This first phase of the innovation process is often referred to as the Fuzzy Front-End (FFE....... In this article we examine the characteristics of the FFE phase and explore this phase in an inter-firm perspective. Through an in-depth case-study of a single firm and its innovation partners we identify parameters for improved collaboration in the FFE. In conclusion we outline a model for inter...

  16. Developing an Intelligent Automatic Appendix Extraction Method from Ultrasonography Based on Fuzzy ART and Image Processing

    Directory of Open Access Journals (Sweden)

    Kwang Baek Kim

    2015-01-01

    Full Text Available Ultrasound examination (US does a key role in the diagnosis and management of the patients with clinically suspected appendicitis which is the most common abdominal surgical emergency. Among the various sonographic findings of appendicitis, outer diameter of the appendix is most important. Therefore, clear delineation of the appendix on US images is essential. In this paper, we propose a new intelligent method to extract appendix automatically from abdominal sonographic images as a basic building block of developing such an intelligent tool for medical practitioners. Knowing that the appendix is located at the lower organ area below the bottom fascia line, we conduct a series of image processing techniques to find the fascia line correctly. And then we apply fuzzy ART learning algorithm to the organ area in order to extract appendix accurately. The experiment verifies that the proposed method is highly accurate (successful in 38 out of 40 cases in extracting appendix.

  17. FUZZY INFERENCE SYSTEM MODELING FOR BED ACTIVE CARBON RE-GENERATION PROCESS (CO2 GAS FACTORY CASE

    Directory of Open Access Journals (Sweden)

    S. Febriana

    2005-01-01

    Full Text Available Bed active carbon is one of the most important materials that had great impact in determining level of impurities in production of CO2 gas. In this particular factory case, there is unavailability of standard duration time of heating and cooling and steam flow rate for the re-generation process of bed active carbon. The paper discusses the fuzzy inference system for modeling of re-generation process of bed active carbon to find the optimum setting parameter. The fuzzy inference system was build using real historical daily processing data. After validation process, surface plot analysis was performed to find the optimum setting. The result of re-generation parameter setting is 9-10 hours of heating process, 4.66-5.32 hours of cooling process, and 1500-2500 kg/hr of steam flow rate.

  18. Integrated Optical Information Processing

    Science.gov (United States)

    1988-08-01

    applications in optical disk memory systems [91. This device is constructed in a glass /SiO2/Si waveguide. The choice of a Si substrate allows for the...contact mask) were formed in the photoresist deposited on all of the samples, we covered the unwanted gratings on each sample with cover glass slides...processing, let us consider TeO2 (v, = 620 m/s) as a potential substrate for applications requiring large time delays. This con- sideration is despite

  19. A fuzzy model based adaptive PID controller design for nonlinear and uncertain processes.

    Science.gov (United States)

    Savran, Aydogan; Kahraman, Gokalp

    2014-03-01

    We develop a novel adaptive tuning method for classical proportional-integral-derivative (PID) controller to control nonlinear processes to adjust PID gains, a problem which is very difficult to overcome in the classical PID controllers. By incorporating classical PID control, which is well-known in industry, to the control of nonlinear processes, we introduce a method which can readily be used by the industry. In this method, controller design does not require a first principal model of the process which is usually very difficult to obtain. Instead, it depends on a fuzzy process model which is constructed from the measured input-output data of the process. A soft limiter is used to impose industrial limits on the control input. The performance of the system is successfully tested on the bioreactor, a highly nonlinear process involving instabilities. Several tests showed the method's success in tracking, robustness to noise, and adaptation properties. We as well compared our system's performance to those of a plant with altered parameters with measurement noise, and obtained less ringing and better tracking. To conclude, we present a novel adaptive control method that is built upon the well-known PID architecture that successfully controls highly nonlinear industrial processes, even under conditions such as strong parameter variations, noise, and instabilities. © 2013 Published by ISA on behalf of ISA.

  20. SISTEM PENGEMBANGAN KENDALI FUZZY LOGIC BERBASIS MIKROKONTROLER KELUARGA MCS51 (PetraFuz

    Directory of Open Access Journals (Sweden)

    Thiang Thiang

    1999-01-01

    Full Text Available This paper presents a Fuzzy Logic Development Tool called PetraFuz which has been developed at Control System Laboratory, Electrical Engineering Department, Petra Christian University. The system consists of a hardware target based on MCS51 microcontroller and a software support running under PC Windows. The system is targeted for developing fuzzy logic based systems. It supports fuzzy logic design, evaluation, assembly language generator and downloading process to the target hardware to perform on-line fuzzy process. Process action and fuzzy parameters could be transferred to PC monitor via RS-232 serial communication, this on-line process parameters is used for fuzzy tuning, i.e. fuzzy if-then rules and fuzzy membership functions. The PetraFuz tool helps very much for Fuzzy system developments, it could reduce development time significantly. The tool could spur the development of fuzzy systems based on microcontroller systems such as fuzzy control systems, fuzzy information processing, etc. Abstract in Bahasa Indonesia : Makalah ini menyajikan sebuah sistem pengembangan kendali fuzzy logic (PetraFuz, Petra Fuzzy Development System yang dikembangkan oleh laboratorium Sistem Kontrol, Jurusan Teknik Elektro, Universitas Kristen Petra Surabaya. Sistem ini terdiri dari perangkat keras sistem mikrokontroler MCS51 dan perangkat lunak pendukung yang berjalan pada PC. Sistem PetraFuz digunakan untuk mengembangkan sistem berbasis fuzzy logic utamanya pada bidang kendali. Kemampuan sistem meliputi pengembangan pada fase perancangan kendali, evaluasi kendali, pembentukan program bahasa assembly MCS51 dan proses downloading program menuju target sistem mikrokontroler MCS51 untuk dieksekusi melakukan kendali pada plant yang nyata. Aksi kendali dapat diakuisi oleh program PC melalui komunikasi serial RS232 sehingga respon kendali dapat digambarkan pada layar monitor untuk dilakukan analisis lebih lanjut yang diperlukan pada proses tuning if-then fuzzy rules

  1. Risk and information processing

    International Nuclear Information System (INIS)

    Rasmussen, J.

    1985-08-01

    The reasons for the current widespread arguments between designers of advanced technological systems like, for instance, nuclear power plants and opponents from the general public concerning levels of acceptable risk may be found in incompatible definitions of risk, in differences in risk perception and criteria for acceptance, etc. Of importance may, however, also be the difficulties met in presenting the basis for risk analysis, such as the conceptual system models applied, in an explicit and credible form. Application of modern information technology for the design of control systems and human-machine interfaces together with the trends towards large centralised industrial installations have made it increasingly difficult to establish an acceptable model framework, in particular considering the role of human errors in major system failures and accidents. Different aspects of this problem are discussed in the paper, and areas are identified where research is needed in order to improve not only the safety of advanced systems, but also the basis for their acceptance by the general public. (author)

  2. A Recommender System for Programming Online Judges Using Fuzzy Information Modeling

    Directory of Open Access Journals (Sweden)

    Raciel Yera Toledo

    2018-04-01

    Full Text Available Programming online judges (POJs are an emerging application scenario in e-learning recommendation areas. Specifically, they are e-learning tools usually used in programming practices for the automatic evaluation of source code developed by students when they are solving programming problems. Usually, they contain a large collection of such problems, to be solved by students at their own personalized pace. The more problems in the POJ the harder the selection of the right problem to solve according to previous users performance, causing information overload and a widespread discouragement. This paper presents a recommendation framework to mitigate this issue by suggesting problems to solve in programming online judges, through the use of fuzzy tools which manage the uncertainty related to this scenario. The evaluation of the proposal uses real data obtained from a programming online judge, and shows that the new approach improves previous recommendation strategies which do not consider uncertainty management in the programming online judge scenarios. Specifically, the best results were obtained for short recommendation lists.

  3. Identifying relevant group of miRNAs in cancer using fuzzy mutual information.

    Science.gov (United States)

    Pal, Jayanta Kumar; Ray, Shubhra Sankar; Pal, Sankar K

    2016-04-01

    MicroRNAs (miRNAs) act as a major biomarker of cancer. All miRNAs in human body are not equally important for cancer identification. We propose a methodology, called FMIMS, which automatically selects the most relevant miRNAs for a particular type of cancer. In FMIMS, miRNAs are initially grouped by using a SVM-based algorithm; then the group with highest relevance is determined and the miRNAs in that group are finally ranked for selection according to their redundancy. Fuzzy mutual information is used in computing the relevance of a group and the redundancy of miRNAs within it. Superiority of the most relevant group to all others, in deciding normal or cancer, is demonstrated on breast, renal, colorectal, lung, melanoma and prostate data. The merit of FMIMS as compared to several existing methods is established. While 12 out of 15 selected miRNAs by FMIMS corroborate with those of biological investigations, three of them viz., "hsa-miR-519," "hsa-miR-431" and "hsa-miR-320c" are possible novel predictions for renal cancer, lung cancer and melanoma, respectively. The selected miRNAs are found to be involved in disease-specific pathways by targeting various genes. The method is also able to detect the responsible miRNAs even at the primary stage of cancer. The related code is available at http://www.jayanta.droppages.com/FMIMS.html .

  4. An enhanced reliability-oriented workforce planning model for process industry using combined fuzzy goal programming and differential evolution approach

    Science.gov (United States)

    Ighravwe, D. E.; Oke, S. A.; Adebiyi, K. A.

    2018-03-01

    This paper draws on the "human reliability" concept as a structure for gaining insight into the maintenance workforce assessment in a process industry. Human reliability hinges on developing the reliability of humans to a threshold that guides the maintenance workforce to execute accurate decisions within the limits of resources and time allocations. This concept offers a worthwhile point of deviation to encompass three elegant adjustments to literature model in terms of maintenance time, workforce performance and return-on-workforce investments. These fully explain the results of our influence. The presented structure breaks new grounds in maintenance workforce theory and practice from a number of perspectives. First, we have successfully implemented fuzzy goal programming (FGP) and differential evolution (DE) techniques for the solution of optimisation problem in maintenance of a process plant for the first time. The results obtained in this work showed better quality of solution from the DE algorithm compared with those of genetic algorithm and particle swarm optimisation algorithm, thus expressing superiority of the proposed procedure over them. Second, the analytical discourse, which was framed on stochastic theory, focusing on specific application to a process plant in Nigeria is a novelty. The work provides more insights into maintenance workforce planning during overhaul rework and overtime maintenance activities in manufacturing systems and demonstrated capacity in generating substantially helpful information for practice.

  5. 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.

  6. PENENTUAN FAKTOR YANG BERPENGARUH DALAM FAULTY BEHAVIOR RISK MELALUI PENDEKATAN METODE FUZZY ANALYTIC HIERARCHY PROCESS

    Directory of Open Access Journals (Sweden)

    Rizal Irfan Fuadi

    2015-06-01

    Full Text Available Manajemen keselamatan merupakan pengorganisasian, sumber daya manusia, kebijakan dan prosedur interaktif yang bertujuan untuk mengurangi kemungkinan kerusakan dan kerugian di tempat kerja. Salah satu cara untuk memperbaiki manajemen keselamatan di perusahaan adalah dengan melakukan penelitian mengenai faktor yang berpengaruh dalam risiko kesalahan perilaku. Secara umum, faktor-faktor yang mempengaruhi keselamatan kerja tidak memiliki struktur fisik. Untuk itu, maka masalah pada kondisi nyata dapat direpresentasikan dengan cara yang lebih baik menggunakan angka fuzzy untuk mengevaluasi faktor-faktor ini. Pada penelitian ini, pendekatan Fuzzy AHP bertujuan untuk menentukan tingkat Faulty Behavior Risk (FBR pada sistem kerja.Penentuan faktor yang berpengaruh dalam Faulty Behavior Risk (FBR/risiko dari perilaku yang salah dimulai dengan menentukan responden, penyusunan kuesioner, uji validitas dan reliabilitas, hasil dari kuesioner dijadikan inputan dalam pengolahan data dengan metode FuzzyAnalytic Hierachy Process (FAHP. Kuesioner ini dibuat berdasarkan konsep safety management yang terdiri dari 4 faktor, yaitu faktor organisasi, faktor pribadi, faktor pekerjaan dan faktor lingkungan. Penelitian ini dilakukan pada Bay 2.1 yang memproduksi panel dan bay 7.1 yang memproduksi finning. Berdasarkan perhitungan FBR pada bay 2.1 menunjukkan nilai 0,4793 yang berarti risiko kesalahan perilaku di antara batas bawah (0,25 dan batas atas (0,50. Sedangkan pada bay 7.1 sebesar 0,5317 yang berarti risiko kesalahan perilaku memiliki potensi tinggi karena berada di atas batas atas. Dari hasil penentuan FBR didapatkan nilai  pada bay 2.1 yang memiliki risiko penyebab tertinggi terdapat pada sub faktor kurang persiapan (0,0788 sedangkan pada bay 7.1 dengan nilai FBR sebesar 0,5317 yang memiliki risiko tertinggi terdapat pada sub faktor kelelahan kerja (0,0970. Melalui penelitian ini, faktor penyebab kesalahan perilaku kerja dapat diketahui dan diberikan

  7. Fuzzy Entropy: Axiomatic Definition and Neural Networks Model

    Institute of Scientific and Technical Information of China (English)

    QINGMing; CAOYue; HUANGTian-min

    2004-01-01

    The measure of uncertainty is adopted as a measure of information. The measures of fuzziness are known as fuzzy information measures. The measure of a quantity of fuzzy information gained from a fuzzy set or fuzzy system is known as fuzzy entropy. Fuzzy entropy has been focused and studied by many researchers in various fields. In this paper, firstly, the axiomatic definition of fuzzy entropy is discussed. Then, neural networks model of fuzzy entropy is proposed, based on the computing capability of neural networks. In the end, two examples are discussed to show the efficiency of the model.

  8. BRICS and Quantum Information Processing

    DEFF Research Database (Denmark)

    Schmidt, Erik Meineche

    1998-01-01

    BRICS is a research centre and international PhD school in theoretical computer science, based at the University of Aarhus, Denmark. The centre has recently become engaged in quantum information processing in cooperation with the Department of Physics, also University of Aarhus. This extended...... abstract surveys activities at BRICS with special emphasis on the activities in quantum information processing....

  9. Information Processing and Limited Liability

    OpenAIRE

    Bartosz Mackowiak; Mirko Wiederholt

    2012-01-01

    Decision-makers often face limited liability and thus know that their loss will be bounded. We study how limited liability affects the behavior of an agent who chooses how much information to acquire and process in order to take a good decision. We find that an agent facing limited liability processes less information than an agent with unlimited liability. The informational gap between the two agents is larger in bad times than in good times and when information is more costly to process.

  10. Evaluation of End-Products in Architecture Design Process: A Fuzzy Decision-Making Model

    Directory of Open Access Journals (Sweden)

    Serkan PALABIYIK

    2012-06-01

    Full Text Available This paper presents a study on the development of a fuzzy multi-criteria decision-making model for the evaluation of end products of the architectural design process. Potentials of the developed model were investigated within the scope of architectural design education, specifically an international design studio titled “Design for Disassembly and Reuse: Design & Building Multipurpose Transformable Pavilions.” The studio work followed a design process that integrated systematic and heuristic thinking. The design objectives and assessment criteria were clearly set out at the beginning of the process by the studio coordinator with the aim of narrowing the design space and increasing awareness of the consequences of design decisions. At the end of the design process, designs produced in the studio were evaluated using the developed model to support decision making. The model facilitated the identification of positive and negative aspects of the designs and selection of the design alternative that best met the studio objectives set at the beginning.

  11. Improvement of the Performance of an Electrocoagulation Process System Using Fuzzy Control of pH.

    Science.gov (United States)

    Demirci, Yavuz; Pekel, Lutfiye Canan; Altinten, Ayla; Alpbaz, Mustafa

    2015-12-01

    The removal efficiencies of electrocoagulation (EC) systems are highly dependent on the initial value of pH. If an EC system has an acidic influent, the pH of the effluent increases during the treatment process; conversely, if such a system has an alkaline influent, the pH of the effluent decreases during the treatment process. Thus, changes in the pH of the wastewater affect the efficiency of the EC process. In this study, we investigated the dynamic effects of pH. To evaluate approaches for preventing increases in the pH of the system, the MATLAB/Simulink program was used to develop and evaluate an on-line computer-based system for pH control. The aim of this work was to study Proportional-Integral-Derivative (PID) control and fuzzy control of the pH of a real textile wastewater purification process using EC. The performances and dynamic behaviors of these two control systems were evaluated based on determinations of COD, colour, and turbidity removal efficiencies.

  12. Intelligent Modeling Combining Adaptive Neuro Fuzzy Inference System and Genetic Algorithm for Optimizing Welding Process Parameters

    Science.gov (United States)

    Gowtham, K. N.; Vasudevan, M.; Maduraimuthu, V.; Jayakumar, T.

    2011-04-01

    Modified 9Cr-1Mo ferritic steel is used as a structural material for steam generator components of power plants. Generally, tungsten inert gas (TIG) welding is preferred for welding of these steels in which the depth of penetration achievable during autogenous welding is limited. Therefore, activated flux TIG (A-TIG) welding, a novel welding technique, has been developed in-house to increase the depth of penetration. In modified 9Cr-1Mo steel joints produced by the A-TIG welding process, weld bead width, depth of penetration, and heat-affected zone (HAZ) width play an important role in determining the mechanical properties as well as the performance of the weld joints during service. To obtain the desired weld bead geometry and HAZ width, it becomes important to set the welding process parameters. In this work, adaptative neuro fuzzy inference system is used to develop independent models correlating the welding process parameters like current, voltage, and torch speed with weld bead shape parameters like depth of penetration, bead width, and HAZ width. Then a genetic algorithm is employed to determine the optimum A-TIG welding process parameters to obtain the desired weld bead shape parameters and HAZ width.

  13. A New Prediction Model for Transformer Winding Hotspot Temperature Fluctuation Based on Fuzzy Information Granulation and an Optimized Wavelet Neural Network

    Directory of Open Access Journals (Sweden)

    Li Zhang

    2017-12-01

    Full Text Available Winding hotspot temperature is the key factor affecting the load capacity and service life of transformers. For the early detection of transformer winding hotspot temperature anomalies, a new prediction model for the hotspot temperature fluctuation range based on fuzzy information granulation (FIG and the chaotic particle swarm optimized wavelet neural network (CPSO-WNN is proposed in this paper. The raw data are firstly processed by FIG to extract useful information from each time window. The extracted information is then used to construct a wavelet neural network (WNN prediction model. Furthermore, the structural parameters of WNN are optimized by chaotic particle swarm optimization (CPSO before it is used to predict the fluctuation range of the hotspot temperature. By analyzing the experimental data with four different prediction models, we find that the proposed method is more effective and is of guiding significance for the operation and maintenance of transformers.

  14. Information accessibility and cryptic processes

    Energy Technology Data Exchange (ETDEWEB)

    Mahoney, John R; Ellison, Christopher J; Crutchfield, James P [Complexity Sciences Center and Physics Department, University of California at Davis, One Shields Avenue, Davis, CA 95616 (United States)], E-mail: jrmahoney@ucdavis.edu, E-mail: cellison@cse.ucdavis.edu, E-mail: chaos@cse.ucdavis.edu

    2009-09-11

    We give a systematic expansion of the crypticity-a recently introduced measure of the inaccessibility of a stationary process's internal state information. This leads to a hierarchy of k-cryptic processes and allows us to identify finite-state processes that have infinite cryptic order-the internal state information is present across arbitrarily long, observed sequences. The crypticity expansion is exact in both the finite- and infinite-order cases. It turns out that k-crypticity is complementary to the Markovian finite-order property that describes state information in processes. One application of these results is an efficient expansion of the excess entropy-the mutual information between a process's infinite past and infinite future-that is finite and exact for finite-order cryptic processes. (fast track communication)

  15. Color identification and fuzzy reasoning based monitoring and controlling of fermentation process of branched chain amino acid

    Science.gov (United States)

    Ma, Lei; Wang, Yizhong; Xu, Qingyang; Huang, Huafang; Zhang, Rui; Chen, Ning

    2009-11-01

    The main production method of branched chain amino acid (BCAA) is microbial fermentation. In this paper, to monitor and to control the fermentation process of BCAA, especially its logarithmic phase, parameters such as the color of fermentation broth, culture temperature, pH, revolution, dissolved oxygen, airflow rate, pressure, optical density, and residual glucose, are measured and/or controlled and/or adjusted. The color of fermentation broth is measured using the HIS color model and a BP neural network. The network's input is the histograms of hue H and saturation S, and output is the color description. Fermentation process parameters are adjusted using fuzzy reasoning, which is performed by inference rules. According to the practical situation of BCAA fermentation process, all parameters are divided into four grades, and different fuzzy rules are established.

  16. Effectiveness evaluation of double-layered satellite network with laser and microwave hybrid links based on fuzzy analytic hierarchy process

    Science.gov (United States)

    Zhang, Wei; Rao, Qiaomeng

    2018-01-01

    In order to solve the problem of high speed, large capacity and limited spectrum resources of satellite communication network, a double-layered satellite network with global seamless coverage based on laser and microwave hybrid links is proposed in this paper. By analyzing the characteristics of the double-layered satellite network with laser and microwave hybrid links, an effectiveness evaluation index system for the network is established. And then, the fuzzy analytic hierarchy process, which combines the analytic hierarchy process and the fuzzy comprehensive evaluation theory, is used to evaluate the effectiveness of the double-layered satellite network with laser and microwave hybrid links. Furthermore, the evaluation result of the proposed hybrid link network is obtained by simulation. The effectiveness evaluation process of the proposed double-layered satellite network with laser and microwave hybrid links can help to optimize the design of hybrid link double-layered satellite network and improve the operating efficiency of the satellite system.

  17. Perangkat Lunak Perhitungan Perubahan Jabatan Dengan Menggunakan Fuzzy Analytical Hierarchy Process (studi kasus : UIN Sunan Ampel Surabaya

    Directory of Open Access Journals (Sweden)

    Ilham .

    2017-04-01

    Full Text Available This study discusses the promotion in an institution by considering many factors, and the submission must be conducted objectively, not subjectively. To be able to give an objective assessment results in every employee by considering all the assessment criteria, one of the methods that can be used is the method of Fuzzy Analytical Hierarchy Process (AHP. From the results of research using Fuzzy Analytical Hierarchy Process method showed that the greatest weight virmansyah discount the value that is equal to 80.78 so a great opportunity to get a change or a promotion. Decision to change positions, it gives the rank order value candidates as a recommendation for promotion to employees. So with the Decision Support System with Analytical Hierarchy Process  method can help and facilitate career planning manager (sale or transfer to save time, costs, and more objective.

  18. Process parameter optimization during EDM of AISI 316 LN stainless steel by using fuzzy based multi-objective PSO

    Energy Technology Data Exchange (ETDEWEB)

    Majumder, Arindam [National Institute of Technology Agartala, Tripura (India)

    2013-07-15

    The present contribution describes an application of a hybrid approach using fuzzy logic and particle swarm optimization (PSO) for optimizing the process parameters in the electric discharge machining (EDM) of AISI 316LN Stainless Steel. In this study, each experimentation was performed under different machining conditions of pulse current, pulse on-time, and pulse off-time. Machining performances such as MRR and EWR were evaluated. A Taguchi L9 orthogonal array was produced to plan the experimentation and the regression method was applied to model the relationship between the input factors and responses. A fuzzy model was employed to provide a fitness function to PSO by unifying the multiple responses. Finally, PSO was used to predict the optimal process parametric settings for the multi-performance optimization of the EDM operation. The experimental results confirm the feasibility of the strategy and are in good agreement with the predicted results over a wide range of machining conditions employed in the process.

  19. Information management in process planning

    NARCIS (Netherlands)

    Lutters, Diederick; Wijnker, T.C.; Kals, H.J.J.

    1999-01-01

    A recently proposed reference model indicates the use of structured information as the basis for the control of design and manufacturing processes. The model is used as a basis to describe the integration of design and process planning. A differentiation is made between macro- and micro process

  20. Information processing, computation, and cognition.

    Science.gov (United States)

    Piccinini, Gualtiero; Scarantino, Andrea

    2011-01-01

    Computation and information processing are among the most fundamental notions in cognitive science. They are also among the most imprecisely discussed. Many cognitive scientists take it for granted that cognition involves computation, information processing, or both - although others disagree vehemently. Yet different cognitive scientists use 'computation' and 'information processing' to mean different things, sometimes without realizing that they do. In addition, computation and information processing are surrounded by several myths; first and foremost, that they are the same thing. In this paper, we address this unsatisfactory state of affairs by presenting a general and theory-neutral account of computation and information processing. We also apply our framework by analyzing the relations between computation and information processing on one hand and classicism, connectionism, and computational neuroscience on the other. We defend the relevance to cognitive science of both computation, at least in a generic sense, and information processing, in three important senses of the term. Our account advances several foundational debates in cognitive science by untangling some of their conceptual knots in a theory-neutral way. By leveling the playing field, we pave the way for the future resolution of the debates' empirical aspects.

  1. Grey fuzzy logic approach for the optimization of DLC thin film coating process parameters using PACVD technique

    Science.gov (United States)

    Ghadai, R. K.; Das, P. P.; Shivakoti, I.; Mondal, S. C.; Swain, B. P.

    2017-07-01

    Diamond-like carbon (DLC) coatings are widely used in medical, manufacturing and aerospace industries due to their excellent mechanical, biological, optical and tribological properties. The selection of optimal process parameters for efficient characteristics of DLC film is always a challenging issue for the materials science researchers. The optimal combination of the process parameters involved in the deposition of DLC films provide a better result, which subsequently help other researchers to choose the process parameters. In the present work Grey Relation Analysis (GRA) and Fuzzy-logic are being used for the optimization of process parameters in DLC film coating by using plasma assist chemical vapour deposition (PACVD) technique. The bias voltage, bias frequency, deposition pressure, gas composition are considered as input process parameters and hardness (GPa), Young's modulus (GPa), ratio between diamond to graphic fraction, (Id/Ig) ratio are considered as response parameters. The input parameters are optimized by grey fuzzy analysis. The contribution of individual input parameter is done by ANOVA. In this analysis found that bias voltage having the least influence and gas composition has highest influence in the PACVD deposited DLC films. The grey fuzzy analysis results indicated that optimum results for bias voltage, bias frequency, deposition pressure, gas composition for the DLC thin films are -50 V, 6 kHz, 4 μbar and 60:40 % respectively.

  2. The evaluation of supply chain performance in the Oil Products Distribution Company, using information technology indicators and fuzzy TOPSIS technique

    Directory of Open Access Journals (Sweden)

    Daryosh Mohamadi Janaki

    2018-08-01

    Full Text Available Information Technology (IT plays an essential role on development of effective supply chain planning and it can improve the supply chain performance, either directly or indirectly. As a national industry, the National Iranian Oil Products Distribution Company involves a large number of organizations within its supply chain. Therefore, this descriptive-survey uses information sharing indicators, fuzzy TOPSIS technique based on managers and expert opinions to evaluate and to rank some oil products distribution companies. Data are analyzed and the results show that Oil Products Distribution Company of Chaharmahal and Bakhtiari received the highest rank and Farsan maintained the lowest rank compared with other regional companies.

  3. Brain vascular image segmentation based on fuzzy local information C-means clustering

    Science.gov (United States)

    Hu, Chaoen; Liu, Xia; Liang, Xiao; Hui, Hui; Yang, Xin; Tian, Jie

    2017-02-01

    Light sheet fluorescence microscopy (LSFM) is a powerful optical resolution fluorescence microscopy technique which enables to observe the mouse brain vascular network in cellular resolution. However, micro-vessel structures are intensity inhomogeneity in LSFM images, which make an inconvenience for extracting line structures. In this work, we developed a vascular image segmentation method by enhancing vessel details which should be useful for estimating statistics like micro-vessel density. Since the eigenvalues of hessian matrix and its sign describes different geometric structure in images, which enable to construct vascular similarity function and enhance line signals, the main idea of our method is to cluster the pixel values of the enhanced image. Our method contained three steps: 1) calculate the multiscale gradients and the differences between eigenvalues of Hessian matrix. 2) In order to generate the enhanced microvessels structures, a feed forward neural network was trained by 2.26 million pixels for dealing with the correlations between multi-scale gradients and the differences between eigenvalues. 3) The fuzzy local information c-means clustering (FLICM) was used to cluster the pixel values in enhance line signals. To verify the feasibility and effectiveness of this method, mouse brain vascular images have been acquired by a commercial light-sheet microscope in our lab. The experiment of the segmentation method showed that dice similarity coefficient can reach up to 85%. The results illustrated that our approach extracting line structures of blood vessels dramatically improves the vascular image and enable to accurately extract blood vessels in LSFM images.

  4. 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.

  5. Fuzzy model predictive control algorithm applied in nuclear power plant

    International Nuclear Information System (INIS)

    Zuheir, Ahmad

    2006-01-01

    The aim of this paper is to design a predictive controller based on a fuzzy model. The Takagi-Sugeno fuzzy model with an Adaptive B-splines neuro-fuzzy implementation is used and incorporated as a predictor in a predictive controller. An optimization approach with a simplified gradient technique is used to calculate predictions of the future control actions. In this approach, adaptation of the fuzzy model using dynamic process information is carried out to build the predictive controller. The easy description of the fuzzy model and the easy computation of the gradient sector during the optimization procedure are the main advantages of the computation algorithm. The algorithm is applied to the control of a U-tube steam generation unit (UTSG) used for electricity generation. (author)

  6. Evaluation and prioritization of rice production practices and constraints under temperate climatic conditions using Fuzzy Analytical Hierarchy Process (FAHP

    Directory of Open Access Journals (Sweden)

    Shabir A. Mir

    2016-12-01

    Full Text Available Due to overwhelming complex and vague nature of interactions between multiple factors describing agriculture, Multi-Criteria Decision Making (MCDM methods are widely used from farm to fork to facilitate systematic and transparent decision support, figure out multiple decision outcomes and equip decision maker with confident decision choices in order to choose best alternative. This research proposes a Fuzzy Analytical Hierarchy Process (FAHP based decision support to evaluate and prioritize important factors of rice production practices and constraints under temperate climatic conditions and provides estimate of weightings, which measure relative importance of critical factors of the crop under biotic, abiotic, socio-economic and technological settings. The results envisage that flood, drought, water logging, late sali, temperature and rainfall are important constraints. However, regulating transplantation time; maintaining planting density; providing training to the educated farmers; introducing high productive varieties like Shalimar Rice-1 and Jhelum; better management of nutrients, weeds and diseases are most important opportunities to enhance rice production in the region. Therefore, the proposed system supplements farmers with precise decision information about important rice production practices, opportunities and constraints.

  7. Evaluation and prioritization of rice production practices and constraints under temperate climatic conditions using Fuzzy Analytical Hierarchy Process (FAHP)

    International Nuclear Information System (INIS)

    Mir, S.A.; Padma, T.

    2016-01-01

    Due to overwhelming complex and vague nature of interactions between multiple factors describing agriculture, Multi-Criteria Decision Making (MCDM) methods are widely used from farm to fork to facilitate systematic and transparent decision support, figure out multiple decision outcomes and equip decision maker with confident decision choices in order to choose best alternative. This research proposes a Fuzzy Analytical Hierarchy Process (FAHP) based decision support to evaluate and prioritize important factors of rice production practices and constraints under temperate climatic conditions and provides estimate of weightings, which measure relative importance of critical factors of the crop under biotic, abiotic, socio-economic and technological settings. The results envisage that flood, drought, water logging, late sali, temperature and rainfall are important constraints. However, regulating transplantation time; maintaining planting density; providing training to the educated farmers; introducing high productive varieties like Shalimar Rice-1 and Jhelum; better management of nutrients, weeds and diseases are most important opportunities to enhance rice production in the region. Therefore, the proposed system supplements farmers with precise decision information about important rice production practices, opportunities and constraints.

  8. Evaluation and prioritization of rice production practices and constraints under temperate climatic conditions using Fuzzy Analytical Hierarchy Process (FAHP)

    Energy Technology Data Exchange (ETDEWEB)

    Mir, S.A.; Padma, T.

    2016-07-01

    Due to overwhelming complex and vague nature of interactions between multiple factors describing agriculture, Multi-Criteria Decision Making (MCDM) methods are widely used from farm to fork to facilitate systematic and transparent decision support, figure out multiple decision outcomes and equip decision maker with confident decision choices in order to choose best alternative. This research proposes a Fuzzy Analytical Hierarchy Process (FAHP) based decision support to evaluate and prioritize important factors of rice production practices and constraints under temperate climatic conditions and provides estimate of weightings, which measure relative importance of critical factors of the crop under biotic, abiotic, socio-economic and technological settings. The results envisage that flood, drought, water logging, late sali, temperature and rainfall are important constraints. However, regulating transplantation time; maintaining planting density; providing training to the educated farmers; introducing high productive varieties like Shalimar Rice-1 and Jhelum; better management of nutrients, weeds and diseases are most important opportunities to enhance rice production in the region. Therefore, the proposed system supplements farmers with precise decision information about important rice production practices, opportunities and constraints.

  9. Modelling and Analysis of Automobile Vibration System Based on Fuzzy Theory under Different Road Excitation Information

    Directory of Open Access Journals (Sweden)

    Xue-wen Chen

    2018-01-01

    Full Text Available A fuzzy increment controller is designed aimed at the vibration system of automobile active suspension with seven degrees of freedom (DOF. For decreasing vibration, an active control force is acquired by created Proportion-Integration-Differentiation (PID controller. The controller’s parameters are adjusted by a fuzzy increment controller with self-modifying parameters functions, which adopts the deviation and its rate of change of the body’s vertical vibration velocity and the desired value in the position of the front and rear suspension as the input variables based on 49 fuzzy control rules. Adopting Simulink, the fuzzy increment controller is validated under different road excitation, such as the white noise input with four-wheel correlation in time-domain, the sinusoidal input, and the pulse input of C-grade road surface. The simulation results show that the proposed controller can reduce obviously the vehicle vibration compared to other independent control types in performance indexes, such as, the root mean square value of the body’s vertical vibration acceleration, pitching, and rolling angular acceleration.

  10. Mathematical modeling and fuzzy availability analysis for serial processes in the crystallization system of a sugar plant

    Science.gov (United States)

    Aggarwal, Anil Kr.; Kumar, Sanjeev; Singh, Vikram

    2017-03-01

    The binary states, i.e., success or failed state assumptions used in conventional reliability are inappropriate for reliability analysis of complex industrial systems due to lack of sufficient probabilistic information. For large complex systems, the uncertainty of each individual parameter enhances the uncertainty of the system reliability. In this paper, the concept of fuzzy reliability has been used for reliability analysis of the system, and the effect of coverage factor, failure and repair rates of subsystems on fuzzy availability for fault-tolerant crystallization system of sugar plant is analyzed. Mathematical modeling of the system is carried out using the mnemonic rule to derive Chapman-Kolmogorov differential equations. These governing differential equations are solved with Runge-Kutta fourth-order method.

  11. Sorting of pistachio nuts using image processing techniques and an adaptive neural-fuzzy inference system

    Directory of Open Access Journals (Sweden)

    A. R Abdollahnejad Barough

    2016-04-01

    Full Text Available Introduction: Pistachio nut is one of the most important agricultural products of Iran and it is priced due to the quality and type. One of the significant factors of pistachio cost is its type in terms of shell. Filled split pistachio nut has the most quality and is utilized as nuts, while the closed shell type has lower cost, at the same time is economically efficient in food industry such as confectionery. Now, pistachio sorting is performed usually by human and sometimes using electromechanical apparatuses. Classification of pistachio by human is time consuming and is done with an unacceptable accuracy, on the other hand, electromechanical and electro optical apparatuses damages pistachio because the mechanism used in them while separating. So, the need to develop automated systems that could be implemented by intelligent ways is evident to increase the speed and accuracy of classification. Materials and Methods: In this study, 300 samples of pistachios contains 100 Filled split, 100 Filled non-split and 100 split blank nuts ones are used. The training set consisted of 60 samples of each type of opened nuts, closed and empty opened shell nuts a total of 180 samples and the evaluation set consisted of 40 samples of each type of opened shell, closed shell and empty opened shell nuts a total of 120 samples. The principle of this study is implemented in two steps: 1 sample imaging and image processing to extract features 2 fuzzy network design based on the characteristics of data and training. To select useful features from the hypothesis, C4.5 decision tree is used. C4.5 algorithm makes a greedy top to bottom search on the hypothesis, and is made by the question what feature must be at the root of the tree. By the help of statistical methods, extracted features from the images were prioritized and the most appropriate features for classification of training set were selected. The algorithm chooses the best features as their number is minimum

  12. Selection of optimum maintenance strategies based on a fuzzy analytic hierarchy process

    Directory of Open Access Journals (Sweden)

    Aida Azizi

    2014-05-01

    Full Text Available This paper presents an empirical investigation to rank different factors influencing on maintenance strategies on Iranian oil terminals’ company. The study determines four main factors, production quality, reliability, cost and safety. Using fuzzy analytical process, the study determines various factors associated with each main factor and ranks them by performing pair-wise comparisons. The results indicate that reliability ranks first (0.255, followed by production quality (0.252, cost (0.25 and safety (0.244. In terms of reliability, the best utilization of resources is number one priority followed by increase access to maintenance tools, reduction in production interruption are among the most important issues. In terms of production quality, reduction in system failure as well as reworks is the most important factors followed by customer satisfaction and defects. In terms of cost items, ease of access to accessories and consulting are important factors followed by necessary software, hardware and training programs. Finally, in terms of safety factors, external, internal and employee services are the most important issues, which are needed to be considered.

  13. New neuro-fuzzy system-based holey polymer fibers drawing process

    Science.gov (United States)

    Mohammed Salim, Omar Nameer

    2017-10-01

    Furnace temperature (T), draw tension (TE), and draw ratio (Dr) are the main parameters that could directly affect holey polymer fiber (HPF) production during the drawing stage. Therefore, a suitable mechanism to control (T), (TE), and (Dr) is required to enhance the HPF production process. The conventional approaches, such as observation and tuning technique, experience many difficulties in realizing the accurate values of (T), (TE), and (Dr) in addition to being expensive and time consuming. Therefore, an artificial intelligence model using the adaptive neuro-fuzzy system (ANFIS) method is proposed as an effective solution to achieve an accurate value of the main parameters that affect HPF drawing. Three ANFIS models are developed and tested to determine which one has the best performance for emulating the operation of HPF drawing tower. The ANFIS model with a gbell MF provides a better performance than Gaussian MF ANFIS model and triangular MF ANFIS model in terms of lower mean absolute error and mean square error. Furthermore, the proposed gbell MF model achieved the highest Q-Q response, which indicates the excellent performance of this model.

  14. Power substation location selection using fuzzy analytic hierarchy process and PROMETHEE: A case study from Bangladesh

    International Nuclear Information System (INIS)

    Kabir, Golam; Sumi, Razia Sultana

    2014-01-01

    Electromagnetic radiations emanating from the high voltage lines and substations pose serious adverse health consequences to living beings. As a result, selection of power substation location is an important strategic decision-making problem for both public and private sectors. In general, many conflicting factors affect the appropriate substation location selection problem which adheres to uncertain and imprecise data. In this paper, a simple, systematic and logical scientific approach is structured to evaluate power substation location through integrating Fuzzy Analytical Hierarchy Process (FAHP) with the Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE). The proposed integrated approach provides more realistic and reliable results, and facilitates the decision-maker to handle multiple contradictory decision perspectives through eliminating the limitations of FAHP and PROMETHEE methods. To accredit the proposed model, it is implemented in a power substation location selection problem in Bangladesh. - Highlights: • Integrate the strengths and eliminate the limitations of FAHP and PROMETHEE. • Consider social, technological, economic, environmental, and site characteristics criteria. • Determine the weights of criteria and sub-criteria using FAHP. • Present both PROMETHEE I and PROMETHEE II ranking. • Enable graphical representation of the alternatives and criteria by GAIA plane

  15. Effective factors on optimizing banks’ balance sheet using fuzzy analytical hierarchy process

    Directory of Open Access Journals (Sweden)

    Shoja Rezaei

    2013-11-01

    Full Text Available Every bank seeks methods to optimize its assets and liabilities, thus the main subject is managing assets-liabilities in the balance sheet and the main question is by which factor banks will be enabled to have an optimized combination of assets and liabilities in a common level of risk to get the most return. This case study is dedicated to Refah bank and is an applicable study. The data has collected from the headquarter by a questionnaire and finally effective factors weight on optimizing bank balance sheet determined by using Fuzzy analytical hierarchy process. Results showed that revenue has more effect on optimizing for %39.5 and also loan to deposit ratio for %.74, regarding revenue as a symbol of efficiency in banks, it seems to be the most important factor and goal in banking industry. Furthermore banks need to have some liquidity to respond customers demand to cover one of the most important risks of banking. This factor importance determined to be %18 in Refah Bank by using model and experts view.

  16. Evaluation of challenges of wood imports to Iran using Fuzzy Delphi Analytical Hierarchy Process

    Directory of Open Access Journals (Sweden)

    amin arian

    2017-08-01

    Full Text Available Abstract:Considering the increasing consumption of wood and wood products in Iran and limited domestic sources of wood and shortage of wood raw material in Iran, wood raw material imports is a solution for Iranian developing wood industries' wood procurement.But, wood imports to Iran, always faced with a lot of challenges. The aim of this research is to determine and evaluate the challenges in the way of wood imports to Iran. The research method used in this study is a descriptive-analytic method. The analytic method used in the study to evaluate the challenges is the Fuzzy Delphi Analytical Hierarchy Process (FDAHP. First the findings of previous researches in the field and the literature were studied and doing interviews with industry experts, the challenges in the way of wood imports to Iran were extracted and classified in 5 groups and 35 factors and were evaluated.The results shows that in the first level (groups the regulation, economic, politic, infrastructure and management groups have the most importance respectively. In second level (challenges, plant protection regulations have the most importance. After that, exchange rate tolerance, oil income, banking support and GDP have most importance respectively.

  17. Optimal evaluation of infectious medical waste disposal companies using the fuzzy analytic hierarchy process

    International Nuclear Information System (INIS)

    Ho, Chao Chung

    2011-01-01

    Ever since Taiwan's National Health Insurance implemented the diagnosis-related groups payment system in January 2010, hospital income has declined. Therefore, to meet their medical waste disposal needs, hospitals seek suppliers that provide high-quality services at a low cost. The enactment of the Waste Disposal Act in 1974 had facilitated some improvement in the management of waste disposal. However, since the implementation of the National Health Insurance program, the amount of medical waste from disposable medical products has been increasing. Further, of all the hazardous waste types, the amount of infectious medical waste has increased at the fastest rate. This is because of the increase in the number of items considered as infectious waste by the Environmental Protection Administration. The present study used two important findings from previous studies to determine the critical evaluation criteria for selecting infectious medical waste disposal firms. It employed the fuzzy analytic hierarchy process to set the objective weights of the evaluation criteria and select the optimal infectious medical waste disposal firm through calculation and sorting. The aim was to propose a method of evaluation with which medical and health care institutions could objectively and systematically choose appropriate infectious medical waste disposal firms.

  18. Information Warfare-Worthy Jamming Attack Detection Mechanism for Wireless Sensor Networks Using a Fuzzy Inference System

    Directory of Open Access Journals (Sweden)

    Sudip Misra

    2010-04-01

    Full Text Available The proposed mechanism for jamming attack detection for wireless sensor networks is novel in three respects: firstly, it upgrades the jammer to include versatile military jammers; secondly, it graduates from the existing node-centric detection system to the network-centric system making it robust and economical at the nodes, and thirdly, it tackles the problem through fuzzy inference system, as the decision regarding intensity of jamming is seldom crisp. The system with its high robustness, ability to grade nodes with jamming indices, and its true-detection rate as high as 99.8%, is worthy of consideration for information warfare defense purposes.

  19. Transparent predictive modelling of the twin screw granulation process using a compensated interval type-2 fuzzy system.

    Science.gov (United States)

    AlAlaween, Wafa' H; Khorsheed, Bilal; Mahfouf, Mahdi; Gabbott, Ian; Reynolds, Gavin K; Salman, Agba D

    2018-03-01

    In this research, a new systematic modelling framework which uses machine learning for describing the granulation process is presented. First, an interval type-2 fuzzy model is elicited in order to predict the properties of the granules produced by twin screw granulation (TSG) in the pharmaceutical industry. Second, a Gaussian mixture model (GMM) is integrated in the framework in order to characterize the error residuals emanating from the fuzzy model. This is done to refine the model by taking into account uncertainties and/or any other unmodelled behaviour, stochastic or otherwise. All proposed modelling algorithms were validated via a series of Laboratory-scale experiments. The size of the granules produced by TSG was successfully predicted, where most of the predictions fit within a 95% confidence interval. Copyright © 2017 Elsevier B.V. All rights reserved.

  20. Factors controlling groundwater quality in the Yeonjegu District of Busan City, Korea, using the hydrogeochemical processes and fuzzy GIS.

    Science.gov (United States)

    Venkatramanan, Senapathi; Chung, Sang Yong; Selvam, Sekar; Lee, Seung Yeop; Elzain, Hussam Eldin

    2017-10-01

    The hydrogeochemical processes and fuzzy GIS techniques were used to evaluate the groundwater quality in the Yeonjegu district of Busan Metropolitan City, Korea. The highest concentrations of major ions were mainly related to the local geology. The seawater intrusion into the river water and municipal contaminants were secondary contamination sources of groundwater in the study area. Factor analysis represented the contamination sources of the mineral dissolution of the host rocks and domestic influences. The Gibbs plot exhibited that the major ions were derived from the rock weathering condition. Piper's trilinear diagram showed that the groundwater quality was classified into five types of CaHCO 3 , NaHCO 3 , NaCl, CaCl 2 , and CaSO 4 types in that order. The ionic relationship and the saturation mineral index of the ions indicated that the evaporation, dissolution, and precipitation processes controlled the groundwater chemistry. The fuzzy GIS map showed that highly contaminated groundwater occurred in the northeastern and the central parts and that the groundwater of medium quality appeared in most parts of the study area. It suggested that the groundwater quality of the study area was influenced by local geology, seawater intrusion, and municipal contaminants. This research clearly demonstrated that the geochemical analyses and fuzzy GIS method were very useful to identify the contaminant sources and the location of good groundwater quality.

  1. Multi-Responses Optimization Of Edm Sinking Process Of Aisi D2 Tool Steel Using Taguchi Grey–Fuzzy Method

    Directory of Open Access Journals (Sweden)

    Bobby Oedy Pramoedyo Soepangkat

    2014-12-01

    Full Text Available Rough machining with Electro Discharge Machining (EDM process gives a large Material Removal Rate (MRR and high Surface Roughness (SR, while finish machining gives low SR and very slow MRR. In this study, Taguchi method coupled with Grey Relational Analysis (GRA and fuzzy logic has been applied for optimization of multiple performance characteristics. The EDM machining parameters (gap voltage, pulse current, on time and duty factor are optimized with considerations of multiple performance characteristics, i.e., MRR and SR. The quality characteristic of MRR is larger-is-better, while the quality characteristic of SR is smaller-is-better. Based on Taguchi method, an L18 mixed-orthogonal array is selected for the experiments. By using the combination of GRA and fuzzy logic, the optimization of complicated multiple performance characteristics was transformed into the optimization of a single response performance index. The most significant machining parameters which affect the multiple performance characteristics were gapvoltage and pulse current. Experimental results have also shown that machining performance characteristics of EDM process can be improved effectively through the combination of Taguchi method, GRA and fuzzy logic.

  2. Information fusion in signal and image processing major probabilistic and non-probabilistic numerical approaches

    CERN Document Server

    Bloch, Isabelle

    2010-01-01

    The area of information fusion has grown considerably during the last few years, leading to a rapid and impressive evolution. In such fast-moving times, it is important to take stock of the changes that have occurred. As such, this books offers an overview of the general principles and specificities of information fusion in signal and image processing, as well as covering the main numerical methods (probabilistic approaches, fuzzy sets and possibility theory and belief functions).

  3. Landslide susceptibility mapping by combining the three methods Fuzzy Logic, Frequency Ratio and Analytical Hierarchy Process in Dozain basin

    Directory of Open Access Journals (Sweden)

    E. Tazik

    2014-10-01

    Full Text Available Landslides are among the most important natural hazards that lead to modification of the environment. Therefore, studying of this phenomenon is so important in many areas. Because of the climate conditions, geologic, and geomorphologic characteristics of the region, the purpose of this study was landslide hazard assessment using Fuzzy Logic, frequency ratio and Analytical Hierarchy Process method in Dozein basin, Iran. At first, landslides occurred in Dozein basin were identified using aerial photos and field studies. The influenced landslide parameters that were used in this study including slope, aspect, elevation, lithology, precipitation, land cover, distance from fault, distance from road and distance from river were obtained from different sources and maps. Using these factors and the identified landslide, the fuzzy membership values were calculated by frequency ratio. Then to account for the importance of each of the factors in the landslide susceptibility, weights of each factor were determined based on questionnaire and AHP method. Finally, fuzzy map of each factor was multiplied to its weight that obtained using AHP method. At the end, for computing prediction accuracy, the produced map was verified by comparing to existing landslide locations. These results indicate that the combining the three methods Fuzzy Logic, Frequency Ratio and Analytical Hierarchy Process method are relatively good estimators of landslide susceptibility in the study area. According to landslide susceptibility map about 51% of the occurred landslide fall into the high and very high susceptibility zones of the landslide susceptibility map, but approximately 26 % of them indeed located in the low and very low susceptibility zones.

  4. Proprioceptive information processing in schizophrenia

    DEFF Research Database (Denmark)

    Arnfred, Sidse M H

    of the left somatosensory cortex and it was suggested to be in accordance with two theories of schizophrenic information processing: the theory of deficiency of corollary discharge and the theory of weakening of the influence of past regularities. No gating deficiency was observed and the imprecision...... Rado (1890-1972) suggested that one of two un-reducible deficits in schizophrenia was a disorder of proprioception. Exploration of proprioceptive information processing is possible through the measurement of evoked and event related potentials. Event related EEG can be analyzed as conventional time...... and amplitude attenuation was not a general phenomenon across the entire brain response. Summing up, in support of Rado's hypothesis, schizophrenia spectrum patients demonstrated abnormalities in proprioceptive information processing. Future work needs to extend the findings in larger un-medicated, non...

  5. An Intelligent Information Retrieval Approach Based on Two Degrees of Uncertainty Fuzzy Ontology

    OpenAIRE

    Maryam Hourali; Gholam Ali Montazer

    2011-01-01

    In spite of the voluminous studies in the field of intelligent retrieval systems, effective retrieving of information has been remained an important unsolved problem. Implementations of different conceptual knowledge in the information retrieval process such as ontology have been considered as a solution to enhance the quality of results. Furthermore, the conceptual formalism supported by typical ontology may not be sufficient to represent uncertainty information due to the lack of clear-cut ...

  6. Application of fuzzy methods in tunnelling

    Directory of Open Access Journals (Sweden)

    Ľudmila Tréfová

    2011-12-01

    Full Text Available Full-face tunnelling machines were used for the tunnel construction in Slovakia for boring of the exploratory galleries of highwaytunnels Branisko and Višňové-Dubná skala. A monitoring system of boring process parameters was installed on the tunnelling machinesand the acquired outcomes were processed by several theoretical approaches. Method IKONA was developed for the determination ofchanges in the rock mass strength characteristics in the line of exploratory gallery. Individual geological sections were evaluated bythe descriptive statistics and the TBM performance was evaluated by the fuzzy method. The paper informs on the procedure of the designof fuzzy models and their verification.

  7. A subjective and objective fuzzy-based analytical hierarchy process model for prioritization of lean product development practices

    Directory of Open Access Journals (Sweden)

    Daniel O. Aikhuele

    2017-06-01

    Full Text Available In this paper, a subjective and objective fuzzy-based Analytical Hierarchy Process (AHP model is proposed. The model which is based on a newly defined evaluation matrix replaces the fuzzy comparison matrix (FCM in the traditional fuzzy AHP model, which has been found ineffective and time-consuming when criteria/alternatives are increased. The main advantage of the new model is that it is straightforward and completely eliminates the repetitive adjustment of data that is common with the FCM in traditional AHP model. The model reduces the complete dependen-cy on human judgment in prioritization assessment since the weights values are solved automati-cally using the evaluation matrix and the modified priority weight formula in the proposed mod-el. By virtue of a numerical case study, the model is successfully applied in the determination of the implementation priorities of lean practices for a product development environment and com-pared with similar computational methods in the literature.

  8. 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.

  9. Classicality of quantum information processing

    International Nuclear Information System (INIS)

    Poulin, David

    2002-01-01

    The ultimate goal of the classicality program is to quantify the amount of quantumness of certain processes. Here, classicality is studied for a restricted type of process: quantum information processing (QIP). Under special conditions, one can force some qubits of a quantum computer into a classical state without affecting the outcome of the computation. The minimal set of conditions is described and its structure is studied. Some implications of this formalism are the increase of noise robustness, a proof of the quantumness of mixed state quantum computing, and a step forward in understanding the very foundation of QIP

  10. Interfirm collaboration in the fuzzy front-end of the innovation process - Exploring new forms of collaboration

    DEFF Research Database (Denmark)

    Bergenholtz, Carsten; Jørgensen, Jacob Høj; Goduscheit, Rene Chester

    The objective of this paper is to elaborate on the differentiating characteristics between intra-firm and inter-firm innovation projects in the Fuzzy Front-End (FFE) of the innovation process. Focus is on management methods of the collaboration and the CEO-commitment to the project. The main point...... is the balance between to types of structure, namely: Structure of Content and structure of Process.  The right balance of these two kinds of structure will ensure that the focal company benefits from the creative input from the inter-organisational innovation partners and that they stay committed...

  11. Process Monitoring by combining several signal-analysis results using fuzzy logic

    International Nuclear Information System (INIS)

    Schoonwelle, H.; Van der Hagen, T.H.J.J.; Hoogenboom, J.E.

    1996-01-01

    In order to improve reliability in detecting anomalies in nuclear power plant performance, a method is presented which is based on acquiring various characteristics of signal data using autoregressive, wavelet and fractal-analysis techniques. These characteristics are combined using a decision making approach based on fuzzy logic. This approach is able to detect and distinguish several system states

  12. Design of a fuzzy ranking system for admission processes in higher ...

    African Journals Online (AJOL)

    specific knowledge, as well as the knowledge and analytical skills of one or more human experts and reasons with ... In this paper we introduced fuzzy harming distance function into candidates ranking and implemented it with Java Netbean IDE 6.0.

  13. Tool vibration detection with eddy current sensors in machining process and computation of stability lobes using fuzzy classifiers

    Science.gov (United States)

    Devillez, Arnaud; Dudzinski, Daniel

    2007-01-01

    Today the knowledge of a process is very important for engineers to find optimal combination of control parameters warranting productivity, quality and functioning without defects and failures. In our laboratory, we carry out research in the field of high speed machining with modelling, simulation and experimental approaches. The aim of our investigation is to develop a software allowing the cutting conditions optimisation to limit the number of predictive tests, and the process monitoring to prevent any trouble during machining operations. This software is based on models and experimental data sets which constitute the knowledge of the process. In this paper, we deal with the problem of vibrations occurring during a machining operation. These vibrations may cause some failures and defects to the process, like workpiece surface alteration and rapid tool wear. To measure on line the tool micro-movements, we equipped a lathe with a specific instrumentation using eddy current sensors. Obtained signals were correlated with surface finish and a signal processing algorithm was used to determine if a test is stable or unstable. Then, a fuzzy classification method was proposed to classify the tests in a space defined by the width of cut and the cutting speed. Finally, it was shown that the fuzzy classification takes into account of the measurements incertitude to compute the stability limit or stability lobes of the process.

  14. 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.

  15. Efficiency of cellular information processing

    International Nuclear Information System (INIS)

    Barato, Andre C; Hartich, David; Seifert, Udo

    2014-01-01

    We show that a rate of conditional Shannon entropy reduction, characterizing the learning of an internal process about an external process, is bounded by the thermodynamic entropy production. This approach allows for the definition of an informational efficiency that can be used to study cellular information processing. We analyze three models of increasing complexity inspired by the Escherichia coli sensory network, where the external process is an external ligand concentration jumping between two values. We start with a simple model for which ATP must be consumed so that a protein inside the cell can learn about the external concentration. With a second model for a single receptor we show that the rate at which the receptor learns about the external environment can be nonzero even without any dissipation inside the cell since chemical work done by the external process compensates for this learning rate. The third model is more complete, also containing adaptation. For this model we show inter alia that a bacterium in an environment that changes at a very slow time-scale is quite inefficient, dissipating much more than it learns. Using the concept of a coarse-grained learning rate, we show for the model with adaptation that while the activity learns about the external signal the option of changing the methylation level increases the concentration range for which the learning rate is substantial. (paper)

  16. Information processing. [in human performance

    Science.gov (United States)

    Wickens, Christopher D.; Flach, John M.

    1988-01-01

    Theoretical models of sensory-information processing by the human brain are reviewed from a human-factors perspective, with a focus on their implications for aircraft and avionics design. The topics addressed include perception (signal detection and selection), linguistic factors in perception (context provision, logical reversals, absence of cues, and order reversals), mental models, and working and long-term memory. Particular attention is given to decision-making problems such as situation assessment, decision formulation, decision quality, selection of action, the speed-accuracy tradeoff, stimulus-response compatibility, stimulus sequencing, dual-task performance, task difficulty and structure, and factors affecting multiple task performance (processing modalities, codes, and stages).

  17. Principles of neural information processing

    CERN Document Server

    Seelen, Werner v

    2016-01-01

    In this fundamental book the authors devise a framework that describes the working of the brain as a whole. It presents a comprehensive introduction to the principles of Neural Information Processing as well as recent and authoritative research. The books´ guiding principles are the main purpose of neural activity, namely, to organize behavior to ensure survival, as well as the understanding of the evolutionary genesis of the brain. Among the developed principles and strategies belong self-organization of neural systems, flexibility, the active interpretation of the world by means of construction and prediction as well as their embedding into the world, all of which form the framework of the presented description. Since, in brains, their partial self-organization, the lifelong adaptation and their use of various methods of processing incoming information are all interconnected, the authors have chosen not only neurobiology and evolution theory as a basis for the elaboration of such a framework, but also syst...

  18. Research on Inferring ELECTRE-III’s Parameters with Fuzzy information and A Case on Naval Gun Weapon System Integration

    Directory of Open Access Journals (Sweden)

    Sun Shi Yan

    2016-01-01

    Full Text Available Multiple attributes decision making (MADM method is an important measure for system integration. Robustness analysis on MADM is a hotspot in these years which wins academe’s great attention, and is supposed to be an effective way when countering imperfect information. Setting parameters in ELECTRE-III’s is a vital and difficult step. In this paper, a method of inferring ELECTRE-III’s parameters with fuzzy information based on robustness analysis is presented. First, ELECTRE-III is transformed into a continuous smooth function of each parameter vector. Then, robustness analysis structure and a parameters inferring algorithm are provided by maximizing robustness margin based on mathematics programming. Moreover, how to resolve the programming problem is also discussed. At last, a illustrative example of Naval Gun Weapon System Integration is put forward.

  19. 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.

  20. On the mathematics of fuzziness

    Energy Technology Data Exchange (ETDEWEB)

    Chulichkov, A.I.; Chulichkova, N.M.; Pyt`ev, Y. P.; Smolnik, L.

    1994-12-31

    The problem of the minimax linear interpretation of stochastic measurements with fuzzy conditions on values of the object`s parameters is considered. The result of a measurement interpretation is the fuzzy element (u, h, alpha, mu(.,.,.)), where u is the object`s parameter estimation, h is the estimation accuracy and alpha is the reliability of interpretation, mu is the characteristic function of a fuzzy element. Reliability is the characteristic of the agreement between fuzzy a priori information and measuring data. The information on the values of the parameters of an object under investigation is interactively submitted to the computer.

  1. An analytical hierarchy process and fuzzy inference system tsukamoto for production planning: a review and conceptual research

    Directory of Open Access Journals (Sweden)

    Abdul Talib Bon

    2015-03-01

    Full Text Available Production planning is an area that is very important on the corporate strategy-level decision-making, especially in the manufacturing companies. The problems that often arise in the production planning are the factors that affect the decline of production and uncertainty that often complicate the decision-making in the production process. These factors are derived from the company’s internal and external factors. The purpose of this study is to introduce the Analytical Hierarchy Process as an effective method that can help to determine the priority of the production factors, so as to facilitate and accelerate decision-making. Other than the AHP methods, this paper will introduce the Tsukamoto Fuzzy Inference System as a method that can help to determine how much product to be manufactured by the company using the variables in the form of fuzzy numbers. These methods hopefully can assist in a better decision making process in the production process and manufacturing generally.

  2. Intuitionistic fuzzy aggregation and clustering

    CERN Document Server

    Xu, Zeshui

    2012-01-01

    This book offers a systematic introduction to the clustering algorithms for intuitionistic fuzzy values, the latest research results in intuitionistic fuzzy aggregation techniques, the extended results in interval-valued intuitionistic fuzzy environments, and their applications in multi-attribute decision making, such as supply chain management, military system performance evaluation, project management, venture capital, information system selection, building materials classification, and operational plan assessment, etc.

  3. PENENTUAN PRODUK OLAHAN APEL UNGGULAN MENGGUNAKAN TEKNIK FUZZY NON NUMERIK AN ANALISIS STRUKTUR SERTA POLA PEMBINAAN KELEMBAGAAN [Determination Prosprctive Appe processing product Using Non-Numeric Fuzzy Method, Analyze Institutional Structure and Develompent Model

    Directory of Open Access Journals (Sweden)

    Imam Santoso 1

    2001-08-01

    Full Text Available Apple and its processing product is one of prospective commodities in Malang, East Java. The article discussed application of fuzzy non-numerik decision making to select prospective apple processing product, analyse institutional structure using ISM method and determine development model using AHP method. The research result showed apple dodol selected as the most prospective product with high category elements of entrepreneur, corporation, and high ediucation are as independent elements; and partnership (46% selected as model of institutional estabilishment.

  4. The Application of Fuzzy Analytical Network Process (FANP Approach for Appropriate Location Selection of Health Centers: case study in ramsar cite

    Directory of Open Access Journals (Sweden)

    Dariush Mohammadi Zanjirani

    2012-06-01

    Full Text Available Background: Appropriate location selection for health Services unites is a Strategic decision which is based on gathering information and also exact analysis of related alternatives. It's clear that result of this decision is really important and will led to long time improvement in all dimensions including economic, social, and etc. Otherwise, the most studies of location have done in background manufacturing rather than service area and there are just few articles which have focused in field of healthcare. This study attempted to solve this stock of researches. Methods: By using an almost comprehensive literatures review, objective and subjective criteria are identified. After finalizing criteria's, Are used from decision-makers’ assessments for collection data. Fuzzy Analytical Network Process is used for analyzing the data. Results: The finding indicates that the criteria's of proposed model are high validity and reliability for appropriate location selection of Health Centers. Conclusion: The analyzing of data indicates that lamtar locate is selected appropriate location.

  5. Implementation of Steiner point of fuzzy set.

    Science.gov (United States)

    Liang, Jiuzhen; Wang, Dejiang

    2014-01-01

    This paper deals with the implementation of Steiner point of fuzzy set. Some definitions and properties of Steiner point are investigated and extended to fuzzy set. This paper focuses on establishing efficient methods to compute Steiner point of fuzzy set. Two strategies of computing Steiner point of fuzzy set are proposed. One is called linear combination of Steiner points computed by a series of crisp α-cut sets of the fuzzy set. The other is an approximate method, which is trying to find the optimal α-cut set approaching the fuzzy set. Stability analysis of Steiner point of fuzzy set is also studied. Some experiments on image processing are given, in which the two methods are applied for implementing Steiner point of fuzzy image, and both strategies show their own advantages in computing Steiner point of fuzzy set.

  6. Adding memory processing behaviors to the fuzzy behaviorist-based navigation of mobile robots

    Energy Technology Data Exchange (ETDEWEB)

    Pin, F.G.; Bender, S.R.

    1996-05-01

    Most fuzzy logic-based reasoning schemes developed for robot control are fully reactive, i.e., the reasoning modules consist of fuzzy rule bases that represent direct mappings from the stimuli provided by the perception systems to the responses implemented by the motion controllers. Due to their totally reactive nature, such reasoning systems can encounter problems such as infinite loops and limit cycles. In this paper, we proposed an approach to remedy these problems by adding a memory and memory-related behaviors to basic reactive systems. Three major types of memory behaviors are addressed: memory creation, memory management, and memory utilization. These are first presented, and examples of their implementation for the recognition of limit cycles during the navigation of an autonomous robot in a priori unknown environments are then discussed.

  7. A NOISE ADAPTIVE FUZZY EQUALIZATION METHOD FOR PROCESSING SOLAR EXTREME ULTRAVIOLET IMAGES

    Energy Technology Data Exchange (ETDEWEB)

    Druckmueller, M., E-mail: druckmuller@fme.vutbr.cz [Institute of Mathematics, Faculty of Mechanical Engineering, Brno University of Technology, Technicka 2, 616 69 Brno (Czech Republic)

    2013-08-15

    A new image enhancement tool ideally suited for the visualization of fine structures in extreme ultraviolet images of the corona is presented in this paper. The Noise Adaptive Fuzzy Equalization method is particularly suited for the exceptionally high dynamic range images from the Atmospheric Imaging Assembly instrument on the Solar Dynamics Observatory. This method produces artifact-free images and gives significantly better results than methods based on convolution or Fourier transform which are often used for that purpose.

  8. 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.

  9. Advanced Information Processing System (AIPS)

    Science.gov (United States)

    Pitts, Felix L.

    1993-01-01

    Advanced Information Processing System (AIPS) is a computer systems philosophy, a set of validated hardware building blocks, and a set of validated services as embodied in system software. The goal of AIPS is to provide the knowledgebase which will allow achievement of validated fault-tolerant distributed computer system architectures, suitable for a broad range of applications, having failure probability requirements of 10E-9 at 10 hours. A background and description is given followed by program accomplishments, the current focus, applications, technology transfer, FY92 accomplishments, and funding.

  10. 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...

  11. Improved Vehicular Information Network Architecture Using Fuzzy Based Named Data NetworkingNDN

    Directory of Open Access Journals (Sweden)

    Kanwalpreet Kaur

    2015-08-01

    Full Text Available Vehicular Ad-hoc System VANETs is really a component with smart transport systems. It has ability to prevent accidents and the road congestion issues on highways but it suffers from the accomplishment and scalability issues. To handle these difficulties from the Inter Vehicular Communication IVC we apply Name Data Networking NDN. All though in NDN the users are only concerned about necessary data and give no attention on the number of locations from where the data is coming. The NDN layout is usually much more worthy for IVC circumstance getting the ordered material labeling design as well as amp64258exible material retrieval. In this report we propose vehicular network dependent on fuzzy membership function which offers the fundamental NDN style to improve support location dependent forwarding content aggregation and distributed mobility management. This paper finally winds up the several boundaries regarding earlier approaches.

  12. Quantum information processing in nanostructures

    International Nuclear Information System (INIS)

    Reina Estupinan, John-Henry

    2002-01-01

    Since information has been regarded os a physical entity, the field of quantum information theory has blossomed. This brings novel applications, such as quantum computation. This field has attracted the attention of numerous researchers with backgrounds ranging from computer science, mathematics and engineering, to the physical sciences. Thus, we now have an interdisciplinary field where great efforts are being made in order to build devices that should allow for the processing of information at a quantum level, and also in the understanding of the complex structure of some physical processes at a more basic level. This thesis is devoted to the theoretical study of structures at the nanometer-scale, 'nanostructures', through physical processes that mainly involve the solid-state and quantum optics, in order to propose reliable schemes for the processing of quantum information. Initially, the main results of quantum information theory and quantum computation are briefly reviewed. Next, the state-of-the-art of quantum dots technology is described. In so doing, the theoretical background and the practicalities required for this thesis are introduced. A discussion of the current quantum hardware used for quantum information processing is given. In particular, the solid-state proposals to date are emphasised. A detailed prescription is given, using an optically-driven coupled quantum dot system, to reliably prepare and manipulate exciton maximally entangled Bell and Greenberger-Horne-Zeilinger (GHZ) states. Manipulation of the strength and duration of selective light-pulses needed for producing these highly entangled states provides us with crucial elements for the processing of solid-state based quantum information. The all-optical generation of states of the so-called Bell basis for a system of two quantum dots (QDs) is exploited for performing the quantum teleportation of the excitonic state of a dot in an array of three coupled QDs. Theoretical predictions suggest

  13. 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.

  14. An Approach to Represent and Communicate Product or System Design Ideas at the Fuzzy-Front End of the Design Process

    NARCIS (Netherlands)

    Opiyo, E.Z.

    2016-01-01

    The primary challenge underscored and dealt with was how to represent the product’s or system’s use environment and processes and to communicate ideas and envisaged use contexts effectively at the fuzzy-front early stages of the design process. The work focused specifically on complex products or

  15. Fuzzy Control Teaching Models

    Directory of Open Access Journals (Sweden)

    Klaus-Dietrich Kramer

    2016-05-01

    Full Text Available Many degree courses at technical universities include the subject of control systems engineering. As an addition to conventional approaches Fuzzy Control can be used to easily find control solutions for systems, even if they include nonlinearities. To support further educational training, models which represent a technical system to be controlled are required. These models have to represent the system in a transparent and easy cognizable manner. Furthermore, a programming tool is required that supports an easy Fuzzy Control development process, including the option to verify the results and tune the system behavior. In order to support the development process a graphical user interface is needed to display the fuzzy terms under real time conditions, especially with a debug system and trace functionality. The experiences with such a programming tool, the Fuzzy Control Design Tool (FHFCE Tool, and four fuzzy teaching models will be presented in this paper. The methodical and didactical objective in the utilization of these teaching models is to develop solution strategies using Computational Intelligence (CI applications for Fuzzy Controllers in order to analyze different algorithms of inference or defuzzyfication and to verify and tune those systems efficiently.

  16. On Hesitant Fuzzy Reducible Weighted Bonferroni Mean and Its Generalized Form for Multicriteria Aggregation

    Directory of Open Access Journals (Sweden)

    Wei Zhou

    2014-01-01

    Full Text Available Due to convenience and powerfulness in dealing with vagueness and uncertainty of real situation, hesitant fuzzy set has received more and more attention and has been a hot research topic recently. To differently process and effectively aggregate hesitant fuzzy information and capture their interrelationship, in this paper, we propose the hesitant fuzzy reducible weighted Bonferroni mean (HFRWBM and present its four prominent characteristics, namely, reductibility, monotonicity, boundedness, and idempotency. Then, we further investigate its generalized form, that is, the generalized hesitant fuzzy reducible weighted Bonferroni mean (GHFRWBM. Based on the discussion of model parameters, some special cases of the HFRWBM and GHFRWBM are studied in detail. In addition, to deal with the situation that multicriteria have connections in hesitant fuzzy information aggregation, a three-step aggregation approach has been proposed on the basis of the HFRWBM and GHFRWBM. In the end, we apply the proposed aggregation operators to multicriteria aggregation and give an example to illustrate our results.

  17. 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.

  18. Multimodality Inferring of Human Cognitive States Based on Integration of Neuro-Fuzzy Network and Information Fusion Techniques

    Directory of Open Access Journals (Sweden)

    P. Bhattacharya

    2007-11-01

    Full Text Available To achieve an effective and safe operation on the machine system where the human interacts with the machine mutually, there is a need for the machine to understand the human state, especially cognitive state, when the human's operation task demands an intensive cognitive activity. Due to a well-known fact with the human being, a highly uncertain cognitive state and behavior as well as expressions or cues, the recent trend to infer the human state is to consider multimodality features of the human operator. In this paper, we present a method for multimodality inferring of human cognitive states by integrating neuro-fuzzy network and information fusion techniques. To demonstrate the effectiveness of this method, we take the driver fatigue detection as an example. The proposed method has, in particular, the following new features. First, human expressions are classified into four categories: (i casual or contextual feature, (ii contact feature, (iii contactless feature, and (iv performance feature. Second, the fuzzy neural network technique, in particular Takagi-Sugeno-Kang (TSK model, is employed to cope with uncertain behaviors. Third, the sensor fusion technique, in particular ordered weighted aggregation (OWA, is integrated with the TSK model in such a way that cues are taken as inputs to the TSK model, and then the outputs of the TSK are fused by the OWA which gives outputs corresponding to particular cognitive states under interest (e.g., fatigue. We call this method TSK-OWA. Validation of the TSK-OWA, performed in the Northeastern University vehicle drive simulator, has shown that the proposed method is promising to be a general tool for human cognitive state inferring and a special tool for the driver fatigue detection.

  19. SELECTION OF PROJECT MANAGERS IN CONSTRUCTION FIRMS USING ANALYTIC HIERARCHY PROCESS (AHP AND FUZZY TOPSIS: A CASE STUDY

    Directory of Open Access Journals (Sweden)

    Fatemeh Torfi

    2011-10-01

    Full Text Available Selecting a project manager is a major decision for every construction company. Traditionally, a project manager is selected by interviewing applicants and evaluating their capabilities by considering the special requirements of the project. The interviews are usually conducted by senior managers, and the selection of the best candidate depends on their opinions. Thus, the results may not be completely reliable. Moreover, conducting interviews for a large group of candidates is time-consuming. Thus, there is a need for computational models that can be used to select the most suitable applicant, given the project specifications and the applicants’ details. In this paper, a case study is performed in which a Fuzzy Multiple Criteria Decision Making (FMCDM model is used to select the best candidate for the post of project manager in a large construction firm. First, with the opinions of the senior managers, all the criteria and sub-criteria required for the selection are gathered, and the criteria priorities are qualitatively specified. Then, the applicants are ranked using the Analytic Hierarchy Process (AHP, approximate weights of the criteria, and fuzzy technique for order performance by similarity to ideal solution (TOPSIS. The results of the case study are shown to be satisfactory.

  20. Risk Identification and Assessment in PPP Infrastructure Projects using Fuzzy Analytical Hierarchy Process and Life-Cycle Methodology

    Directory of Open Access Journals (Sweden)

    Jie Li

    2012-11-01

    Full Text Available To fulfil the increasing demands of the public,Public Private Partnership (PPP has beenincreasingly used to procure infrastructureprojects, such as motor ways, bridges, tunnelsand railways. However, the risks involved inPPP projects are unique and dynamic due tolarge amount of investment and longconcession period. This paper aims to developa risk identification framework from theperspectives of project life cycle, and anassessment framework for risks associatedwith PPP project using fuzzy analyticalhierarchy process (AHP. First the paperreviews the current literature to identifycommon risks in PPP infrastructure projectsand classification methods used. The risksidentified from the literature were classifiedusing project life cycle perspectives. Followingthat, the paper presents the advantages offuzzy AHP. Furthermore, the paper provides aframework for assessment of risks in PPPprojects followed by an illustrative examplewhere the data was obtained from surveyquestionnaires. The paper concludes that risksassociated in PPP infrastructure projects areunique and therefore it is beneficial to classifythem from project life cycle perspectives, andthe proposed fuzzy AHP method is suitable forthe assessment of these risks.

  1. Predicting performance of a ground-source heat pump system using fuzzy weighted pre-processing-based ANFIS

    Energy Technology Data Exchange (ETDEWEB)

    Esen, Hikmet; Esen, Mehmet [Department of Mechanical Education, Faculty of Technical Education, Firat University, 23119 Elazig (Turkey); Inalli, Mustafa [Department of Mechanical Engineering, Faculty of Engineering, Firat University, 23279 Elazig (Turkey); Sengur, Abdulkadir [Department of Electronic and Computer Science, Faculty of Technical Education, Firat University, 23119 Elazig (Turkey)

    2008-12-15

    The goal of this work is to predict the daily performance (COP) of a ground-source heat pump (GSHP) system with the minimum data set based on an adaptive neuro-fuzzy inference system (ANFIS) with a fuzzy weighted pre-processing (FWP) method. To evaluate the effectiveness of our proposal (FWP-ANFIS), a computer simulation is developed on MATLAB environment. The comparison of the proposed hybridized system's results with the standard ANFIS results is carried out and the results are given in the tables. The efficiency of the proposed method was demonstrated by using the 3-fold cross-validation test. The statistical methods, such as the root-mean squared (RMS), the coefficient of multiple determinations (R{sup 2}) and the coefficient of variation (cov), are given to compare the predicted and actual values for model validation. The average R{sup 2} values is 0.9998, the average RMS value is 0.0272 and the average cov value is 0.7733, which can be considered as very promising. The data set for the COP of GSHP system available included 38 data patterns. The simulation results show that the FWP-based ANFIS can be used in an alternative way in these systems. The prediction results of the proposed structure were much better than the standard ANFIS results. Therefore, instead of limited experimental data found in the literature, faster and simpler solutions are obtained using hybridized structures such as FWP-based ANFIS. (author)

  2. ALIGNING INFORMATION SECURITY WITH THE IMAGE OF THE ORGANIZATION AND PRIORITIZATION BASED ON FUZZY LOGIC FOR THE INDUSTRIAL AUTOMATION SECTOR

    Directory of Open Access Journals (Sweden)

    Adolfo Alberto Vanti

    2011-12-01

    Full Text Available This paper develops the strategic alignment of organizational behavior through the organizations´ image, prioritization and information security practices. To this end, information security is studied based on the business requirements of confidentiality, integrity and availability by applying a tool which integrates the strategic, tactical and operational vision through the following framework: Balanced Scorecard - BSC (strategic x Control Objectives for Information and Related Technology - COBIT (tactical x International Organization for Standardization - ISO/International Electro Technical Commission - IEC27002 (operational. Another image instrument of the organization is applied in parallel with this analysis to identify and analyze performance involving profiles related to mechanistic, psychic prisons, political systems, instruments of domination, organisms, cybernetics, flux and transformation (MORGAN, 1996. Finally, a model of strategic prioritization, based on compensatory fuzzy logic (ESPIN and VANTI, 2005, is applied. The method was applied to an industrial company located in southern Brazil. The results with the application show two organizational images: "organism" and "flux and transformation ". The strategic priorities indicated a significant search for new business services and international markets. Regarding protection of information, security found the gap between "minimum" and "Reasonable" and in domain 8 (HR of standard ISO/IEC27002, considered 71% protection as "inappropriate" and "minimal" in the IT Governance context.

  3. Information systems process and practice

    CERN Document Server

    Urquhart, Christine; Tbaishat, Dina; Yeoman, Alison

    2017-01-01

    This book adopts a holistic interpretation of information architecture, to offer a variety of methods, tools, and techniques that may be used when designing websites and information systems that support workflows and what people require when 'managing information'.

  4. 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.

  5. 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.

  6. Fuzzy Commitment

    Science.gov (United States)

    Juels, Ari

    The purpose of this chapter is to introduce fuzzy commitment, one of the earliest and simplest constructions geared toward cryptography over noisy data. The chapter also explores applications of fuzzy commitment to two problems in data security: (1) secure management of biometrics, with a focus on iriscodes, and (2) use of knowledge-based authentication (i.e., personal questions) for password recovery.

  7. Fuzzy control in environmental engineering

    CERN Document Server

    Chmielowski, Wojciech Z

    2016-01-01

    This book is intended for engineers, technicians and people who plan to use fuzzy control in more or less developed and advanced control systems for manufacturing processes, or directly for executive equipment. Assuming that the reader possesses elementary knowledge regarding fuzzy sets and fuzzy control, by way of a reminder, the first parts of the book contain a reminder of the theoretical foundations as well as a description of the tools to be found in the Matlab/Simulink environment in the form of a toolbox. The major part of the book presents applications for fuzzy controllers in control systems for various manufacturing and engineering processes. It presents seven processes and problems which have been programmed using fuzzy controllers. The issues discussed concern the field of Environmental Engineering. Examples are the control of a flood wave passing through a hypothetical, and then the real Dobczyce reservoir in the Raba River, which is located in the upper Vistula River basin in Southern Poland, th...

  8. Assessing safety risk in electricity distribution processes using ET & BA improved technique and its ranking by VIKOR and TOPSIS models in fuzzy environment

    Directory of Open Access Journals (Sweden)

    S. Rahmani

    2016-04-01

      Conclusion: The height and electricity are of the main causes of accidents in electricity transmission and distribution industry which caused the overhead power networks to be ranked as high risk. Application of decision-making models in fuzzy environment minimizes the judgment of assessors in the risk assessment process.

  9. Identification of different geologic units using fuzzy constrained resistivity tomography

    Science.gov (United States)

    Singh, Anand; Sharma, S. P.

    2018-01-01

    Different geophysical inversion strategies are utilized as a component of an interpretation process that tries to separate geologic units based on the resistivity distribution. In the present study, we present the results of separating different geologic units using fuzzy constrained resistivity tomography. This was accomplished using fuzzy c means, a clustering procedure to improve the 2D resistivity image and geologic separation within the iterative minimization through inversion. First, we developed a Matlab-based inversion technique to obtain a reliable resistivity image using different geophysical data sets (electrical resistivity and electromagnetic data). Following this, the recovered resistivity model was converted into a fuzzy constrained resistivity model by assigning the highest probability value of each model cell to the cluster utilizing fuzzy c means clustering procedure during the iterative process. The efficacy of the algorithm is demonstrated using three synthetic plane wave electromagnetic data sets and one electrical resistivity field dataset. The presented approach shows improvement on the conventional inversion approach to differentiate between different geologic units if the correct number of geologic units will be identified. Further, fuzzy constrained resistivity tomography was performed to examine the augmentation of uranium mineralization in the Beldih open cast mine as a case study. We also compared geologic units identified by fuzzy constrained resistivity tomography with geologic units interpreted from the borehole information.

  10. Practicality of quantum information processing

    Science.gov (United States)

    Lau, Hoi-Kwan

    Quantum Information Processing (QIP) is expected to bring revolutionary enhancement to various technological areas. However, today's QIP applications are far from being practical. The problem involves both hardware issues, i.e., quantum devices are imperfect, and software issues, i.e., the functionality of some QIP applications is not fully understood. Aiming to improve the practicality of QIP, in my PhD research I have studied various topics in quantum cryptography and ion trap quantum computation. In quantum cryptography, I first studied the security of position-based quantum cryptography (PBQC). I discovered a wrong assumption in the previous literature that the cheaters are not allowed to share entangled resources. I proposed entanglement attacks that could cheat all known PBQC protocols. I also studied the practicality of continuous-variable (CV) quantum secret sharing (QSS). While the security of CV QSS was considered by the literature only in the limit of infinite squeezing, I found that finitely squeezed CV resources could also provide finite secret sharing rate. Our work relaxes the stringent resources requirement of implementing QSS. In ion trap quantum computation, I studied the phase error of quantum information induced by dc Stark effect during ion transportation. I found an optimized ion trajectory for which the phase error is the minimum. I also defined a threshold speed, above which ion transportation would induce significant error. In addition, I proposed a new application for ion trap systems as universal bosonic simulators (UBS). I introduced two architectures, and discussed their respective strength and weakness. I illustrated the implementations of bosonic state initialization, transformation, and measurement by applying radiation fields or by varying the trap potential. When comparing with conducting optical experiments, the ion trap UBS is advantageous in higher state initialization efficiency and higher measurement accuracy. Finally, I

  11. PENERAPAN FUZZY ANALYTIC HIERARCHY PROCESS DALAM METODE MULTI ATTRIBUTE FAILURE MODE ANALYSIS UNTUK MENGIDENTIFIKASI PENYEBAB KEGAGALAN POTENSIAL PADA PROSES PRODUKSI

    Directory of Open Access Journals (Sweden)

    Dorina Hetharia

    2012-02-01

    Full Text Available Banyak metode dalam Total Quality Management (TQM yang dapat digunakan untuk melakukan perbaikan kualitas produk dan jasa. Salah satunya adalah Multi Attribute Failure Mode Analysis (MAFMA, yang dapat digunakan untuk mengeliminasi atau mengurangi kemungkinan terjadinya kegagalan bila dilihat dari faktor penyebabnya, sehingga dapat mencegah terulang kembali kegagalan tersebut. MAFMA merupakan pengembangan dari Failure Mode and Effect Analysis (FMEA, yang mengintegrasikan atribut severity, occurance, dan detectability dengan aspek ekonomi yakni expected cost. Pada FMEA, penentuan penyebab kegagalan potensial suatu produk dilakukan dengan memberikan nilai (score pada atribut severity, occurance, dan detectability, yang dilanjutkan dengan menghitung nilai Risk Priority Number (RPN tertinggi. Sedangkan pada MAFMA, penentuan penyebab kegagalan potensial dilakukan dengan pemberian bobot pada ke-empat atribut. Pemberian bobot tersebut menggunakan Analytic Hierarchy Process (AHP dengan logika fuzy. Atribut severity, occurance, detectability dan expected cost pada MAFMA dimasukkan sebagai level kriteria dalam struktur hirarkhi AHP, sedangkan penyebab-penyebab kegagalan akan menjadi level alternatif pada struktur hirarkhi tersebut. Studi kasus pada PT Pelita Cengkareng Paper & Co. menunjukkan bahwa bobot  kriteria severity sebesar 0.3461, kriteria occurance sebesar 0.0848, kriteria detectability sebesar 0.1741 dan kriteria expected cost sebesar 0.3950.Sedangkan penyebab kegagalan potensial adalah penggumpalan chemical dengan bobot tertinggi sebesar 0.210. Kata kunci: AHP, logika fuzzy, MAFMA     There are several methods of Total Quality Management (TQM that can be used to improve quality of product and service. One of those is Multi Attribute Failure Mode Analysis (MAFMA, which can be used to eliminate or minimize the failure probability based on its causal factor, so we can prevent the same failure in the future. MAFMA is development of Failure Mode

  12. Type-2 fuzzy granular models

    CERN Document Server

    Sanchez, Mauricio A; Castro, Juan R

    2017-01-01

    In this book, a series of granular algorithms are proposed. A nature inspired granular algorithm based on Newtonian gravitational forces is proposed. A series of methods for the formation of higher-type information granules represented by Interval Type-2 Fuzzy Sets are also shown, via multiple approaches, such as Coefficient of Variation, principle of justifiable granularity, uncertainty-based information concept, and numerical evidence based. And a fuzzy granular application comparison is given as to demonstrate the differences in how uncertainty affects the performance of fuzzy information granules.

  13. Handbook on neural information processing

    CERN Document Server

    Maggini, Marco; Jain, Lakhmi

    2013-01-01

    This handbook presents some of the most recent topics in neural information processing, covering both theoretical concepts and practical applications. The contributions include:                         Deep architectures                         Recurrent, recursive, and graph neural networks                         Cellular neural networks                         Bayesian networks                         Approximation capabilities of neural networks                         Semi-supervised learning                         Statistical relational learning                         Kernel methods for structured data                         Multiple classifier systems                         Self organisation and modal learning                         Applications to ...

  14. Accuracy in Optical Information Processing

    Science.gov (United States)

    Timucin, Dogan Aslan

    Low computational accuracy is an important obstacle for optical processors which blocks their way to becoming a practical reality and a serious challenger for classical computing paradigms. This research presents a comprehensive solution approach to the problem of accuracy enhancement in discrete analog optical information processing systems. Statistical analysis of a generic three-plane optical processor is carried out first, taking into account the effects of diffraction, interchannel crosstalk, and background radiation. Noise sources included in the analysis are photon, excitation, and emission fluctuations in the source array, transmission and polarization fluctuations in the modulator, and photoelectron, gain, dark, shot, and thermal noise in the detector array. Means and mutual coherence and probability density functions are derived for both optical and electrical output signals. Next, statistical models for a number of popular optoelectronic devices are studied. Specific devices considered here are light-emitting and laser diode sources, an ideal noiseless modulator and a Gaussian random-amplitude-transmittance modulator, p-i-n and avalanche photodiode detectors followed by electronic postprocessing, and ideal free-space geometrical -optics propagation and single-lens imaging systems. Output signal statistics are determined for various interesting device combinations by inserting these models into the general formalism. Finally, based on these special-case output statistics, results on accuracy limitations and enhancement in optical processors are presented. Here, starting with the formulation of the accuracy enhancement problem as (1) an optimal detection problem and (2) as a parameter estimation problem, the potential accuracy improvements achievable via the classical multiple-hypothesis -testing and maximum likelihood and Bayesian parameter estimation methods are demonstrated. Merits of using proper normalizing transforms which can potentially stabilize

  15. Study of decision framework of wind farm project plan selection under intuitionistic fuzzy set and fuzzy measure environment

    International Nuclear Information System (INIS)

    Wu, Yunna; Geng, Shuai; Xu, Hu; Zhang, Haobo

    2014-01-01

    Highlights: • Experts’ opinions are expressed by using the intuitionistic fuzzy values. • Fuzzy measure is used to solve the dependence problem of criteria. • The compensatory problem of performance scores is reasonably processed. - Abstract: Project selection plays an important role in the entire life cycle of wind farm project and the multi-criteria decision making (MCDM) methods are very important in the whole wind farm project plan selection process. There are problems in the present MCDM methods decrease evaluation quality of the wind farm project plans: first, the information loss exists in the wind farm project plan evaluation process. Second, it is difficult to satisfy the independent assumption of the multi-criteria decision making methods used in the wind farm project plan evaluation in fact. Third, the compensatory problem of performance scores of the wind farm project plans is processed unreasonably. Hence the innovation points of this paper are as follows: first, the intuitionistic fuzzy numbers are used instead of fuzzy numbers or numerical values to reflect the experts’ intuitive preferences to decrease the probability of information loss; second, the fuzzy measure is used to rate the important degrees of criteria in order to avoid the independent assumption and to increase the reasonability; third, the partial compensatory problem of performance scores is well processed by using intuitionistic fuzzy Choquet (IFC) operator and generalized intuitionistic fuzzy ordered geometric averaging (GIFOGA) operator. These operators can deal with the compensatory performance scores and non-compensatory performance scores respectively. Finally, a case study demonstrates the effectiveness of decision framework

  16. Analysis of algal bloom risk with uncertainties in lakes by integrating self-organizing map and fuzzy information theory

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Qiuwen, E-mail: qchen@rcees.ac.cn [RCEES, Chinese Academy of Sciences, Shuangqinglu 18, Beijing 10085 (China); China Three Gorges University, Daxuelu 8, Yichang 443002 (China); CEER, Nanjing Hydraulics Research Institute, Guangzhoulu 223, Nanjing 210029 (China); Rui, Han; Li, Weifeng; Zhang, Yanhui [RCEES, Chinese Academy of Sciences, Shuangqinglu 18, Beijing 10085 (China)

    2014-06-01

    Algal blooms are a serious problem in waters, which damage aquatic ecosystems and threaten drinking water safety. However, the outbreak mechanism of algal blooms is very complex with great uncertainty, especially for large water bodies where environmental conditions have obvious variation in both space and time. This study developed an innovative method which integrated a self-organizing map (SOM) and fuzzy information diffusion theory to comprehensively analyze algal bloom risks with uncertainties. The Lake Taihu was taken as study case and the long-term (2004–2010) on-site monitoring data were used. The results showed that algal blooms in Taihu Lake were classified into four categories and exhibited obvious spatial–temporal patterns. The lake was mainly characterized by moderate bloom but had high uncertainty, whereas severe blooms with low uncertainty were observed in the northwest part of the lake. The study gives insight on the spatial–temporal dynamics of algal blooms, and should help government and decision-makers outline policies and practices on bloom monitoring and prevention. The developed method provides a promising approach to estimate algal bloom risks under uncertainties. - Highlights: • An innovative method is developed to analyze algal bloom risks with uncertainties. • The algal blooms in Taihu Lake showed obvious spatial and temporal patterns. • The lake is mainly characterized as moderate bloom but with high uncertainty. • Severe bloom with low uncertainty appeared occasionally in the northwest part. • The results provide important information to bloom monitoring and management.

  17. 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.

  18. Inter-firm collaboration in the Fuzzy Front-End of the innovation process - Exploring New Forms of Collaboration

    DEFF Research Database (Denmark)

    Jørgensen, Jacob Høj; Goduscheit, René Chester; Bergenholz, Carsten

    2007-01-01

    , marketing, sales. The focus of this paper is on collaboration where innovation is the main part of the collaborative effort. Innovation refers to the research and development (R&D) activity devoted to increasing scientific or technical knowledge and the application of that knowledge to the creation of new...... and tendencies in formal R&D partnering relations. This paper, however, focuses on collaboration between independent companies prior to such formal agreements as joint ventures or other contractual agreements. This first phase of the innovation process is often referred to as the Fuzzy Front-End (FFE....... In this article we examine the characteristics of the FFE phase and explore this phase in an inter-firm perspective. Through an in-depth case-study of a single firm and its innovation partners we identify parameters for improved collaboration in the FFE. In conclusion we outline a model for inter...

  19. Managing Operational Risk Related to Microfinance Lending Process using Fuzzy Inference System based on the FMEA Method: Moroccan Case Study

    Directory of Open Access Journals (Sweden)

    Alaoui Youssef Lamrani

    2017-12-01

    Full Text Available Managing operational risk efficiently is a critical factor of microfinance institutions (MFIs to get a financial and social return. The purpose of this paper is to identify, assess and prioritize the root causes of failure within the microfinance lending process (MLP especially in Moroccan microfinance institutions. Considering the limitation of traditional failure mode and effect analysis (FMEA method in assessing and classifying risks, the methodology adopted in this study focuses on developing a fuzzy logic inference system (FLIS based on (FMEA. This approach can take into account the subjectivity of risk indicators and the insufficiency of statistical data. The results show that the Moroccan MFIs need to focus more on customer relationship management and give more importance to their staff training, to clients screening as well as to their business analysis.

  20. Evaluation of barriers of corporate social responsibility using an analytical hierarchy process under a fuzzy environment - A textile case

    DEFF Research Database (Denmark)

    Shen, Lixin; Govindan, Kannan; Shankar, Madan

    2015-01-01

    Process (AHP) under a fuzzy environment. The results show that financial constraints comprise the main barrier to the implementation of CSR in the Indian textiles industry, which is then further validated with feedback from case industry managers. This study offers both societal and scientific insights...... model, and this model is validated with a case industry situated in southern India. Common barriers are collected through various reliable means, and among those common barriers, the essential barrier was identified with the assistance of the case industrial manager through an Analytical Hierarchy......The ventilating crisis of Corporate Social Responsibility (CSR) issues in the textiles industry resulted in the engagement of many researchers in the analysis of CSR and its related factors throughout the globe. Some researchers in developed nations extend their policies beyond the boundary of CSR...

  1. Processing of microCT implant-bone systems images using Fuzzy Mathematical Morphology

    International Nuclear Information System (INIS)

    Bouchet, A; Pastore, J; Colabella, L; Omar, S; Ballarre, J

    2016-01-01

    The relationship between a metallic implant and the existing bone in a surgical permanent prosthesis is of great importance since the fixation and osseointegration of the system leads to the failure or success of the surgery. Micro Computed Tomography is a technique that helps to visualize the structure of the bone. In this study, the microCT is used to analyze implant-bone systems images. However, one of the problems presented in the reconstruction of these images is the effect of the iron based implants, with a halo or fluorescence scattering distorting the micro CT image and leading to bad 3D reconstructions. In this work we introduce an automatic method for eliminate the effect of AISI 316L iron materials in the implant-bone system based on the application of Compensatory Fuzzy Mathematical Morphology for future investigate about the structural and mechanical properties of bone and cancellous materials. (paper)

  2. Advanced modeling of management processes in information technology

    CERN Document Server

    Kowalczuk, Zdzislaw

    2014-01-01

    This book deals with the issues of modelling management processes of information technology and IT projects while its core is the model of information technology management and its component models (contextual, local) describing initial processing and the maturity capsule as well as a decision-making system represented by a multi-level sequential model of IT technology selection, which acquires a fuzzy rule-based implementation in this work. In terms of applicability, this work may also be useful for diagnosing applicability of IT standards in evaluation of IT organizations. The results of this diagnosis might prove valid for those preparing new standards so that – apart from their own visions – they could, to an even greater extent, take into account the capabilities and needs of the leaders of project and manufacturing teams. The book is intended for IT professionals using the ITIL, COBIT and TOGAF standards in their work. Students of computer science and management who are interested in the issue of IT...

  3. Continuous-variable quantum information processing

    DEFF Research Database (Denmark)

    Andersen, Ulrik Lund; Leuchs, G.; Silberhorn, C.

    2010-01-01

    the continuous degree of freedom of a quantum system for encoding, processing or detecting information, one enters the field of continuous-variable (CV) quantum information processing. In this paper we review the basic principles of CV quantum information processing with main focus on recent developments...... in the field. We will be addressing the three main stages of a quantum information system; the preparation stage where quantum information is encoded into CVs of coherent states and single-photon states, the processing stage where CV information is manipulated to carry out a specified protocol and a detection...... stage where CV information is measured using homodyne detection or photon counting....

  4. NONLINEAR ASSIGNMENT-BASED METHODS FOR INTERVAL-VALUED INTUITIONISTIC FUZZY MULTI-CRITERIA DECISION ANALYSIS WITH INCOMPLETE PREFERENCE INFORMATION

    OpenAIRE

    TING-YU CHEN

    2012-01-01

    In the context of interval-valued intuitionistic fuzzy sets, this paper develops nonlinear assignment-based methods to manage imprecise and uncertain subjective ratings under incomplete preference structures and thereby determines the optimal ranking order of the alternatives for multiple criteria decision analysis. By comparing each interval-valued intuitionistic fuzzy number's score function, accuracy function, membership uncertainty index, and hesitation uncertainty index, a ranking proced...

  5. Infochemistry Information Processing at the Nanoscale

    CERN Document Server

    Szacilowski, Konrad

    2012-01-01

    Infochemistry: Information Processing at the Nanoscale, defines a new field of science, and describes the processes, systems and devices at the interface between chemistry and information sciences. The book is devoted to the application of molecular species and nanostructures to advanced information processing. It includes the design and synthesis of suitable materials and nanostructures, their characterization, and finally applications of molecular species and nanostructures for information storage and processing purposes. Divided into twelve chapters; the first three chapters serve as an int

  6. Correlation Coefficients of Extended Hesitant Fuzzy Sets and Their Applications to Decision Making

    Directory of Open Access Journals (Sweden)

    Na Lu

    2017-03-01

    Full Text Available Extended hesitant fuzzy sets (EHFSs, which allow the membership degree of an element to a set represented by several possible value-groups, can be considered as a powerful tool to express uncertain information in the process of group decision making. Therefore, we derive some correlation coefficients between EHFSs, which contain two cases, the correlation coefficients taking into account the length of extended hesitant fuzzy elements (EHFEs and the correlation coefficients without taking into account the length of EHFEs, as a new extension of existing correlation coefficients for hesitant fuzzy sets (HFSs and apply them to decision making under extended hesitant fuzzy environments. A real-world example based on the energy policy problem is employed to illustrate the actual need for dealing with the difference of evaluation information provided by different experts without information loss in decision making processes.

  7. Social Information Processing in Deaf Adolescents

    Science.gov (United States)

    Torres, Jesús; Saldaña, David; Rodríguez-Ortiz, Isabel R.

    2016-01-01

    The goal of this study was to compare the processing of social information in deaf and hearing adolescents. A task was developed to assess social information processing (SIP) skills of deaf adolescents based on Crick and Dodge's (1994; A review and reformulation of social information-processing mechanisms in children's social adjustment.…

  8. Information processing by neuronal populations

    National Research Council Canada - National Science Library

    Hölscher, Christian; Munk, Matthias

    2009-01-01

    ... simultaneously recorded spike trains 120 Mark Laubach, Nandakumar S. Narayanan, and Eyal Y. Kimchi Part III Neuronal population information coding and plasticity in specific brain areas 149 7 F...

  9. Ecosystem approach and the Fuzzy logic: a dialectical proposal for information on Environmental Health Abordagem ecossistêmica e lógica Fuzzy: uma proposta dialética para o uso da informação em Saúde Ambiental

    Directory of Open Access Journals (Sweden)

    Daniel Canavese

    2012-12-01

    Full Text Available The ever-growing production and the problematization of Environmental Health have shown the need to apprehend complex realities and deal with uncertainties from the most diversified instruments which may even incorporate local aspects and subjectivities by means of qualitative realities, while broadening the capacity of the information system. This paper presents a view on the reflection upon some challenges and possible convergences between the ecosystemic approach and the Fuzzy logic in the process of dealing with scientific information and decision-making in Environmental Health.O avanço da produção intelectual sobre Saúde e Ambiente tem demonstrado a necessidade de apreender realidades que são complexas, além de lidar com suas incertezas. Nesse sentido, os instrumentos utilizados deveriam incorporar aspectos subjetivos e qualitativos, além dos elementos de cunho quantitativo, ao retratar uma condição local. Esse artigo apresenta uma reflexão a respeito dos desafios e dos possíveis pontos de convergência entre uma abordagem ecossistêmica e a lógica Fuzzy nesse processo de lidar com a informação para apoio a tomada de decisão envolvendo Saúde e Ambiente.

  10. An integrated approach of analytical network process and fuzzy based spatial decision making systems applied to landslide risk mapping

    Science.gov (United States)

    Abedi Gheshlaghi, Hassan; Feizizadeh, Bakhtiar

    2017-09-01

    Landslides in mountainous areas render major damages to residential areas, roads, and farmlands. Hence, one of the basic measures to reduce the possible damage is by identifying landslide-prone areas through landslide mapping by different models and methods. The purpose of conducting this study is to evaluate the efficacy of a combination of two models of the analytical network process (ANP) and fuzzy logic in landslide risk mapping in the Azarshahr Chay basin in northwest Iran. After field investigations and a review of research literature, factors affecting the occurrence of landslides including slope, slope aspect, altitude, lithology, land use, vegetation density, rainfall, distance to fault, distance to roads, distance to rivers, along with a map of the distribution of occurred landslides were prepared in GIS environment. Then, fuzzy logic was used for weighting sub-criteria, and the ANP was applied to weight the criteria. Next, they were integrated based on GIS spatial analysis methods and the landslide risk map was produced. Evaluating the results of this study by using receiver operating characteristic curves shows that the hybrid model designed by areas under the curve 0.815 has good accuracy. Also, according to the prepared map, a total of 23.22% of the area, amounting to 105.38 km2, is in the high and very high-risk class. Results of this research are great of importance for regional planning tasks and the landslide prediction map can be used for spatial planning tasks and for the mitigation of future hazards in the study area.

  11. Fuzzy Comprehensive Evaluation of Rural Information Poverty in China - - Case Study of Hebei Province

    Science.gov (United States)

    Sun, Guizhen; Wang, Shuanjun; Li, Yaqing; Wang, Huijun

    Information poverty is a new form of poverty in information society. With the growing information-gap between urban and rural areas, information poverty is prevailing in the vast rural areas in China. It is largely restricted the new rural construction and the social harmonious development of villages and towns and must be resolved. The evaluation of rural information poverty is the premise to resolve it. In order to estimate the problem, index system of rural informatization evaluation of Hebei province was designed by means of Delphi. Then, according to the survey of farmers' information demand, AHP and FCE were used to estimate rural information poverty of Hebei province. The purpose of this study is to provide a new operational approach in evaluating or solving rural information poverty and constructing rural informatization in China.

  12. Information Processing and Human Abilities

    Science.gov (United States)

    Kirby, John R.; Das, J. P.

    1978-01-01

    The simultaneous and successive processing model of cognitive abilities was compared to a traditional primary mental abilities model. Simultaneous processing was found to be primarily related to spatial ability; and to a lesser extent, to memory and inductive reasoning. Subjects were 104 fourth-grade urban males. (Author/GD C)

  13. Analysis of algal bloom risk with uncertainties in lakes by integrating self-organizing map and fuzzy information theory.

    Science.gov (United States)

    Chen, Qiuwen; Rui, Han; Li, Weifeng; Zhang, Yanhui

    2014-06-01

    Algal blooms are a serious problem in waters, which damage aquatic ecosystems and threaten drinking water safety. However, the outbreak mechanism of algal blooms is very complex with great uncertainty, especially for large water bodies where environmental conditions have obvious variation in both space and time. This study developed an innovative method which integrated a self-organizing map (SOM) and fuzzy information diffusion theory to comprehensively analyze algal bloom risks with uncertainties. The Lake Taihu was taken as study case and the long-term (2004-2010) on-site monitoring data were used. The results showed that algal blooms in Taihu Lake were classified into four categories and exhibited obvious spatial-temporal patterns. The lake was mainly characterized by moderate bloom but had high uncertainty, whereas severe blooms with low uncertainty were observed in the northwest part of the lake. The study gives insight on the spatial-temporal dynamics of algal blooms, and should help government and decision-makers outline policies and practices on bloom monitoring and prevention. The developed method provides a promising approach to estimate algal bloom risks under uncertainties. Copyright © 2014 Elsevier B.V. All rights reserved.

  14. Fuzzy statistical decision-making theory and applications

    CERN Document Server

    Kabak, Özgür

    2016-01-01

    This book offers a comprehensive reference guide to fuzzy statistics and fuzzy decision-making techniques. It provides readers with all the necessary tools for making statistical inference in the case of incomplete information or insufficient data, where classical statistics cannot be applied. The respective chapters, written by prominent researchers, explain a wealth of both basic and advanced concepts including: fuzzy probability distributions, fuzzy frequency distributions, fuzzy Bayesian inference, fuzzy mean, mode and median, fuzzy dispersion, fuzzy p-value, and many others. To foster a better understanding, all the chapters include relevant numerical examples or case studies. Taken together, they form an excellent reference guide for researchers, lecturers and postgraduate students pursuing research on fuzzy statistics. Moreover, by extending all the main aspects of classical statistical decision-making to its fuzzy counterpart, the book presents a dynamic snapshot of the field that is expected to stimu...

  15. Fuzzy GML Modeling Based on Vague Soft Sets

    Directory of Open Access Journals (Sweden)

    Bo Wei

    2017-01-01

    Full Text Available The Open Geospatial Consortium (OGC Geography Markup Language (GML explicitly represents geographical spatial knowledge in text mode. All kinds of fuzzy problems will inevitably be encountered in spatial knowledge expression. Especially for those expressions in text mode, this fuzziness will be broader. Describing and representing fuzziness in GML seems necessary. Three kinds of fuzziness in GML can be found: element fuzziness, chain fuzziness, and attribute fuzziness. Both element fuzziness and chain fuzziness belong to the reflection of the fuzziness between GML elements and, then, the representation of chain fuzziness can be replaced by the representation of element fuzziness in GML. On the basis of vague soft set theory, two kinds of modeling, vague soft set GML Document Type Definition (DTD modeling and vague soft set GML schema modeling, are proposed for fuzzy modeling in GML DTD and GML schema, respectively. Five elements or pairs, associated with vague soft sets, are introduced. Then, the DTDs and the schemas of the five elements are correspondingly designed and presented according to their different chains and different fuzzy data types. While the introduction of the five elements or pairs is the basis of vague soft set GML modeling, the corresponding DTD and schema modifications are key for implementation of modeling. The establishment of vague soft set GML enables GML to represent fuzziness and solves the problem of lack of fuzzy information expression in GML.

  16. Fuzzy promises

    DEFF Research Database (Denmark)

    Anker, Thomas Boysen; Kappel, Klemens; Eadie, Douglas

    2012-01-01

    as narrative material to communicate self-identity. Finally, (c) we propose that brands deliver fuzzy experiential promises through effectively motivating consumers to adopt and play a social role implicitly suggested and facilitated by the brand. A promise is an inherently ethical concept and the article...... concludes with an in-depth discussion of fuzzy brand promises as two-way ethical commitments that put requirements on both brands and consumers....

  17. Pythagorean Fuzzy Muirhead Mean Operators and Their Application in Multiple-Criteria Group Decision-Making

    Directory of Open Access Journals (Sweden)

    Jianghong Zhu

    2018-06-01

    Full Text Available As a generalization of the intuitionistic fuzzy set (IFS, a Pythagorean fuzzy set has more flexibility than IFS in expressing uncertainty and fuzziness in the process of multiple criteria group decision-making (MCGDM. Meanwhile, the prominent advantage of the Muirhead mean (MM operator is that it can reflect the relationships among the various input arguments through changing a parameter vector. Motivated by these primary characters, in this study, we introduced the MM operator into the Pythagorean fuzzy context to expand its applied fields. To do so, we presented the Pythagorean fuzzy MM (PFMM operators and Pythagorean fuzzy dual MM (PFDMM operator to fuse the Pythagorean fuzzy information. Then, we investigated their some properties and gave some special cases related to the parameter vector. In addition, based on the developed operators, two MCGDM methods under the Pythagorean fuzzy environment are proposed. An example is given to verify the validity and feasibility of our proposed methods, and a comparative analysis is provided to show their advantages.

  18. A novel segmentation method for uneven lighting image with noise injection based on non-local spatial information and intuitionistic fuzzy entropy

    Science.gov (United States)

    Yu, Haiyan; Fan, Jiulun

    2017-12-01

    Local thresholding methods for uneven lighting image segmentation always have the limitations that they are very sensitive to noise injection and that the performance relies largely upon the choice of the initial window size. This paper proposes a novel algorithm for segmenting uneven lighting images with strong noise injection based on non-local spatial information and intuitionistic fuzzy theory. We regard an image as a gray wave in three-dimensional space, which is composed of many peaks and troughs, and these peaks and troughs can divide the image into many local sub-regions in different directions. Our algorithm computes the relative characteristic of each pixel located in the corresponding sub-region based on fuzzy membership function and uses it to replace its absolute characteristic (its gray level) to reduce the influence of uneven light on image segmentation. At the same time, the non-local adaptive spatial constraints of pixels are introduced to avoid noise interference with the search of local sub-regions and the computation of local characteristics. Moreover, edge information is also taken into account to avoid false peak and trough labeling. Finally, a global method based on intuitionistic fuzzy entropy is employed on the wave transformation image to obtain the segmented result. Experiments on several test images show that the proposed method has excellent capability of decreasing the influence of uneven illumination on images and noise injection and behaves more robustly than several classical global and local thresholding methods.

  19. Using boolean and fuzzy logic combined with analytic hierarchy process for hazardous waste landfill site selection: A case study from Hormozgan province, Iran

    Directory of Open Access Journals (Sweden)

    Mahdieh Saadat Foomani

    2017-01-01

    Full Text Available Hazardous wastes include numerous kinds of discarded chemicals and other wastes generated from industrial, commercial, and institutional activities. These types of waste present immediate or long-term risks to humans, animals, plants, or the environment and therefore require special handling for safe disposal. Landfills that can accept hazardous wastes are excavated or engineered sites where these special types of waste can be disposed of securely. Since landfills are permanent sites, special attention must be afforded in selecting the location. This paper investigated the use of the Boolean theory and Fuzzy logic in combination with Analytic Hierarchy Process (AHP methods by applying GIS and IDRISI software for the selection of a hazardous waste landfill site in the Iranian province of Hormozgan. The best location was determined via the Fuzzy and the Boolean methodologies. By collating the area selected for the hazardous waste landfill, this study found that Fuzzy logic with an AND operator had the best options for this purpose. In the end, the most suitable area for a hazardous waste landfill was about 1.6 km2 which was obtained by employing Fuzzy in combination with AHP and by using an AND operator. In addition, all the fundamental criteria affecting the landfill location were considered.

  20. Fuzzy logic controller to improve powerline communication

    Science.gov (United States)

    Tirrito, Salvatore

    2015-12-01

    The Power Line Communications (PLC) technology allows the use of the power grid in order to ensure the exchange of data information among devices. This work proposes an approach, based on Fuzzy Logic, that dynamically manages the amplitude of the signal, with which each node transmits, by processing the master-slave link quality measured and the master-slave distance. The main objective of this is to reduce both the impact of communication interferences induced and power consumption.

  1. Effects of foveal information processing

    Science.gov (United States)

    Harris, R. L., Sr.

    1984-01-01

    The scanning behavior of pilots must be understood so that cockpit displays can be assembled which will provide the most information accurately and quickly to the pilot. The results of seven years of collecting and analyzing pilot scanning data are summarized. The data indicate that pilot scanning behavior is: (1) subsconscious; (2) situation dependent; and (3) can be disrupted if pilots are forced to make conscious decisions. Testing techniques and scanning analysis techniques have been developed that are sensitive to pilot workload.

  2. 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...

  3. WHY FUZZY QUALITY?

    Directory of Open Access Journals (Sweden)

    Abbas Parchami

    2016-09-01

    Full Text Available Such as other statistical problems, we may confront with uncertain and fuzzy concepts in quality control. One particular case in process capability analysis is a situation in which specification limits are two fuzzy sets. In such a uncertain and vague environment, the produced product is not qualified with a two-valued Boolean view, but to some degree depending on the decision-maker strictness and the quality level of the produced product. This matter can be cause to a rational decision-making on the quality of the production line. First, a comprehensive approach is presented in this paper for modeling the fuzzy quality concept. Then, motivations and advantages of applying this flexible approach instead of using classical quality are mentioned.

  4. Fuzzy spaces topology change and BH thermodynamics

    International Nuclear Information System (INIS)

    Silva, C A S; Landim, R R

    2014-01-01

    What is the ultimate fate of something that falls into a black hole? From this question arises one of the most intricate problems of modern theoretical physics: the black hole information loss paradox. Bekenstein and Hawking have been shown that the entropy in a black hole is proportional to the surface area of its event horizon, which should be quantized in a multiple of the Planck area. This led G.'t Hooft and L. Susskind to propose the holographic principle which states that all the information inside the black hole can be stored on its event horizon. From this results, one may think if the solution to the information paradox could lies in the quantum properties of the black hole horizon. One way to quantize the event horizon is to see it as a fuzzy sphere, which posses a closed relation with Hopf algebras. This relation makes possible a topology change process where a fuzzy sphere splits in two others. In this work it will be shown that, if one quantize the black hole event horizon as a fuzzy sphere taking into account its quantum symmetry properties, a topology change process to black holes can be defined without break unitarity or locality, and we can obtain a possible solution to the information paradox. Moreover, we show that this model can explain the origin of the black hole entropy, and why black holes obey a generalized second law of thermodynamics

  5. Selection Input Output by Restriction Using DEA Models Based on a Fuzzy Delphi Approach and Expert Information

    Science.gov (United States)

    Arsad, Roslah; Nasir Abdullah, Mohammad; Alias, Suriana; Isa, Zaidi

    2017-09-01

    Stock evaluation has always been an interesting problem for investors. In this paper, a comparison regarding the efficiency stocks of listed companies in Bursa Malaysia were made through the application of estimation method of Data Envelopment Analysis (DEA). One of the interesting research subjects in DEA is the selection of appropriate input and output parameter. In this study, DEA was used to measure efficiency of stocks of listed companies in Bursa Malaysia in terms of the financial ratio to evaluate performance of stocks. Based on previous studies and Fuzzy Delphi Method (FDM), the most important financial ratio was selected. The results indicated that return on equity, return on assets, net profit margin, operating profit margin, earnings per share, price to earnings and debt to equity were the most important ratios. Using expert information, all the parameter were clarified as inputs and outputs. The main objectives were to identify most critical financial ratio, clarify them based on expert information and compute the relative efficiency scores of stocks as well as rank them in the construction industry and material completely. The methods of analysis using Alirezaee and Afsharian’s model were employed in this study, where the originality of Charnes, Cooper and Rhodes (CCR) with the assumption of Constant Return to Scale (CSR) still holds. This method of ranking relative efficiency of decision making units (DMUs) was value-added by the Balance Index. The interested data was made for year 2015 and the population of the research includes accepted companies in stock markets in the construction industry and material (63 companies). According to the ranking, the proposed model can rank completely for 63 companies using selected financial ratio.

  6. An Interactive Signed Distance Approach for Multiple Criteria Group Decision-Making Based on Simple Additive Weighting Method with Incomplete Preference Information Defined by Interval Type-2 Fuzzy Sets

    OpenAIRE

    Ting-Yu Chen

    2014-01-01

    Interval type-2 fuzzy sets (T2FSs) with interval membership grades are suitable for dealing with imprecision or uncertainties in many real-world problems. In the Interval type-2 fuzzy context, the aim of this paper is to develop an interactive signed distance-based simple additive weighting (SAW) method for solving multiple criteria group decision-making problems with linguistic ratings and incomplete preference information. This paper first formulates a group decision-making problem with unc...

  7. Application of grey-fuzzy approach in parametric optimization of EDM process in machining of MDN 300 steel

    Science.gov (United States)

    Protim Das, Partha; Gupta, P.; Das, S.; Pradhan, B. B.; Chakraborty, S.

    2018-01-01

    Maraging steel (MDN 300) find its application in many industries as it exhibits high hardness which are very difficult to machine material. Electro discharge machining (EDM) is an extensively popular machining process which can be used in machining of such materials. Optimization of response parameters are essential for effective machining of these materials. Past researchers have already used Taguchi for obtaining the optimal responses of EDM process for this material with responses such as material removal rate (MRR), tool wear rate (TWR), relative wear ratio (RWR), and surface roughness (SR) considering discharge current, pulse on time, pulse off time, arc gap, and duty cycle as process parameters. In this paper, grey relation analysis (GRA) with fuzzy logic is applied to this multi objective optimization problem to check the responses by an implementation of the derived parametric setting. It was found that the parametric setting derived by the proposed method results in better a response than those reported by the past researchers. Obtained results are also verified using the technique for order of preference by similarity to ideal solution (TOPSIS). The predicted result also shows that there is a significant improvement in comparison to the results of past researchers.

  8. Information-Processing Models and Curriculum Design

    Science.gov (United States)

    Calfee, Robert C.

    1970-01-01

    "This paper consists of three sections--(a) the relation of theoretical analyses of learning to curriculum design, (b) the role of information-processing models in analyses of learning processes, and (c) selected examples of the application of information-processing models to curriculum design problems." (Author)

  9. Scaling the Information Processing Demands of Occupations

    Science.gov (United States)

    Haase, Richard F.; Jome, LaRae M.; Ferreira, Joaquim Armando; Santos, Eduardo J. R.; Connacher, Christopher C.; Sendrowitz, Kerrin

    2011-01-01

    The purpose of this study was to provide additional validity evidence for a model of person-environment fit based on polychronicity, stimulus load, and information processing capacities. In this line of research the confluence of polychronicity and information processing (e.g., the ability of individuals to process stimuli from the environment…

  10. Fuzzy logic controller using different inference methods

    International Nuclear Information System (INIS)

    Liu, Z.; De Keyser, R.

    1994-01-01

    In this paper the design of fuzzy controllers by using different inference methods is introduced. Configuration of the fuzzy controllers includes a general rule-base which is a collection of fuzzy PI or PD rules, the triangular fuzzy data model and a centre of gravity defuzzification algorithm. The generalized modus ponens (GMP) is used with the minimum operator of the triangular norm. Under the sup-min inference rule, six fuzzy implication operators are employed to calculate the fuzzy look-up tables for each rule base. The performance is tested in simulated systems with MATLAB/SIMULINK. Results show the effects of using the fuzzy controllers with different inference methods and applied to different test processes

  11. Mathematics of Information Processing and the Internet

    Science.gov (United States)

    Hart, Eric W.

    2010-01-01

    The mathematics of information processing and the Internet can be organized around four fundamental themes: (1) access (finding information easily); (2) security (keeping information confidential); (3) accuracy (ensuring accurate information); and (4) efficiency (data compression). In this article, the author discusses each theme with reference to…

  12. Prioritization of balanced scorecard measurement indicators as a process management approach via fuzzy AHP: Case study in automotive industry

    Czech Academy of Sciences Publication Activity Database

    Senvar, M. O.; Vayvay, O.; Kurt, E.; Hloch, Sergej

    2014-01-01

    Roč. 21, č. 1 (2014), s. 155-162 ISSN 1330-3651 Institutional support: RVO:68145535 Keywords : balanced scorecard * fuzzy * automotive Subject RIV: JQ - Machines ; Tools Impact factor: 0.579, year: 2014

  13. Quantum information processing : science & technology.

    Energy Technology Data Exchange (ETDEWEB)

    Horton, Rebecca; Carroll, Malcolm S.; Tarman, Thomas David

    2010-09-01

    Qubits demonstrated using GaAs double quantum dots (DQD). The qubit basis states are the (1) singlet and (2) triplet stationary states. Long spin decoherence times in silicon spurs translation of GaAs qubit in to silicon. In the near term the goals are: (1) Develop surface gate enhancement mode double quantum dots (MOS & strained-Si/SiGe) to demonstrate few electrons and spin read-out and to examine impurity doped quantum-dots as an alternative architecture; (2) Use mobility, C-V, ESR, quantum dot performance & modeling to feedback and improve upon processing, this includes development of atomic precision fabrication at SNL; (3) Examine integrated electronics approaches to RF-SET; (4) Use combinations of numerical packages for multi-scale simulation of quantum dot systems (NEMO3D, EMT, TCAD, SPICE); and (5) Continue micro-architecture evaluation for different device and transport architectures.

  14. Stabilization of nonlinear systems using sampled-data output-feedback fuzzy controller based on polynomial-fuzzy-model-based control approach.

    Science.gov (United States)

    Lam, H K

    2012-02-01

    This paper investigates the stability of sampled-data output-feedback (SDOF) polynomial-fuzzy-model-based control systems. Representing the nonlinear plant using a polynomial fuzzy model, an SDOF fuzzy controller is proposed to perform the control process using the system output information. As only the system output is available for feedback compensation, it is more challenging for the controller design and system analysis compared to the full-state-feedback case. Furthermore, because of the sampling activity, the control signal is kept constant by the zero-order hold during the sampling period, which complicates the system dynamics and makes the stability analysis more difficult. In this paper, two cases of SDOF fuzzy controllers, which either share the same number of fuzzy rules or not, are considered. The system stability is investigated based on the Lyapunov stability theory using the sum-of-squares (SOS) approach. SOS-based stability conditions are obtained to guarantee the system stability and synthesize the SDOF fuzzy controller. Simulation examples are given to demonstrate the merits of the proposed SDOF fuzzy control approach.

  15. Fuzzy relations for the analysis of traders' preferences in an information market game

    NARCIS (Netherlands)

    van de Walle, B.A.; Turoff, M.

    2009-01-01

    In this paper we focus on preference and decision data gathered during a computer-supported information market game in which 35 students participated during seven consecutive trading sessions. The participants’ individual preferences on the market shares are collected to calculate a collective

  16. 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

  17. Managing Controversies in the Fuzzy Front End

    DEFF Research Database (Denmark)

    Christiansen, John K.; Gasparin, Marta

    2016-01-01

    . The analysis investigates the microprocesses around the controversies that emerge during the fuzzy front end of four products. Five different types of controversies are identified: profit, production, design, brand and customers/market. Each controversy represents a threat, but also an opportunity to search...... for new solutions in the unpredictable non-linear processes. The study uses an ethnographic approach using qualitative data from interviews, company documents, external communication and marketing material, minutes of meetings, informal conversations and observations. The analysis of four FFE processes...... demonstrates how the fuzzy front requires managers to deal with controversies that emerge from many different places and involve both human and non-human actors. Closing the controversies requires managers to take account of the situation, identify the problem that needs to be addressed, and initiate a search...

  18. Fuzzy histogram for internal and external fuzzy directional relations

    OpenAIRE

    Salamat , Nadeem; Zahzah , El-Hadi

    2009-01-01

    5 Pages; Spatial relations have key point importance in image analysis and computer vision. Numerous technics have been developed to study these relations especially directional relations. Modern digital computers give rise to quantitative methods and among them fuzzy methods have core importance due to handling imprecise knowledge information and vagueness. In most fuzzy methods external directional relations are considered which are useful for small scale space image analysis but in large s...

  19. Process information systems in nuclear reprocessing

    International Nuclear Information System (INIS)

    Jaeschke, A.; Keller, H.; Orth, H.

    1987-01-01

    On a production management level, a process information system in a nuclear reprocessing plant (NRP) has to fulfill conventional operating functions and functions for nuclear material surveillance (safeguards). Based on today's state of the art of on-line process control technology, the progress in hardware and software technology allows to introduce more process-specific intelligence into process information systems. Exemplified by an expert-system-aided laboratory management system as component of a NRP process information system, the paper demonstrates that these technologies can be applied already. (DG) [de

  20. Fuzzy Clustering

    DEFF Research Database (Denmark)

    Berks, G.; Keyserlingk, Diedrich Graf von; Jantzen, Jan

    2000-01-01

    A symptom is a condition indicating the presence of a disease, especially, when regarded as an aid in diagnosis.Symptoms are the smallest units indicating the existence of a disease. A syndrome on the other hand is an aggregate, set or cluster of concurrent symptoms which together indicate...... and clustering are the basic concerns in medicine. Classification depends on definitions of the classes and their required degree of participant of the elements in the cases' symptoms. In medicine imprecise conditions are the rule and therefore fuzzy methods are much more suitable than crisp ones. Fuzzy c......-mean clustering is an easy and well improved tool, which has been applied in many medical fields. We used c-mean fuzzy clustering after feature extraction from an aphasia database. Factor analysis was applied on a correlation matrix of 26 symptoms of language disorders and led to five factors. The factors...

  1. A comparative assessment of prediction capabilities of modified analytical hierarchy process (M-AHP and Mamdani fuzzy logic models using Netcad-GIS for forest fire susceptibility mapping

    Directory of Open Access Journals (Sweden)

    Hamid reza Pourghasemi

    2016-03-01

    Full Text Available The main purpose of this study is to assess forest fire susceptibility maps (FFSMs and their performances comparison using modified analytical hierarchy process (M-AHP and Mamdani fuzzy logic (MFL models in a geographic information system (GIS environment. This study was carried out in the Minudasht Forests, Golestan Province, Iran, and was conducted in three main stages such as spatial data construction, forest fire modelling using M-AHP and MFL, and validation of constructed models using receiver operating characteristic (ROC curve. At first, seven conditioning factors, such as altitude, slope aspect, slope angle, annual temperature, wind effect, land use, and normalized different vegetation index, were extracted from the spatial database. In the next step, FFSMs were prepared using M-AHP and MFL modules in a Netcad-GIS Architect environment. Finally, the ROC curves and area under the curves (AUCs were estimated for validation purposes. The results showed that the AUCs for MFL and M-AHP are 88.20% and 77.72%, respectively. The results obtained in this study also showed that the MFL model performed better than the M-AHP model. These FFSMs can be applied for land use planning, management, and prevention of future fire hazards.

  2. Improvements to Earthquake Location with a Fuzzy Logic Approach

    Science.gov (United States)

    Gökalp, Hüseyin

    2018-01-01

    In this study, improvements to the earthquake location method were investigated using a fuzzy logic approach proposed by Lin and Sanford (Bull Seismol Soc Am 91:82-93, 2001). The method has certain advantages compared to the inverse methods in terms of eliminating the uncertainties of arrival times and reading errors. In this study, adopting this approach, epicentral locations were determined based on the results of a fuzzy logic space concerning the uncertainties in the velocity models. To map the uncertainties in arrival times into the fuzzy logic space, a trapezoidal membership function was constructed by directly using the travel time difference between the two stations for the P- and S-arrival times instead of the P- and S-wave models to eliminate the need for obtaining information concerning the velocity structure of the study area. The results showed that this method worked most effectively when earthquakes occurred away from a network or when the arrival time data contained phase reading errors. In this study, to resolve the problems related to determining the epicentral locations of the events, a forward modeling method like the grid search technique was used by applying different logical operations (i.e., intersection, union, and their combination) with a fuzzy logic approach. The locations of the events were depended on results of fuzzy logic outputs in fuzzy logic space by searching in a gridded region. The process of location determination with the defuzzification of only the grid points with the membership value of 1 obtained by normalizing all the maximum fuzzy output values of the highest values resulted in more reliable epicentral locations for the earthquakes than the other approaches. In addition, throughout the process, the center-of-gravity method was used as a defuzzification operation.

  3. A Fuzzy Expression Way for Air Quality Index with More Comprehensive Information

    OpenAIRE

    Yujie Wang; Mingxuan Zhao; Yulin Han; Jian Zhou

    2017-01-01

    The Air Quality Index (AQI) is an evaluating indicator for the atmospheric environment released by various environmental monitoring centers to communicate the present air quality status to the public, which is calculated by the aid of the monitored concentrations of six common air pollutants and relevant computational formulae. Considering that the historical data of daily overall AQI illustrated by the traditional expression way merely contain limited information about the original data, thi...

  4. 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.

  5. Solution Monitoring Evaluated by Proliferation Risk Assessment and Fuzzy Optimization Analysis for Safeguards in a Reprocessing Process

    Directory of Open Access Journals (Sweden)

    Mitsutoshi Suzuki

    2013-01-01

    Full Text Available Solution monitoring (SM has been used in a nuclear reprocessing plant as an additional measure to provide assurance that the plant is operated as declared. The inline volume and density monitoring equipment with dip tubes is important for safety and safeguards purposes and is a typical example of safeguards by design (SBD. Recently safety, safeguards, and security by design (3SBD are proposed to promote an efficient and effective generation of nuclear energy. In 3SBD, proliferation risk assessment has the potential to consider likelihood of the incidence and proliferation risk in safeguards. In this study, risk assessment methodologies for safeguards and security are discussed and several mathematical methods are presented to investigate risk notion applied to intentional acts of facility misuse in an uncertainty environment. Proliferation risk analysis with the Markov model, deterrence effect with the game model, and SBD with fuzzy optimization are shown in feasibility studies to investigate the potential application of the risk and uncertainty analyses in safeguards. It is demonstrated that the SM is an effective measurement system using risk-informed and cost-effective SBD, even though there are inherent difficulties related to the possibility of operator’s falsification.

  6. Probability Estimation in the Framework of Intuitionistic Fuzzy Evidence Theory

    Directory of Open Access Journals (Sweden)

    Yafei Song

    2015-01-01

    Full Text Available Intuitionistic fuzzy (IF evidence theory, as an extension of Dempster-Shafer theory of evidence to the intuitionistic fuzzy environment, is exploited to process imprecise and vague information. Since its inception, much interest has been concentrated on IF evidence theory. Many works on the belief functions in IF information systems have appeared. Although belief functions on the IF sets can deal with uncertainty and vagueness well, it is not convenient for decision making. This paper addresses the issue of probability estimation in the framework of IF evidence theory with the hope of making rational decision. Background knowledge about evidence theory, fuzzy set, and IF set is firstly reviewed, followed by introduction of IF evidence theory. Axiomatic properties of probability distribution are then proposed to assist our interpretation. Finally, probability estimations based on fuzzy and IF belief functions together with their proofs are presented. It is verified that the probability estimation method based on IF belief functions is also potentially applicable to classical evidence theory and fuzzy evidence theory. Moreover, IF belief functions can be combined in a convenient way once they are transformed to interval-valued possibilities.

  7. Fuzziness and Foundations of Exact and Inexact Sciences

    CERN Document Server

    Dompere, Kofi Kissi

    2013-01-01

    The monograph is an examination of the fuzzy rational foundations of the structure of exact and inexact sciences over the epistemological space which is distinguished from the ontological space. It is thus concerned with the demarcation problem. It examines exact science and its critique of inexact science. The role of fuzzy rationality in these examinations is presented. The driving force of the discussions is the nature of the information that connects the cognitive relational structure of the epistemological space to the ontological space for knowing. The knowing action is undertaken by decision-choice agents who must process information to derive exact-inexact or true-false conclusions. The information processing is done with a paradigm and laws of thought that constitute the input-output machine. The nature of the paradigm selected depends on the nature of the information structure that is taken as input of the thought processing. Generally, the information structure received from the ontological space i...

  8. On the mathematics of fuzziness

    Energy Technology Data Exchange (ETDEWEB)

    Kerre, E. [Ghent Univ. (Belgium)

    1994-12-31

    During the past twenty-five years, the scientific community has been working very extensively on the development of reliable models for the representation and manipulation of impreciseness and uncertainty that pervade the real world. Fuzzy set theory is one of the most popular theories able to treat incomplete information. In this paper, the basic mathematical principles underlying fuzzy set theory are outlined. Special attention is paid to the way that set theory has influenced the development of mathematics in a positive way.

  9. On the mathematics of fuzziness

    International Nuclear Information System (INIS)

    Kerre, E.

    1994-01-01

    During the past twenty-five years, the scientific community has been working very extensively on the development of reliable models for the representation and manipulation of impreciseness and uncertainty that pervade the real world. Fuzzy set theory is one of the most popular theories able to treat incomplete information. In this paper, the basic mathematical principles underlying fuzzy set theory are outlined. Special attention is paid to the way that set theory has influenced the development of mathematics in a positive way

  10. Animal models for information processing during sleep

    NARCIS (Netherlands)

    Coenen, A.M.L.; Drinkenburg, W.H.I.M.

    2002-01-01

    Information provided by external stimuli does reach the brain during sleep, although the amount of information is reduced during sleep compared to wakefulness. The process controlling this reduction is called `sensory' gating and evidence exists that the underlying neurophysiological processes take

  11. Some fixed point theorems in fuzzy reflexive Banach spaces

    International Nuclear Information System (INIS)

    Sadeqi, I.; Solaty kia, F.

    2009-01-01

    In this paper, we first show that there are some gaps in the fixed point theorems for fuzzy non-expansive mappings which are proved by Bag and Samanta, in [Bag T, Samanta SK. Fixed point theorems on fuzzy normed linear spaces. Inf Sci 2006;176:2910-31; Bag T, Samanta SK. Some fixed point theorems in fuzzy normed linear spaces. Inform Sci 2007;177(3):3271-89]. By introducing the notion of fuzzy and α- fuzzy reflexive Banach spaces, we obtain some results which help us to establish the correct version of fuzzy fixed point theorems. Second, by applying Theorem 3.3 of Sadeqi and Solati kia [Sadeqi I, Solati kia F. Fuzzy normed linear space and it's topological structure. Chaos, Solitons and Fractals, in press] which says that any fuzzy normed linear space is also a topological vector space, we show that all topological version of fixed point theorems do hold in fuzzy normed linear spaces.

  12. Career information processing strategies of secondary school ...

    African Journals Online (AJOL)

    This study examined the strategies commonly adopted by Osun state secondary school students in processing career information. It specifically examined the sources of career information available to the students, the uses to which the students put the information collected and how their career decision making skills can be ...

  13. A language for information commerce processes

    NARCIS (Netherlands)

    Aberer, Karl; Wombacher, Andreas

    Automatizing information commerce requires languages to represent the typical information commerce processes. Existing languages and standards cover either only very specific types of business models or are too general to capture in a concise way the specific properties of information commerce

  14. Selecting the most appropriate maintenance strategies using fuzzy Analytic Network Process: A case study of Saipa vehicle industry

    Directory of Open Access Journals (Sweden)

    Mina Rahimi

    2014-04-01

    Full Text Available It is necessary for companies and industries to select the most appropriate maintenance strategy to increase the reliability and safety level with reasonable cost. The primary objective of this paper is to assess different maintenance strategies and to select the best and the most appropriate alternatives for Saipa vehicle industry in Tehran, Iran. For this purpose, we simultaneously consider numerous conflicting objectives and constraints. In this study to counter with this conflicting and to consider the dependency among the qualitative and quantitative criteria and sub-criteria, an integration of Analytic Network Process (ANP and fuzzy set theory are considered. Therefore, factors playing important role in selecting the best maintenance strategy are determined by reviewing the research literature and interviewing with the experts by Delphi technique. Considering the relations among different factors, a network with 4 criteria and 28 sub-criteria are proposed. In the next step, ANP technique is applied for ranking effective factors in evolution of appropriate maintenance strategy. Results reveal that the best maintenance strategy for fixture body of pride (setter is corrective maintenance.

  15. Identification of food spoilage in the smart home based on neural and fuzzy processing of odour sensor responses.

    Science.gov (United States)

    Green, Geoffrey C; Chan, Adrian D C; Goubran, Rafik A

    2009-01-01

    Adopting the use of real-time odour monitoring in the smart home has the potential to alert the occupant of unsafe or unsanitary conditions. In this paper, we measured (with a commercial metal-oxide sensor-based electronic nose) the odours of five household foods that had been left out at room temperature for a week to spoil. A multilayer perceptron (MLP) neural network was trained to recognize the age of the samples (a quantity related to the degree of spoilage). For four of these foods, median correlation coefficients (between target values and MLP outputs) of R > 0.97 were observed. Fuzzy C-means clustering (FCM) was applied to the evolving odour patterns of spoiling milk, which had been sampled more frequently (4h intervals for 7 days). The FCM results showed that both the freshest and oldest milk samples had a high degree of membership in "fresh" and "spoiled" clusters, respectively. In the future, as advancements in electronic nose development remove the present barriers to acceptance, signal processing methods like those explored in this paper can be incorporated into odour monitoring systems used in the smart home.

  16. Integration fuzzy analytic network process (ANP) and SWOT business strategy for the development of small and medium enterprises (SME)

    Science.gov (United States)

    Khotimah, Bain Khusnul; Irhamni, Firli; Kustiyahningsih, Yenny

    2017-08-01

    Business competition is one risk factor for Small and Medium Enterprises (SME) to set up good management in handling the risk of loss. This proposed research will look for criteria that influence the occurrence of damages based on data from by Cooperative and SME on Batik Madura. Method approach which used Fuzzy Analytic Network Process (FANP) as the weight of interest in decision support systems. Factor analysis of the level losses will influence the performance in the business sector. SWOT analysis combined with FANP method to determine the most appropriate development strategy to be applied industry. From the results of SWOT analysis and FANP, it was found the strategy of the best development to apply business strategy. The raw materials and human resources are available to increase the production capacity of the test results of SWOT analysis SME on Batik Madura. The result measurement of SME are always favourable the position, because the value is well resulted production and the amount is stable revenue which caused SME are in the first quadrant, so the power can exist take advantage of business opportunities. While the trial results of SWOT analysis on SME on Batik Madura in January and March are quadrant of second quadrant because of the number of defective products is quite produced, causing SME are under threat. But although SME suffer threats, SME still have strength on the amount of production and timely delivery.

  17. Evaluation of Barriers of Corporate Social Responsibility Using an Analytical Hierarchy Process under a Fuzzy Environment—A Textile Case

    Directory of Open Access Journals (Sweden)

    Lixin Shen

    2015-03-01

    Full Text Available The ventilating crisis of Corporate Social Responsibility (CSR issues in the textiles industry resulted in the engagement of many researchers in the analysis of CSR and its related factors throughout the globe. Some researchers in developed nations extend their policies beyond the boundary of CSR in the textiles industry, but some developing contexts are still limited to this boundary, including India, due to facts that have not yet been revealed. Hence, to fill this gap, this study reveals the factors that are resisting the implementation of CSR in the textiles industry with the assistance of a proposed model, and this model is validated with a case industry situated in southern India. Common barriers are collected through various reliable means, and among those common barriers, the essential barrier was identified with the assistance of the case industrial manager through an Analytical Hierarchy Process (AHP under a fuzzy environment. The results show that financial constraints comprise the main barrier to the implementation of CSR in the Indian textiles industry, which is then further validated with feedback from case industry managers. This study offers both societal and scientific insights, identifies limitations, and provides an approach that may be extended in the future once additional factors are implemented.

  18. Optimization of Surface Roughness Parameters of Al-6351 Alloy in EDC Process: A Taguchi Coupled Fuzzy Logic Approach

    Science.gov (United States)

    Kar, Siddhartha; Chakraborty, Sujoy; Dey, Vidyut; Ghosh, Subrata Kumar

    2017-10-01

    This paper investigates the application of Taguchi method with fuzzy logic for multi objective optimization of roughness parameters in electro discharge coating process of Al-6351 alloy with powder metallurgical compacted SiC/Cu tool. A Taguchi L16 orthogonal array was employed to investigate the roughness parameters by varying tool parameters like composition and compaction load and electro discharge machining parameters like pulse-on time and peak current. Crucial roughness parameters like Centre line average roughness, Average maximum height of the profile and Mean spacing of local peaks of the profile were measured on the coated specimen. The signal to noise ratios were fuzzified to optimize the roughness parameters through a single comprehensive output measure (COM). Best COM obtained with lower values of compaction load, pulse-on time and current and 30:70 (SiC:Cu) composition of tool. Analysis of variance is carried out and a significant COM model is observed with peak current yielding highest contribution followed by pulse-on time, compaction load and composition. The deposited layer is characterised by X-Ray Diffraction analysis which confirmed the presence of tool materials on the work piece surface.

  19. Use of fuzzy sets in modeling of GIS objects

    Science.gov (United States)

    Mironova, Yu N.

    2018-05-01

    The paper discusses modeling and methods of data visualization in geographic information systems. Information processing in Geoinformatics is based on the use of models. Therefore, geoinformation modeling is a key in the chain of GEODATA processing. When solving problems, using geographic information systems often requires submission of the approximate or insufficient reliable information about the map features in the GIS database. Heterogeneous data of different origin and accuracy have some degree of uncertainty. In addition, not all information is accurate: already during the initial measurements, poorly defined terms and attributes (e.g., "soil, well-drained") are used. Therefore, there are necessary methods for working with uncertain requirements, classes, boundaries. The author proposes using spatial information fuzzy sets. In terms of a characteristic function, a fuzzy set is a natural generalization of ordinary sets, when one rejects the binary nature of this feature and assumes that it can take any value in the interval.

  20. Using Fuzzy SOM Strategy for Satellite Image Retrieval and Information Mining

    Directory of Open Access Journals (Sweden)

    Yo-Ping Huang

    2008-02-01

    Full Text Available This paper proposes an efficient satellite image retrieval and knowledge discovery model. The strategy comprises two major parts. First, a computational algorithm is used for off-line satellite image feature extraction, image data representation and image retrieval. Low level features are automatically extracted from the segmented regions of satellite images. A self-organization feature map is used to construct a two-layer satellite image concept hierarchy. The events are stored in one layer and the corresponding feature vectors are categorized in the other layer. Second, a user friendly interface is provided that retrieves images of interest and mines useful information based on the events in the concept hierarchy. The proposed system is evaluated with prominent features such as typhoons or high-pressure masses.

  1. 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.

  2. 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

  3. The Fuzzy u-Chart for Sustainable Manufacturing in the Vietnam Textile Dyeing Industry

    Directory of Open Access Journals (Sweden)

    Kim-Phung Truong

    2017-07-01

    Full Text Available The inevitability of measurement errors and/or humans of subjectivity in data collection processes make accumulated data imprecise, and are thus called fuzzy data. To adapt to this fuzzy domain in a manufacturing process, a traditional u control chart for monitoring the average number of nonconformities per unit is required to extend. In this paper, we first generalize the u chart, named fuzzy u-chart, whose control limits are built on the basis of resolution identity, which is a well-known fuzzy set theory. Then, an approach to fuzzy-logic reasoning, incorporating the decision-maker’s varying levels of optimism towards the online process, is proposed to categorize the manufacturing conditions. In addition, we further develop a condition-based classification mechanism, where the process conditions can be discriminated into intermittent states between in-control and out-of-control. As anomalous conditions are monitored to some extent, this condition-based classification mechanism can provide the critical information to deliberate the cost of process intervention with respect to the gain of quality improvement. Finally, the proposed fuzzy u-chart is implemented in the Vietnam textile dyeing industry to replace its conventional u-chart. The results demonstrate that the industry can effectively evade unnecessary adjustments to its current processes; thus, the industry can substantially reduce its operational cost and potential loss.

  4. 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.

  5. 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...

  6. Consumer Behavior Modeling: Fuzzy Logic Model for Air Purifiers Choosing

    Directory of Open Access Journals (Sweden)

    Oleksandr Dorokhov

    2017-12-01

    Full Text Available At the beginning, the article briefly describes the features of the marketing complex household goods. Also provides an overview of some aspects of the market for indoor air purifiers. The specific subject of the study was the process of consumer choice of household appliances for cleaning air in living quarters. The aim of the study was to substantiate and develop a computer model for evaluating by the potential buyers devices for air purification in conditions of vagueness and ambiguity of their consumer preferences. Accordingly, the main consumer criteria are identified, substantiated and described when buyers choose air purifiers. As methods of research, approaches based on fuzzy logic, fuzzy sets theory and fuzzy modeling were chosen. It was hypothesized that the fuzzy-multiple model allows rather accurately reflect consumer preferences and potential consumer choice in conditions of insufficient and undetermined information. Further, a computer model for estimating the consumer qualities of air cleaners by customers is developed. A proposed approach based on the application of fuzzy logic theory and practical modeling in the specialized computer software MATLAB. In this model, the necessary membership functions and their terms are constructed, as well as a set of rules for fuzzy inference to make decisions on the estimation of a specific air purifier. A numerical example of a comparative evaluation of air cleaners presented on the Ukrainian market is made and is given. Numerical simulation results confirmed the applicability of the proposed approach and the correctness of the hypothesis advanced about the possibility of modeling consumer behavior using fuzzy logic. The analysis of the obtained results is carried out and the prospects of application, development, and improvement of the developed model and the proposed approach are determined.

  7. 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 ...

  8. Using life cycle information in process discovery

    NARCIS (Netherlands)

    Leemans, S.J.J.; Fahland, D.; Van Der Aalst, W.M.P.; Reichert, M.; Reijers, H.A.

    2016-01-01

    Understanding the performance of business processes is an important part of any business process intelligence project. From historical information recorded in event logs, performance can be measured and visualized on a discovered process model. Thereby the accuracy of the measured performance, e.g.,

  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. 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...

  11. Fuzzy logic based control system for fresh water aquaculture: A MATLAB based simulation approach

    Directory of Open Access Journals (Sweden)

    Rana Dinesh Singh

    2015-01-01

    Full Text Available Fuzzy control is regarded as the most widely used application of fuzzy logic. Fuzzy logic is an innovative technology to design solutions for multiparameter and non-linear control problems. One of the greatest advantages of fuzzy control is that it uses human experience and process information obtained from operator rather than a mathematical model for the definition of a control strategy. As a result, it often delivers solutions faster than conventional control design techniques. The proposed system is an attempt to apply fuzzy logic techniques to predict the stress factor on the fish, based on line data and rule base generated using domain expert. The proposed work includes a use of Data acquisition system, an interfacing device for on line parameter acquisition and analysis, fuzzy logic controller (FLC for inferring the stress factor. The system takes stress parameters on the fish as inputs, fuzzified by using FLC with knowledge base rules and finally provides single output. All the parameters are controlled and calibrated by the fuzzy logic toolbox and MATLAB programming.

  12. Preference of effective Factors in suitable selection of Microtunnel boring machines (mtbm by using the fuzzy analytic hierarchy process (fahp approach

    Directory of Open Access Journals (Sweden)

    Alireza Jafari

    2011-07-01

    Full Text Available The development of underground infrastructure, environmental concerns, and economic trend is influencing society. Due to the increasingly critical nature of installations of utility systems especially in congested areas, the need for monitoring and control system has increased. The microtunneling system will therefore have to provide for possibility of minimized surface disruption. Suitable selection of Microtunneling Boring Machine (MTBM is the most curial decision that manager must be done. Because once the trenchless excavation has started, it might be too late to make any changes in equipment without extra costs and delays. Therefore, the various factors and parameters are affecting the choice of machine. In this paper discusses a developed methodology based on Fuzzy Analytic Hierarchy Process (FAHP in order to determine weights of the criteria and sub criteria and then ranking them. Within the proposed model, four criteria site, machinery, structural, labor force impact and 18 sub-criteria are specified. The linguistic level of comparisons produced by experts are tapped and constructed in a form of triangular fuzzy numbers in order to construct fuzzy pair wise comparison matrices. Therefore, FAHP uses the pair wise comparison matrices for determining the weights of the criteria and sub-criteria.

  13. Comparison of adaptive neuro-fuzzy inference system (ANFIS) and Gaussian processes for machine learning (GPML) algorithms for the prediction of skin temperature in lower limb prostheses.

    Science.gov (United States)

    Mathur, Neha; Glesk, Ivan; Buis, Arjan

    2016-10-01

    Monitoring of the interface temperature at skin level in lower-limb prosthesis is notoriously complicated. This is due to the flexible nature of the interface liners used impeding the required consistent positioning of the temperature sensors during donning and doffing. Predicting the in-socket residual limb temperature by monitoring the temperature between socket and liner rather than skin and liner could be an important step in alleviating complaints on increased temperature and perspiration in prosthetic sockets. In this work, we propose to implement an adaptive neuro fuzzy inference strategy (ANFIS) to predict the in-socket residual limb temperature. ANFIS belongs to the family of fused neuro fuzzy system in which the fuzzy system is incorporated in a framework which is adaptive in nature. The proposed method is compared to our earlier work using Gaussian processes for machine learning. By comparing the predicted and actual data, results indicate that both the modeling techniques have comparable performance metrics and can be efficiently used for non-invasive temperature monitoring. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  14. Occurrence reporting and processing of operations information

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-07-21

    DOE O 232.1A, Occurrence Reporting and Processing of Operations Information, and 10 CFR 830.350, Occurrence Reporting and Processing of Operations Information (when it becomes effective), along with this manual, set forth occurrence reporting requirements for Department of Energy (DOE) Departmental Elements and contractors responsible for the management and operation of DOE-owned and -leased facilities. These requirements include categorization of occurrences related to safety, security, environment, health, or operations (``Reportable Occurrences``); DOE notification of these occurrences; and the development and submission of documented follow-up reports. This Manual provides detailed information for categorizing and reporting occurrences at DOE facilities. Information gathered by the Occurrence Reporting and processing System is used for analysis of the Department`s performance in environmental protection, safeguards and security, and safety and health of its workers and the public. This information is also used to develop lessons learned and document events that significantly impact DOE operations.

  15. Occurrence reporting and processing of operations information

    International Nuclear Information System (INIS)

    1997-01-01

    DOE O 232.1A, Occurrence Reporting and Processing of Operations Information, and 10 CFR 830.350, Occurrence Reporting and Processing of Operations Information (when it becomes effective), along with this manual, set forth occurrence reporting requirements for Department of Energy (DOE) Departmental Elements and contractors responsible for the management and operation of DOE-owned and -leased facilities. These requirements include categorization of occurrences related to safety, security, environment, health, or operations (''Reportable Occurrences''); DOE notification of these occurrences; and the development and submission of documented follow-up reports. This Manual provides detailed information for categorizing and reporting occurrences at DOE facilities. Information gathered by the Occurrence Reporting and processing System is used for analysis of the Department's performance in environmental protection, safeguards and security, and safety and health of its workers and the public. This information is also used to develop lessons learned and document events that significantly impact DOE operations

  16. Certainty and Uncertainty in Quantum Information Processing

    OpenAIRE

    Rieffel, Eleanor G.

    2007-01-01

    This survey, aimed at information processing researchers, highlights intriguing but lesser known results, corrects misconceptions, and suggests research areas. Themes include: certainty in quantum algorithms; the "fewer worlds" theory of quantum mechanics; quantum learning; probability theory versus quantum mechanics.

  17. Developments in quantum information processing by nuclear ...

    Indian Academy of Sciences (India)

    qubits, the 2n energy levels of the spin-system can be treated as an n-qubit system. ... Quantum information processing; qubit; nuclear magnetic resonance quantum comput- ing. ..... The equilibrium spectrum has theoretical intensities in the ra-.

  18. Information in general medical practices: the information processing model.

    Science.gov (United States)

    Crowe, Sarah; Tully, Mary P; Cantrill, Judith A

    2010-04-01

    The need for effective communication and handling of secondary care information in general practices is paramount. To explore practice processes on receiving secondary care correspondence in a way that integrates the information needs and perceptions of practice staff both clinical and administrative. Qualitative study using semi-structured interviews with a wide range of practice staff (n = 36) in nine practices in the Northwest of England. Analysis was based on the framework approach using N-Vivo software and involved transcription, familiarization, coding, charting, mapping and interpretation. The 'information processing model' was developed to describe the six stages involved in practice processing of secondary care information. These included the amendment or updating of practice records whilst simultaneously or separately actioning secondary care recommendations, using either a 'one-step' or 'two-step' approach, respectively. Many factors were found to influence each stage and impact on the continuum of patient care. The primary purpose of processing secondary care information is to support patient care; this study raises the profile of information flow and usage within practices as an issue requiring further consideration.

  19. Radial Fuzzy Systems

    Czech Academy of Sciences Publication Activity Database

    Coufal, David

    2017-01-01

    Roč. 319, 15 July (2017), s. 1-27 ISSN 0165-0114 R&D Projects: GA MŠk(CZ) LD13002 Institutional support: RVO:67985807 Keywords : fuzzy systems * radial functions * coherence Subject RIV: BA - General Mathematics OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 2.718, year: 2016

  20. A process framework for information security management

    Directory of Open Access Journals (Sweden)

    Knut Haufe

    2016-01-01

    Full Text Available Securing sensitive organizational data has become increasingly vital to organizations. An Information Security Management System (ISMS is a systematic approach for establishing, implementing, operating, monitoring, reviewing, maintaining and improving an organization's information security. Key elements of the operation of an ISMS are ISMS processes. However, and in spite of its importance, an ISMS process framework with a description of ISMS processes and their interaction as well as the interaction with other management processes is not available in the literature. Cost benefit analysis of information security investments regarding single measures protecting information and ISMS processes are not in the focus of current research, mostly focused on economics. This article aims to fill this research gap by proposing such an ISMS process framework as the main contribution. Based on a set of agreed upon ISMS processes in existing standards like ISO 27000 series, COBIT and ITIL. Within the framework, identified processes are described and their interaction and interfaces are specified. This framework helps to focus on the operation of the ISMS, instead of focusing on measures and controls. By this, as a main finding, the systemic character of the ISMS consisting of processes and the perception of relevant roles of the ISMS is strengthened.

  1. Information processing among high-performance managers

    Directory of Open Access Journals (Sweden)

    S.C. Garcia-Santos

    2010-01-01

    Full Text Available The purpose of this study was to evaluate the information processing of 43 business managers with a professional superior performance. The theoretical framework considers three models: the Theory of Managerial Roles of Henry Mintzberg, the Theory of Information Processing, and Process Model Response to Rorschach by John Exner. The participants have been evaluated by Rorschach method. The results show that these managers are able to collect data, evaluate them and establish rankings properly. At same time, they are capable of being objective and accurate in the problems assessment. This information processing style permits an interpretation of the world around on basis of a very personal and characteristic processing way or cognitive style.

  2. FUZZY LOGIC BASED SOFTWARE PROCESS IMPROVIZATION FRAMEWORK FOR INDIAN SMALL SCALE SOFTWARE ORGANIZATIONS

    OpenAIRE

    A.M.Kalpana; Dr.A.Ebenezer Jeyakumar

    2010-01-01

    In this paper, the authors elaborate the results obtained after analyzing and assessing the software process activities in five small to medium sized Indian software companies. This work demonstrates a cost effective framework for software process appraisal, specificallytargeted at Indian software Small-to-Medium-sized Enterprises (SMEs). Improvisation deals with the unforeseen. It involves continual experimentation with new possibilities to create innovative and improved solutions outside cu...

  3. A two-stage planning and control model toward Economically Adapted Power Distribution Systems using analytical hierarchy processes and fuzzy optimization

    Energy Technology Data Exchange (ETDEWEB)

    Schweickardt, Gustavo [Instituto de Economia Energetica, Fundacion Bariloche, Centro Atomico Bariloche - Pabellon 7, Av. Bustillo km 9500, 8400 Bariloche (Argentina); Miranda, Vladimiro [INESC Porto, Instituto de Engenharia de Sistemas e Computadores do Porto and FEUP, Faculdade de Engenharia da Universidade do Porto, R. Dr. Roberto Frias, 378, 4200-465 Porto (Portugal)

    2009-07-15

    This work presents a model to evaluate the Distribution System Dynamic De-adaptation respecting its planning for a given period of Tariff Control. The starting point for modeling is brought about by the results from a multi-criteria method based on Fuzzy Dynamic Programming and on Analytic Hierarchy Processes applied in a mid/short-term horizon (stage 1). Then, the decision-making activities using the Hierarchy Analytical Processes will allow defining, for a Control of System De-adaptation (stage 2), a Vector to evaluate the System Dynamic Adaptation. It is directly associated to an eventual series of inbalances that take place during its evolution. (author)

  4. Teaching Information Systems Development via Process Variants

    Science.gov (United States)

    Tan, Wee-Kek; Tan, Chuan-Hoo

    2010-01-01

    Acquiring the knowledge to assemble an integrated Information System (IS) development process that is tailored to the specific needs of a project has become increasingly important. It is therefore necessary for educators to impart to students this crucial skill. However, Situational Method Engineering (SME) is an inherently complex process that…

  5. Information technology, knowledge processes, and innovation success

    NARCIS (Netherlands)

    Song, X.M.; Zang, F.; Bij, van der J.D.; Weggeman, M.C.D.P.

    2001-01-01

    Despite the obvious linkage between information technologies (IT) and knowledge processes and the apparent strategic importance of both, little research has done to explicitly examine how, if at all, IT and knowledge processes affect firm outcomes. The purpose of this study is to bridge this

  6. ENERGETIC CHARGE OF AN INFORMATION PROCESS

    Directory of Open Access Journals (Sweden)

    Popova T.M.

    2009-12-01

    Full Text Available Main laws of technical thermodynamics are universal and could be applied to processes other than thermodynamic ones. The results of the comparison of peculiarities of irreversible informational and thermodynamic processes are presented in the article and a new term “Infopy” is used. A more precise definition of “infopy” as an energetic charge is given in the article.

  7. Fuzzy logic control and optimization system

    Science.gov (United States)

    Lou, Xinsheng [West Hartford, CT

    2012-04-17

    A control system (300) for optimizing a power plant includes a chemical loop having an input for receiving an input signal (369) and an output for outputting an output signal (367), and a hierarchical fuzzy control system (400) operably connected to the chemical loop. The hierarchical fuzzy control system (400) includes a plurality of fuzzy controllers (330). The hierarchical fuzzy control system (400) receives the output signal (367), optimizes the input signal (369) based on the received output signal (367), and outputs an optimized input signal (369) to the input of the chemical loop to control a process of the chemical loop in an optimized manner.

  8. Application of fuzzy logic control in industry

    International Nuclear Information System (INIS)

    Van der Wal, A.J.

    1994-01-01

    An overview is given of the various ways fuzzy logic can be used to improve industrial control. The application of fuzzy logic in control is illustrated by two case studies. The first example shows how fuzzy logic, incorporated in the hardware of an industrial controller, helps to finetune a PID controller, without the operator having any a priori knowledge of the system to be controlled. The second example is from process industry. Here, fuzzy logic supervisory control is implemented in software and enhances the operation of a sintering oven through a subtle combination of priority management and deviation-controlled timing

  9. AN IMPROVED FUZZY CLUSTERING ALGORITHM FOR MICROARRAY IMAGE SPOTS SEGMENTATION

    Directory of Open Access Journals (Sweden)

    V.G. Biju

    2015-11-01

    Full Text Available An automatic cDNA microarray image processing using an improved fuzzy clustering algorithm is presented in this paper. The spot segmentation algorithm proposed uses the gridding technique developed by the authors earlier, for finding the co-ordinates of each spot in an image. Automatic cropping of spots from microarray image is done using these co-ordinates. The present paper proposes an improved fuzzy clustering algorithm Possibility fuzzy local information c means (PFLICM to segment the spot foreground (FG from background (BG. The PFLICM improves fuzzy local information c means (FLICM algorithm by incorporating typicality of a pixel along with gray level information and local spatial information. The performance of the algorithm is validated using a set of simulated cDNA microarray images added with different levels of AWGN noise. The strength of the algorithm is tested by computing the parameters such as the Segmentation matching factor (SMF, Probability of error (pe, Discrepancy distance (D and Normal mean square error (NMSE. SMF value obtained for PFLICM algorithm shows an improvement of 0.9 % and 0.7 % for high noise and low noise microarray images respectively compared to FLICM algorithm. The PFLICM algorithm is also applied on real microarray images and gene expression values are computed.

  10. Image Segmentation Method Using Fuzzy C Mean Clustering Based on Multi-Objective Optimization

    Science.gov (United States)

    Chen, Jinlin; Yang, Chunzhi; Xu, Guangkui; Ning, Li

    2018-04-01

    Image segmentation is not only one of the hottest topics in digital image processing, but also an important part of computer vision applications. As one kind of image segmentation algorithms, fuzzy C-means clustering is an effective and concise segmentation algorithm. However, the drawback of FCM is that it is sensitive to image noise. To solve the problem, this paper designs a novel fuzzy C-mean clustering algorithm based on multi-objective optimization. We add a parameter λ to the fuzzy distance measurement formula to improve the multi-objective optimization. The parameter λ can adjust the weights of the pixel local information. In the algorithm, the local correlation of neighboring pixels is added to the improved multi-objective mathematical model to optimize the clustering cent. Two different experimental results show that the novel fuzzy C-means approach has an efficient performance and computational time while segmenting images by different type of noises.

  11. Cost-Sharing of Ecological Construction Based on Trapezoidal Intuitionistic Fuzzy Cooperative Games.

    Science.gov (United States)

    Liu, Jiacai; Zhao, Wenjian

    2016-11-08

    There exist some fuzziness and uncertainty in the process of ecological construction. The aim of this paper is to develop a direct and an effective simplified method for obtaining the cost-sharing scheme when some interested parties form a cooperative coalition to improve the ecological environment of Min River together. Firstly, we propose the solution concept of the least square prenucleolus of cooperative games with coalition values expressed by trapezoidal intuitionistic fuzzy numbers. Then, based on the square of the distance in the numerical value between two trapezoidal intuitionistic fuzzy numbers, we establish a corresponding quadratic programming model to obtain the least square prenucleolus, which can effectively avoid the information distortion and uncertainty enlargement brought about by the subtraction of trapezoidal intuitionistic fuzzy numbers. Finally, we give a numerical example about the cost-sharing of ecological construction in Fujian Province in China to show the validity, applicability, and advantages of the proposed model and method.

  12. Cost-Sharing of Ecological Construction Based on Trapezoidal Intuitionistic Fuzzy Cooperative Games

    Directory of Open Access Journals (Sweden)

    Jiacai Liu

    2016-11-01

    Full Text Available There exist some fuzziness and uncertainty in the process of ecological construction. The aim of this paper is to develop a direct and an effective simplified method for obtaining the cost-sharing scheme when some interested parties form a cooperative coalition to improve the ecological environment of Min River together. Firstly, we propose the solution concept of the least square prenucleolus of cooperative games with coalition values expressed by trapezoidal intuitionistic fuzzy numbers. Then, based on the square of the distance in the numerical value between two trapezoidal intuitionistic fuzzy numbers, we establish a corresponding quadratic programming model to obtain the least square prenucleolus, which can effectively avoid the information distortion and uncertainty enlargement brought about by the subtraction of trapezoidal intuitionistic fuzzy numbers. Finally, we give a numerical example about the cost-sharing of ecological construction in Fujian Province in China to show the validity, applicability, and advantages of the proposed model and method.

  13. 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

  14. Quantum information processing with atoms and photons

    International Nuclear Information System (INIS)

    Monroe, C.

    2003-01-01

    Quantum information processors exploit the quantum features of superposition and entanglement for applications not possible in classical devices, offering the potential for significant improvements in the communication and processing of information. Experimental realization of large-scale quantum information processors remains a long term vision, as the required nearly pure quantum behaviour is observed only in exotic hardware such as individual laser-cooled atoms and isolated photons. But recent theoretical and experimental advances suggest that cold atoms and individual photons may lead the way towards bigger and better quantum information processors, effectively building mesoscopic versions of Schroedinger's cat' from the bottom up. (author)

  15. Application of Neuro-Fuzzy to palm oil production process | Odior ...

    African Journals Online (AJOL)

    Palm oil is an important nutritional food requirement and in order to facilitate the production of palm oil for consumption, the production process of palm oil has been investigated. The basic operations involved in the production of edible palm oil include; purchase, transportation and reception of oil palm bunches; bunch ...

  16. 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.

  17. Supplier Assessment and Selection Using Fuzzy Analytic Hierarchy Process in a Steel Manufacturing Company

    OpenAIRE

    Tahriri, Farzad; Ale Ebrahim, Nader; Dabbagh, Mohammad

    2014-01-01

    Every organization needs suppliers and no organization can exist without suppliers. Therefore, the organizations approach to suppliers and the selection of the appropriate supplier, its acquisition processes and policies, and its relationships with suppliers, is of vital importance, both to organizations and suppliers alike. No organization can be successful without the support of its supplier base, operationally and strategically, short or long-term.To select the best supplier, it is essenti...

  18. Algorithmic information theory mathematics of digital information processing

    CERN Document Server

    Seibt, Peter

    2007-01-01

    Treats the Mathematics of many important areas in digital information processing. This book covers, in a unified presentation, five topics: Data Compression, Cryptography, Sampling (Signal Theory), Error Control Codes, Data Reduction. It is useful for teachers, students and practitioners in Electronic Engineering, Computer Science and Mathematics.

  19. PHYSICAL RESOURCES OF INFORMATION PROCESSES AND TECHNOLOGIES

    Directory of Open Access Journals (Sweden)

    Mikhail O. Kolbanev

    2014-11-01

    Full Text Available Subject of study. The paper describes basic information technologies for automating of information processes of data storage, distribution and processing in terms of required physical resources. It is shown that the study of these processes with such traditional objectives of modern computer science, as the ability to transfer knowledge, degree of automation, information security, coding, reliability, and others, is not enough. The reasons are: on the one hand, the increase in the volume and intensity of information exchange in the subject of human activity and, on the other hand, drawing near to the limit of information systems efficiency based on semiconductor technologies. Creation of such technologies, which not only provide support for information interaction, but also consume a rational amount of physical resources, has become an actual problem of modern engineering development. Thus, basic information technologies for storage, distribution and processing of information to support the interaction between people are the object of study, and physical temporal, spatial and energy resources required for implementation of these technologies are the subject of study. Approaches. An attempt is made to enlarge the possibilities of traditional cybernetics methodology, which replaces the consideration of material information component by states search for information objects. It is done by taking explicitly into account the amount of physical resources required for changes in the states of information media. Purpose of study. The paper deals with working out of a common approach to the comparison and subsequent selection of basic information technologies for storage, distribution and processing of data, taking into account not only the requirements for the quality of information exchange in particular subject area and the degree of technology application, but also the amounts of consumed physical resources. Main findings. Classification of resources

  20. Process Information System - Nuclear Power Plant Krsko

    International Nuclear Information System (INIS)

    Mandic, D.; Barbic, B.; Linke, B.; Colak, I.

    1998-01-01

    Original NEK design was using several Process Computer Systems (PCS) for both process control and process supervision. PCS were built by different manufacturers around different hardware and software platforms. Operational experience and new regulatory requirements imposed new technical and functional requirements on the PCS. Requirements such as: - Acquisition of new signals from the technological processes and environment - Implementation of new application programs - Significant improvement of MMI (Man Machine Interface) - Process data transfer to other than Main Control Room (MCR) locations - Process data archiving and capability to retrieve same data for future analysis were impossible to be implemented within old systems. In order to satisfy new requirements, NEK has decided to build new Process Information System (PIS). During the design and construction of the PIS Project Phase I, in addition to the main foreign contractor, there was significant participation of local architect engineering and construction companies. This paper presents experience of NEK and local partners. (author)

  1. Neuro-fuzzy decoding of sensory information from ensembles of simultaneously recorded dorsal root ganglion neurons for functional electrical stimulation applications

    Science.gov (United States)

    Rigosa, J.; Weber, D. J.; Prochazka, A.; Stein, R. B.; Micera, S.

    2011-08-01

    Functional electrical stimulation (FES) is used to improve motor function after injury to the central nervous system. Some FES systems use artificial sensors to switch between finite control states. To optimize FES control of the complex behavior of the musculo-skeletal system in activities of daily life, it is highly desirable to implement feedback control. In theory, sensory neural signals could provide the required control signals. Recent studies have demonstrated the feasibility of deriving limb-state estimates from the firing rates of primary afferent neurons recorded in dorsal root ganglia (DRG). These studies used multiple linear regression (MLR) methods to generate estimates of limb position and velocity based on a weighted sum of firing rates in an ensemble of simultaneously recorded DRG neurons. The aim of this study was to test whether the use of a neuro-fuzzy (NF) algorithm (the generalized dynamic fuzzy neural networks (GD-FNN)) could improve the performance, robustness and ability to generalize from training to test sets compared to the MLR technique. NF and MLR decoding methods were applied to ensemble DRG recordings obtained during passive and active limb movements in anesthetized and freely moving cats. The GD-FNN model provided more accurate estimates of limb state and generalized better to novel movement patterns. Future efforts will focus on implementing these neural recording and decoding methods in real time to provide closed-loop control of FES using the information extracted from sensory neurons.

  2. Neuro-fuzzy decoding of sensory information from ensembles of simultaneously recorded dorsal root ganglion neurons for functional electrical stimulation applications.

    Science.gov (United States)

    Rigosa, J; Weber, D J; Prochazka, A; Stein, R B; Micera, S

    2011-08-01

    Functional electrical stimulation (FES) is used to improve motor function after injury to the central nervous system. Some FES systems use artificial sensors to switch between finite control states. To optimize FES control of the complex behavior of the musculo-skeletal system in activities of daily life, it is highly desirable to implement feedback control. In theory, sensory neural signals could provide the required control signals. Recent studies have demonstrated the feasibility of deriving limb-state estimates from the firing rates of primary afferent neurons recorded in dorsal root ganglia (DRG). These studies used multiple linear regression (MLR) methods to generate estimates of limb position and velocity based on a weighted sum of firing rates in an ensemble of simultaneously recorded DRG neurons. The aim of this study was to test whether the use of a neuro-fuzzy (NF) algorithm (the generalized dynamic fuzzy neural networks (GD-FNN)) could improve the performance, robustness and ability to generalize from training to test sets compared to the MLR technique. NF and MLR decoding methods were applied to ensemble DRG recordings obtained during passive and active limb movements in anesthetized and freely moving cats. The GD-FNN model provided more accurate estimates of limb state and generalized better to novel movement patterns. Future efforts will focus on implementing these neural recording and decoding methods in real time to provide closed-loop control of FES using the information extracted from sensory neurons.

  3. The minimal work cost of information processing

    Science.gov (United States)

    Faist, Philippe; Dupuis, Frédéric; Oppenheim, Jonathan; Renner, Renato

    2015-07-01

    Irreversible information processing cannot be carried out without some inevitable thermodynamical work cost. This fundamental restriction, known as Landauer's principle, is increasingly relevant today, as the energy dissipation of computing devices impedes the development of their performance. Here we determine the minimal work required to carry out any logical process, for instance a computation. It is given by the entropy of the discarded information conditional to the output of the computation. Our formula takes precisely into account the statistically fluctuating work requirement of the logical process. It enables the explicit calculation of practical scenarios, such as computational circuits or quantum measurements. On the conceptual level, our result gives a precise and operational connection between thermodynamic and information entropy, and explains the emergence of the entropy state function in macroscopic thermodynamics.

  4. 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

  5. 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...

  6. Consciousness: a unique way of processing information.

    Science.gov (United States)

    Marchetti, Giorgio

    2018-02-08

    In this article, I argue that consciousness is a unique way of processing information, in that: it produces information, rather than purely transmitting it; the information it produces is meaningful for us; the meaning it has is always individuated. This uniqueness allows us to process information on the basis of our personal needs and ever-changing interactions with the environment, and consequently to act autonomously. Three main basic cognitive processes contribute to realize this unique way of information processing: the self, attention and working memory. The self, which is primarily expressed via the central and peripheral nervous systems, maps our body, the environment, and our relations with the environment. It is the primary means by which the complexity inherent to our composite structure is reduced into the "single voice" of a unique individual. It provides a reference system that (albeit evolving) is sufficiently stable to define the variations that will be used as the raw material for the construction of conscious information. Attention allows for the selection of those variations in the state of the self that are most relevant in the given situation. Attention originates and is deployed from a single locus inside our body, which represents the center of the self, around which all our conscious experiences are organized. Whatever is focused by attention appears in our consciousness as possessing a spatial quality defined by this center and the direction toward which attention is focused. In addition, attention determines two other features of conscious experience: periodicity and phenomenal quality. Self and attention are necessary but not sufficient for conscious information to be produced. Complex forms of conscious experiences, such as the various modes of givenness of conscious experience and the stream of consciousness, need a working memory mechanism to assemble the basic pieces of information selected by attention.

  7. A framework for information warehouse development processes

    OpenAIRE

    Holten, Roland

    1999-01-01

    Since the terms Data Warehouse and On-Line Analytical Processing were proposed by Inmon and Codd, Codd, Sally respectively the traditional ideas of creating information systems in support of management¿s decision became interesting again in theory and practice. Today information warehousing is a strategic market for any data base systems vendor. Nevertheless the theoretical discussions of this topic go back to the early years of the 20th century as far as management science and accounting the...

  8. Fuzzy Treatment of Candidate Outliers in Measurements

    Directory of Open Access Journals (Sweden)

    Giampaolo E. D'Errico

    2012-01-01

    Full Text Available Robustness against the possible occurrence of outlying observations is critical to the performance of a measurement process. Open questions relevant to statistical testing for candidate outliers are reviewed. A novel fuzzy logic approach is developed and exemplified in a metrology context. A simulation procedure is presented and discussed by comparing fuzzy versus probabilistic models.

  9. Modeling Research Project Risks with Fuzzy Maps

    Science.gov (United States)

    Bodea, Constanta Nicoleta; Dascalu, Mariana Iuliana

    2009-01-01

    The authors propose a risks evaluation model for research projects. The model is based on fuzzy inference. The knowledge base for fuzzy process is built with a causal and cognitive map of risks. The map was especially developed for research projects, taken into account their typical lifecycle. The model was applied to an e-testing research…

  10. Parallel fuzzy connected image segmentation on GPU

    OpenAIRE

    Zhuge, Ying; Cao, Yong; Udupa, Jayaram K.; Miller, Robert W.

    2011-01-01

    Purpose: Image segmentation techniques using fuzzy connectedness (FC) principles have shown their effectiveness in segmenting a variety of objects in several large applications. However, one challenge in these algorithms has been their excessive computational requirements when processing large image datasets. Nowadays, commodity graphics hardware provides a highly parallel computing environment. In this paper, the authors present a parallel fuzzy connected image segmentation algorithm impleme...

  11. Markovian Processes for Quantitative Information Leakage

    DEFF Research Database (Denmark)

    Biondi, Fabrizio

    Quantification of information leakage is a successful approach for evaluating the security of a system. It models the system to be analyzed as a channel with the secret as the input and an output as observable by the attacker as the output, and applies information theory to quantify the amount...... and randomized processes with Markovian models and to compute their information leakage for a very general model of attacker. We present the QUAIL tool that automates such analysis and is able to compute the information leakage of an imperative WHILE language. Finally, we show how to use QUAIL to analyze some...... of information transmitted through such channel, thus effectively quantifying how many bits of the secret can be inferred by the attacker by analyzing the system’s output. Channels are usually encoded as matrices of conditional probabilities, known as channel matrices. Such matrices grow exponentially...

  12. Optimal Information Processing in Biochemical Networks

    Science.gov (United States)

    Wiggins, Chris

    2012-02-01

    A variety of experimental results over the past decades provide examples of near-optimal information processing in biological networks, including in biochemical and transcriptional regulatory networks. Computing information-theoretic quantities requires first choosing or computing the joint probability distribution describing multiple nodes in such a network --- for example, representing the probability distribution of finding an integer copy number of each of two interacting reactants or gene products while respecting the `intrinsic' small copy number noise constraining information transmission at the scale of the cell. I'll given an overview of some recent analytic and numerical work facilitating calculation of such joint distributions and the associated information, which in turn makes possible numerical optimization of information flow in models of noisy regulatory and biochemical networks. Illustrating cases include quantification of form-function relations, ideal design of regulatory cascades, and response to oscillatory driving.

  13. Hesitant fuzzy methods for multiple criteria decision analysis

    CERN Document Server

    Zhang, Xiaolu

    2017-01-01

    The book offers a comprehensive introduction to methods for solving multiple criteria decision making and group decision making problems with hesitant fuzzy information. It reports on the authors’ latest research, as well as on others’ research, providing readers with a complete set of decision making tools, such as hesitant fuzzy TOPSIS, hesitant fuzzy TODIM, hesitant fuzzy LINMAP, hesitant fuzzy QUALIFEX, and the deviation modeling approach with heterogeneous fuzzy information. The main focus is on decision making problems in which the criteria values and/or the weights of criteria are not expressed in crisp numbers but are more suitable to be denoted as hesitant fuzzy elements. The largest part of the book is devoted to new methods recently developed by the authors to solve decision making problems in situations where the available information is vague or hesitant. These methods are presented in detail, together with their application to different type of decision-making problems. All in all, the book ...

  14. Scalable Networked Information Processing Environment (SNIPE)

    Energy Technology Data Exchange (ETDEWEB)

    Fagg, G.E.; Moore, K. [Univ. of Tennessee, Knoxville, TN (United States). Dept. of Computer Science; Dongarra, J.J. [Univ. of Tennessee, Knoxville, TN (United States). Dept. of Computer Science]|[Oak Ridge National Lab., TN (United States). Computer Science and Mathematics Div.; Geist, A. [Oak Ridge National Lab., TN (United States). Computer Science and Mathematics Div.

    1997-11-01

    SNIPE is a metacomputing system that aims to provide a reliable, secure, fault tolerant environment for long term distributed computing applications and data stores across the global Internet. This system combines global naming and replication of both processing and data to support large scale information processing applications leading to better availability and reliability than currently available with typical cluster computing and/or distributed computer environments.

  15. A reduced-form intensity-based model under fuzzy environments

    Science.gov (United States)

    Wu, Liang; Zhuang, Yaming

    2015-05-01

    The external shocks and internal contagion are the important sources of default events. However, the external shocks and internal contagion effect on the company is not observed, we cannot get the accurate size of the shocks. The information of investors relative to the default process exhibits a certain fuzziness. Therefore, using randomness and fuzziness to study such problems as derivative pricing or default probability has practical needs. But the idea of fuzzifying credit risk models is little exploited, especially in a reduced-form model. This paper proposes a new default intensity model with fuzziness and presents a fuzzy default probability and default loss rate, and puts them into default debt and credit derivative pricing. Finally, the simulation analysis verifies the rationality of the model. Using fuzzy numbers and random analysis one can consider more uncertain sources in the default process of default and investors' subjective judgment on the financial markets in a variety of fuzzy reliability so as to broaden the scope of possible credit spreads.

  16. Detection of Stator Winding Fault in Induction Motor Using Fuzzy Logic with Optimal Rules

    Directory of Open Access Journals (Sweden)

    Hamid Fekri Azgomi

    2013-04-01

    Full Text Available Induction motors are critical components in many industrial processes. Therefore, swift, precise and reliable monitoring and fault detection systems are required to prevent any further damages. The online monitoring of induction motors has been becoming increasingly important. The main difficulty in this task is the lack of an accurate analytical model to describe a faulty motor. A fuzzy logic approach may help to diagnose traction motor faults. This paper presents a simple method for the detection of stator winding faults (which make up 38% of induction motor failures based on monitoring the line/terminal current amplitudes. In this method, fuzzy logic is used to make decisions about the stator motor condition. In fact, fuzzy logic is reminiscent of human thinking processes and natural language enabling decisions to be made based on vague information. The motor condition is described using linguistic variables. Fuzzy subsets and the corresponding membership functions describe stator current amplitudes. A knowledge base, comprising rule and data bases, is built to support the fuzzy inference. Simulation results are presented to verify the accuracy of motor’s fault detection and knowledge extraction feasibility. The preliminary results show that the proposed fuzzy approach can be used for accurate stator fault diagnosis.

  17. Application of an advanced fuzzy logic model for landslide susceptibility analysis

    Directory of Open Access Journals (Sweden)

    Biswajeet Pradhan

    2010-09-01

    Full Text Available The aim of this study is to evaluate the susceptibility of landslides at Klang valley area, Malaysia, using a Geographic Information System (GIS and remote sensing. Landslide locations were identified in the study area from interpretation of aerial photographs and from field surveys. Topographical and geological data and satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. A data derived model (frequency ratio and a knowledge-derived model (fuzzy operator were combined for landslide susceptibility analysis. The nine factors that influence landslide occurrence were extracted from the database and the frequency ratio coefficient for each factor was computed. Using the factors and the identified landslide, the fuzzy membership values were calculated. Then fuzzy algebraic operators were applied to the fuzzy membership values for landslide susceptibility mapping. Finally, the produced map was verified by comparing with existing landslide locations for calculating prediction accuracy. Among the fuzzy operators, in the case in which the gamma operator (l = 0.8 showed the best accuracy (91% while the case in which the fuzzy algebraic product was applied showed the worst accuracy (79%.

  18. Network-based Type-2 Fuzzy System with Water Flow Like Algorithm for System Identification and Signal Processing

    Directory of Open Access Journals (Sweden)

    Che-Ting Kuo

    2015-02-01

    Full Text Available This paper introduces a network-based interval type-2 fuzzy inference system (NT2FIS with a dynamic solution agent algorithm water flow like algorithm (WFA, for nonlinear system identification and blind source separation (BSS problem. The NT2FIS consists of interval type-2 asymmetric fuzzy membership functions and TSK-type consequent parts to enhance the performance. The proposed scheme is optimized by a new heuristic learning algorithm, WFA, with dynamic solution agents. The proposed WFA is inspired by the natural behavior of water flow. Splitting, moving, merging, evaporation, and precipitation have all been introduced for optimization. Some modifications, including new moving strategies, such as the application of tabu searching and gradient-descent techniques, are proposed to enhance the performance of the WFA in training the NT2FIS systems. Simulation and comparison results for nonlinear system identification and blind signal separation are presented to illustrate the performance and effectiveness of the proposed approach.

  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. Information Processing in Auto-regulated Systems

    Directory of Open Access Journals (Sweden)

    Karl Javorszky

    2003-06-01

    Full Text Available Abstract: We present a model of information processing which is based on two concurrent ways of describing the world, where a description in one of the languages limits the possibilities for realisations in the other language. The two describing dimensions appear in our common sense as dichotomies of perspectives: subjective - objective; diversity - similarity; individual - collective. We abstract from the subjective connotations and treat the test theoretical case of an interval on which several concurrent categories can be introduced. We investigate multidimensional partitions as potential carriers of information and compare their efficiency to that of sequenced carriers. We regard the same assembly once as a contemporary collection, once as a longitudinal sequence and find promising inroads towards understanding information processing by auto-regulated systems. Information is understood to point out that what is the case from among alternatives, which could be the case. We have translated these ideas into logical operations on the set of natural numbers and have found two equivalence points on N where matches between sequential and commutative ways of presenting a state of the world can agree in a stable fashion: a flip-flop mechanism is envisioned. By following this new approach, a mathematical treatment of some poignant biomathematical problems is allowed. Also, the concepts presented in this treatise may well have relevance and applications within the information processing and the theory of language fields.

  1. Springfield Processing Plant (SPP) Facility Information

    Energy Technology Data Exchange (ETDEWEB)

    Leach, Janice; Torres, Teresa M.

    2012-10-01

    The Springfield Processing Plant is a hypothetical facility. It has been constructed for use in training workshops. Information is provided about the facility and its surroundings, particularly security-related aspects such as target identification, threat data, entry control, and response force data.

  2. Motivated information processing and group decision refusal

    NARCIS (Netherlands)

    Nijstad, Bernard A.; Oltmanns, Jan

    Group decision making has attracted much scientific interest, but few studies have investigated group decisions that do not get made. Based on the Motivated Information Processing in Groups model, this study analysed the effect of epistemic motivation (low vs. high) and social motivation (proself

  3. Multidimensional biochemical information processing of dynamical patterns.

    Science.gov (United States)

    Hasegawa, Yoshihiko

    2018-02-01

    Cells receive signaling molecules by receptors and relay information via sensory networks so that they can respond properly depending on the type of signal. Recent studies have shown that cells can extract multidimensional information from dynamical concentration patterns of signaling molecules. We herein study how biochemical systems can process multidimensional information embedded in dynamical patterns. We model the decoding networks by linear response functions, and optimize the functions with the calculus of variations to maximize the mutual information between patterns and output. We find that, when the noise intensity is lower, decoders with different linear response functions, i.e., distinct decoders, can extract much information. However, when the noise intensity is higher, distinct decoders do not provide the maximum amount of information. This indicates that, when transmitting information by dynamical patterns, embedding information in multiple patterns is not optimal when the noise intensity is very large. Furthermore, we explore the biochemical implementations of these decoders using control theory and demonstrate that these decoders can be implemented biochemically through the modification of cascade-type networks, which are prevalent in actual signaling pathways.

  4. Solving multi-objective facility location problem using the fuzzy analytical hierarchy process and goal programming: a case study on infectious waste disposal centers

    Directory of Open Access Journals (Sweden)

    Narong Wichapa

    Full Text Available The selection of a suitable location for infectious waste disposal is one of the major problems in waste management. Determining the location of infectious waste disposal centers is a difficult and complex process because it requires combining social and environmental factors that are hard to interpret, and cost factors that require the allocation of resources. Additionally, it depends on several regulations. Based on the actual conditions of a case study, forty hospitals and three candidate municipalities in the sub-Northeast region of Thailand, we considered multiple factors such as infrastructure, geological and social & environmental factors, calculating global priority weights using the fuzzy analytical hierarchy process (FAHP. After that, a new multi-objective facility location problem model which combines FAHP and goal programming (GP, namely the FAHP-GP model, was tested. The proposed model can lead to selecting new suitable locations for infectious waste disposal by considering both total cost and final priority weight objectives. The novelty of the proposed model is the simultaneous combination of relevant factors that are difficult to interpret and cost factors, which require the allocation of resources. Keywords: Multi-objective facility location problem, Fuzzy analytic hierarchy process, Infectious waste disposal centers

  5. Information processing in the vertebrate habenula.

    Science.gov (United States)

    Fore, Stephanie; Palumbo, Fabrizio; Pelgrims, Robbrecht; Yaksi, Emre

    2018-06-01

    The habenula is a brain region that has gained increasing popularity over the recent years due to its role in processing value-related and experience-dependent information with a strong link to depression, addiction, sleep and social interactions. This small diencephalic nucleus is proposed to act as a multimodal hub or a switchboard, where inputs from different brain regions converge. These diverse inputs to the habenula carry information about the sensory world and the animal's internal state, such as reward expectation or mood. However, it is not clear how these diverse habenular inputs interact with each other and how such interactions contribute to the function of habenular circuits in regulating behavioral responses in various tasks and contexts. In this review, we aim to discuss how information processing in habenular circuits, can contribute to specific behavioral programs that are attributed to the habenula. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. 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)

  7. Testing an alternate informed consent process.

    Science.gov (United States)

    Yates, Bernice C; Dodendorf, Diane; Lane, Judy; LaFramboise, Louise; Pozehl, Bunny; Duncan, Kathleen; Knodel, Kendra

    2009-01-01

    One of the main problems in conducting clinical trials is low participation rate due to potential participants' misunderstanding of the rationale for the clinical trial or perceptions of loss of control over treatment decisions. The objective of this study was to test an alternate informed consent process in cardiac rehabilitation participants that involved the use of a multimedia flip chart to describe a future randomized clinical trial and then asked, hypothetically, if they would participate in the future trial. An attractive and inviting visual presentation of the study was created in the form of a 23-page flip chart that included 24 color photographs displaying information about the purpose of the study, similarities and differences between the two treatment groups, and the data collection process. We tested the flip chart in 35 cardiac rehabilitation participants. Participants were asked if they would participate in this future study on two occasions: immediately after the description of the flip chart and 24 hours later, after reading through the informed consent document. Participants were also asked their perceptions of the flip chart and consent process. Of the 35 participants surveyed, 19 (54%) indicated that they would participate in the future study. No participant changed his or her decision 24 hours later after reading the full consent form. The participation rate improved 145% over that of an earlier feasibility study where the recruitment rate was 22%. Most participants stated that the flip chart was helpful and informative and that the photographs were effective in communicating the purpose of the study. Participation rates could be enhanced in future clinical trials by using a visual presentation to explain and describe the study as part of the informed consent process. More research is needed to test alternate methods of obtaining informed consent.

  8. Information Processing Capacity of Dynamical Systems

    Science.gov (United States)

    Dambre, Joni; Verstraeten, David; Schrauwen, Benjamin; Massar, Serge

    2012-07-01

    Many dynamical systems, both natural and artificial, are stimulated by time dependent external signals, somehow processing the information contained therein. We demonstrate how to quantify the different modes in which information can be processed by such systems and combine them to define the computational capacity of a dynamical system. This is bounded by the number of linearly independent state variables of the dynamical system, equaling it if the system obeys the fading memory condition. It can be interpreted as the total number of linearly independent functions of its stimuli the system can compute. Our theory combines concepts from machine learning (reservoir computing), system modeling, stochastic processes, and functional analysis. We illustrate our theory by numerical simulations for the logistic map, a recurrent neural network, and a two-dimensional reaction diffusion system, uncovering universal trade-offs between the non-linearity of the computation and the system's short-term memory.

  9. Information Processing Capacity of Dynamical Systems

    Science.gov (United States)

    Dambre, Joni; Verstraeten, David; Schrauwen, Benjamin; Massar, Serge

    2012-01-01

    Many dynamical systems, both natural and artificial, are stimulated by time dependent external signals, somehow processing the information contained therein. We demonstrate how to quantify the different modes in which information can be processed by such systems and combine them to define the computational capacity of a dynamical system. This is bounded by the number of linearly independent state variables of the dynamical system, equaling it if the system obeys the fading memory condition. It can be interpreted as the total number of linearly independent functions of its stimuli the system can compute. Our theory combines concepts from machine learning (reservoir computing), system modeling, stochastic processes, and functional analysis. We illustrate our theory by numerical simulations for the logistic map, a recurrent neural network, and a two-dimensional reaction diffusion system, uncovering universal trade-offs between the non-linearity of the computation and the system's short-term memory. PMID:22816038

  10. 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.

  11. 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.

  12. IMPLEMENTATION OF FUZZY LOGIC BASED TEMPERATURE ...

    African Journals Online (AJOL)

    transfer function is derived based on process reaction curve obtained from a heat exchanger pilot plant ... The results show that the control performance for a Fuzzy controller is quite similar to ..... Process. Control Instrumentation Technology.

  13. Fuzzy view of environment

    Directory of Open Access Journals (Sweden)

    Bajat Branislav

    2007-01-01

    Full Text Available A period of fifty years has been reached since the introduction of the first applications based upon geographical information systems (GIS. GIS has not only influenced the development of methods, collection techniques, processing, manipulation and visualization of spatial data. It influenced also the expansion of scientific research in geosciences, as well as the technical disciplines that are engaged in spatial analysis. Nowadays, GIS is becoming the tool for verification and practical implementation of models and algorithms that have been developed within the frame of basic scientific disciplines. The meaning of the GIS acronym is becoming more and more related to term of Geographical or Geo Information Sciences. Scientific concepts that are increasingly applied in GIS are more emphasized in that way. GIS computational techniques, required also the development of geographical data models that should effectively support GIS operations. These models represent formal equivalents of conceptual models used by people in observing geographic phenomena. Spatial phenomena used to be mapped as clearly defined points with known coordinates, or as lines which connect the very same points, or as polygons with exactly defined borders. They were mapped previously in analog form and nowadays in digital format. This approach of perceiving a space, data analyses and visualization of spatial quires is limited on the application of basic rules of Boolean algebra and binary logic, with final results presented as classical thematic maps. The need for a mathematical model that would describe uncertainty of spatial data, resulted in the introduction of the theory of fuzzy sets in spatial analysis. Moreover, this model will provide a solution for visualization and grouping up of spatial phenomena in classes which do not have clearly defined borders.

  14. Intelligent control-II: review of fuzzy systems and theory of approximate reasoning

    International Nuclear Information System (INIS)

    Nagrial, M.H.

    2004-01-01

    Fuzzy systems are knowledge-based or rule-based systems. The heart of a fuzzy systems knowledge base consisting of the so-called fuzzy IF -THEN rules. This paper reviews various aspects of fuzzy IF-THEN rules. The theory of approximate reasoning, which provides a powerful framework for reasoning the imprecise and uncertain information, , is also reviewed. Additional properties of fuzzy systems are also discussed. (author)

  15. Abrasive slurry jet cutting model based on fuzzy relations

    Science.gov (United States)

    Qiang, C. H.; Guo, C. W.

    2017-12-01

    The cutting process of pre-mixed abrasive slurry or suspension jet (ASJ) is a complex process affected by many factors, and there is a highly nonlinear relationship between the cutting parameters and cutting quality. In this paper, guided by fuzzy theory, the fuzzy cutting model of ASJ was developed. In the modeling of surface roughness, the upper surface roughness prediction model and the lower surface roughness prediction model were established respectively. The adaptive fuzzy inference system combines the learning mechanism of neural networks and the linguistic reasoning ability of the fuzzy system, membership functions, and fuzzy rules are obtained by adaptive adjustment. Therefore, the modeling process is fast and effective. In this paper, the ANFIS module of MATLAB fuzzy logic toolbox was used to establish the fuzzy cutting model of ASJ, which is found to be quite instrumental to ASJ cutting applications.

  16. Expectation, information processing, and subjective duration.

    Science.gov (United States)

    Simchy-Gross, Rhimmon; Margulis, Elizabeth Hellmuth

    2018-01-01

    In research on psychological time, it is important to examine the subjective duration of entire stimulus sequences, such as those produced by music (Teki, Frontiers in Neuroscience, 10, 2016). Yet research on the temporal oddball illusion (according to which oddball stimuli seem longer than standard stimuli of the same duration) has examined only the subjective duration of single events contained within sequences, not the subjective duration of sequences themselves. Does the finding that oddballs seem longer than standards translate to entire sequences, such that entire sequences that contain oddballs seem longer than those that do not? Is this potential translation influenced by the mode of information processing-whether people are engaged in direct or indirect temporal processing? Two experiments aimed to answer both questions using different manipulations of information processing. In both experiments, musical sequences either did or did not contain oddballs (auditory sliding tones). To manipulate information processing, we varied the task (Experiment 1), the sequence event structure (Experiments 1 and 2), and the sequence familiarity (Experiment 2) independently within subjects. Overall, in both experiments, the sequences that contained oddballs seemed shorter than those that did not when people were engaged in direct temporal processing, but longer when people were engaged in indirect temporal processing. These findings support the dual-process contingency model of time estimation (Zakay, Attention, Perception & Psychophysics, 54, 656-664, 1993). Theoretical implications for attention-based and memory-based models of time estimation, the pacemaker accumulator and coding efficiency hypotheses of time perception, and dynamic attending theory are discussed.

  17. 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

  18. Towards a Fuzzy Expert System on Toxicological Data Quality Assessment.

    Science.gov (United States)

    Yang, Longzhi; Neagu, Daniel; Cronin, Mark T D; Hewitt, Mark; Enoch, Steven J; Madden, Judith C; Przybylak, Katarzyna

    2013-01-01

    Quality assessment (QA) requires high levels of domain-specific experience and knowledge. QA tasks for toxicological data are usually performed by human experts manually, although a number of quality evaluation schemes have been proposed in the literature. For instance, the most widely utilised Klimisch scheme1 defines four data quality categories in order to tag data instances with respect to their qualities; ToxRTool2 is an extension of the Klimisch approach aiming to increase the transparency and harmonisation of the approach. Note that the processes of QA in many other areas have been automatised by employing expert systems. Briefly, an expert system is a computer program that uses a knowledge base built upon human expertise, and an inference engine that mimics the reasoning processes of human experts to infer new statements from incoming data. In particular, expert systems have been extended to deal with the uncertainty of information by representing uncertain information (such as linguistic terms) as fuzzy sets under the framework of fuzzy set theory and performing inferences upon fuzzy sets according to fuzzy arithmetic. This paper presents an experimental fuzzy expert system for toxicological data QA which is developed on the basis of the Klimisch approach and the ToxRTool in an effort to illustrate the power of expert systems to toxicologists, and to examine if fuzzy expert systems are a viable solution for QA of toxicological data. Such direction still faces great difficulties due to the well-known common challenge of toxicological data QA that "five toxicologists may have six opinions". In the meantime, this challenge may offer an opportunity for expert systems because the construction and refinement of the knowledge base could be a converging process of different opinions which is of significant importance for regulatory policy making under the regulation of REACH, though a consensus may never be reached. Also, in order to facilitate the implementation

  19. Disjunctive Information Flow for Communicating Processes

    DEFF Research Database (Denmark)

    Li, Ximeng; Nielson, Flemming; Nielson, Hanne Riis

    2016-01-01

    The security validation of practical computer systems calls for the ability to specify and verify information flow policies that are dependent on data content. Such policies play an important role in concurrent, communicating systems: consider a scenario where messages are sent to different...... processes according to their tagging. We devise a security type system that enforces content-dependent information flow policies in the presence of communication and concurrency. The type system soundly guarantees a compositional noninterference property. All theoretical results have been formally proved...

  20. Information processing of earth resources data

    Science.gov (United States)

    Zobrist, A. L.; Bryant, N. A.

    1982-01-01

    Current trends in the use of remotely sensed data include integration of multiple data sources of various formats and use of complex models. These trends have placed a strain on information processing systems because an enormous number of capabilities are needed to perform a single application. A solution to this problem is to create a general set of capabilities which can perform a wide variety of applications. General capabilities for the Image-Based Information System (IBIS) are outlined in this report. They are then cross-referenced for a set of applications performed at JPL.

  1. A Hybrid Fuzzy Model for Lean Product Development Performance Measurement

    Science.gov (United States)

    Osezua Aikhuele, Daniel; Mohd Turan, Faiz

    2016-02-01

    In the effort for manufacturing companies to meet up with the emerging consumer demands for mass customized products, many are turning to the application of lean in their product development process, and this is gradually moving from being a competitive advantage to a necessity. However, due to lack of clear understanding of the lean performance measurements, many of these companies are unable to implement and fully integrated the lean principle into their product development process. Extensive literature shows that only few studies have focus systematically on the lean product development performance (LPDP) evaluation. In order to fill this gap, the study therefore proposed a novel hybrid model based on Fuzzy Reasoning Approach (FRA), and the extension of Fuzzy-AHP and Fuzzy-TOPSIS methods for the assessment of the LPDP. Unlike the existing methods, the model considers the importance weight of each of the decision makers (Experts) since the performance criteria/attributes are required to be rated, and these experts have different level of expertise. The rating is done using a new fuzzy Likert rating scale (membership-scale) which is designed such that it can address problems resulting from information lost/distortion due to closed-form scaling and the ordinal nature of the existing Likert scale.

  2. Influence Processes for Information Technology Acceptance

    DEFF Research Database (Denmark)

    Bhattacherjee, Anol; Sanford, Clive Carlton

    2006-01-01

    This study examines how processes of external influence shape information technology acceptance among potential users, how such influence effects vary across a user population, and whether these effects are persistent over time. Drawing on the elaboration-likelihood model (ELM), we compared two...... alternative influence processes, the central and peripheral routes, in motivating IT acceptance. These processes were respectively operationalized using the argument quality and source credibility constructs, and linked to perceived usefulness and attitude, the core perceptual drivers of IT acceptance. We...... further examined how these influence processes were moderated by users' IT expertise and perceived job relevance and the temporal stability of such influence effects. Nine hypotheses thus developed were empirically validated using a field survey of document management system acceptance at an eastern...

  3. 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.

  4. Visual Information Processing for Television and Telerobotics

    Science.gov (United States)

    Huck, Friedrich O. (Editor); Park, Stephen K. (Editor)

    1989-01-01

    This publication is a compilation of the papers presented at the NASA conference on Visual Information Processing for Television and Telerobotics. The conference was held at the Williamsburg Hilton, Williamsburg, Virginia on May 10 to 12, 1989. The conference was sponsored jointly by NASA Offices of Aeronautics and Space Technology (OAST) and Space Science and Applications (OSSA) and the NASA Langley Research Center. The presentations were grouped into three sessions: Image Gathering, Coding, and Advanced Concepts; Systems; and Technologies. The program was organized to provide a forum in which researchers from industry, universities, and government could be brought together to discuss the state of knowledge in image gathering, coding, and processing methods.

  5. 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.

  6. 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...

  7. Quantum information processing with trapped ions

    International Nuclear Information System (INIS)

    Haeffner, H.; Haensel, W.; Rapol, U.; Koerber, T.; Benhelm, J.; Riebe, M.; Chek-al-Kar, D.; Schmidt-Kaler, F.; Becher, C.; Roos, C.; Blatt, R.

    2005-01-01

    Single Ca + ions and crystals of Ca + ions are confined in a linear Paul trap and are investigated for quantum information processing. Here we report on recent experimental advancements towards a quantum computer with such a system. Laser-cooled trapped ions are ideally suited systems for the investigation and implementation of quantum information processing as one can gain almost complete control over their internal and external degrees of freedom. The combination of a Paul type ion trap with laser cooling leads to unique properties of trapped cold ions, such as control of the motional state down to the zero-point of the trapping potential, a high degree of isolation from the environment and thus a very long time available for manipulations and interactions at the quantum level. The very same properties make single trapped atoms and ions well suited for storing quantum information in long lived internal states, e.g. by encoding a quantum bit (qubit) of information within the coherent superposition of the S 1/2 ground state and the metastable D 5/2 excited state of Ca + . Recently we have achieved the implementation of simple algorithms with up to 3 qubits on an ion-trap quantum computer. We will report on methods to implement single qubit rotations, the realization of a two-qubit universal quantum gate (Cirac-Zoller CNOT-gate), the deterministic generation of multi-particle entangled states (GHZ- and W-states), their full tomographic reconstruction, the realization of deterministic quantum teleportation, its quantum process tomography and the encoding of quantum information in decoherence-free subspaces with coherence times exceeding 20 seconds. (author)

  8. Quantum Information Processing with Trapped Ions

    International Nuclear Information System (INIS)

    Barrett, M.D.; Schaetz, T.; Chiaverini, J.; Leibfried, D.; Britton, J.; Itano, W.M.; Jost, J.D.; Langer, C.; Ozeri, R.; Wineland, D.J.; Knill, E.

    2005-01-01

    We summarize two experiments on the creation and manipulation of multi-particle entangled states of trapped atomic ions - quantum dense coding and quantum teleportation. The techniques used in these experiments constitute an important step toward performing large-scale quantum information processing. The techniques also have application in other areas of physics, providing improvement in quantum-limited measurement and fundamental tests of quantum mechanical principles, for example

  9. Human Information Processing and Supervisory Control.

    Science.gov (United States)

    1980-05-01

    errors (that is of the output of the human operator). There is growing evidence (Senders, personal communication; Norman , personal communication...relates to the relative tendency to depend on sensory information or to be more analytic and independent. Norman (personal communication) has referred...decision process model. Ergonomics, 12, 543-557. Senders, J., Elkid, J., Grignetti, M., & Smallwood , R. 1966. An investigation of the visual sampling

  10. Aiming for knowledge information processing systems

    Energy Technology Data Exchange (ETDEWEB)

    Fuchi, K

    1982-01-01

    The Fifth Generation Computer Project in Japan intends to develop a new generation of computers by extensive research in many areas. This paper discusses many research topics which the Japanese are hoping will lead to a radical new knowledge information processing system. Topics discussed include new computer architecture, programming styles, semantics of programming languages, relational databases, linguistics theory, artificial intelligence, functional images and interference systems.

  11. Processing Information in Quantum Decision Theory

    OpenAIRE

    Yukalov, V. I.; Sornette, D.

    2008-01-01

    A survey is given summarizing the state of the art of describing information processing in Quantum Decision Theory, which has been recently advanced as a novel variant of decision making, based on the mathematical theory of separable Hilbert spaces. This mathematical structure captures the effect of superposition of composite prospects, including many incorporated intended actions. The theory characterizes entangled decision making, non-commutativity of subsequent decisions, and intention int...

  12. Manipulating cold atoms for quantum information processing

    International Nuclear Information System (INIS)

    Knight, P.

    2005-01-01

    Full text: I will describe how cold atoms can be manipulated to realize arrays of addressable qbits as prototype quantum registers, focussing on how atom chips can be used in combination with cavity qed techniques to form such an array. I will discuss how the array can be generated and steered using optical lattices and the Mott transition, and describe the sources of noise and how these place limits on the use of such chips in quantum information processing. (author)

  13. Quantum information processing and nuclear magnetic resonance

    International Nuclear Information System (INIS)

    Cummins, H.K.

    2001-01-01

    Quantum computers are information processing devices which operate by and exploit the laws of quantum mechanics, potentially allowing them to solve problems which are intractable using classical computers. This dissertation considers the practical issues involved in one of the more successful implementations to date, nuclear magnetic resonance (NMR). Techniques for dealing with systematic errors are presented, and a quantum protocol is implemented. Chapter 1 is a brief introduction to quantum computation. The physical basis of its efficiency and issues involved in its implementation are discussed. NMR quantum information processing is reviewed in more detail in Chapter 2. Chapter 3 considers some of the errors that may be introduced in the process of implementing an algorithm, and high-level ways of reducing the impact of these errors by using composite rotations. Novel general expressions for stabilising composite rotations are presented in Chapter 4 and a new class of composite rotations, tailored composite rotations, presented in Chapter 5. Chapter 6 describes some of the advantages and pitfalls of combining composite rotations. Experimental evaluations of the composite rotations are given in each case. An actual implementation of a quantum information protocol, approximate quantum cloning, is presented in Chapter 7. The dissertation ends with appendices which contain expansions of some equations and detailed calculations of certain composite rotation results, as well as spectrometer pulse sequence programs. (author)

  14. Using the fuzzy modeling for the retrieval algorithms

    International Nuclear Information System (INIS)

    Mohamed, A.H

    2010-01-01

    A rapid growth in number and size of images in databases and world wide web (www) has created a strong need for more efficient search and retrieval systems to exploit the benefits of this large amount of information. However, the collection of this information is now based on the image technology. One of the limitations of the current image analysis techniques necessitates that most image retrieval systems use some form of text description provided by the users as the basis to index and retrieve images. To overcome this problem, the proposed system introduces the using of fuzzy modeling to describe the image by using the linguistic ambiguities. Also, the proposed system can include vague or fuzzy terms in modeling the queries to match the image descriptions in the retrieval process. This can facilitate the indexing and retrieving process, increase their performance and decrease its computational time . Therefore, the proposed system can improve the performance of the traditional image retrieval algorithms.

  15. Using an adaptive fuzzy-logic system to optimize the performances and the reduction of chattering phenomenon in the control of induction motor

    Directory of Open Access Journals (Sweden)

    Barazane Linda

    2009-01-01

    Full Text Available Neural networks and fuzzy inference systems are becoming well recognized tools of designing an identifier/controller capable of perceiving the operating environment and imitating a human operator with high performance. Also, by combining these two features, more versatile and robust models, called 'neuro-fuzzy' architectures have been developed. The motivation behind the use of neuro-fuzzy approaches is based on the complexity of real life systems, ambiguities on sensory information or time-varying nature of the system under investigation. In this way, the present contribution concerns the application of neuro-fuzzy approach in order to perform the responses of the speed regulation and to reduce the chattering phenomenon introduced by sliding mode control, which is very harmful to the actuators in our case and may excite the unmodeled dynamics of the system. The type of the neuro-fuzzy system used here is called:' adaptive neuro fuzzy inference controller (ANFIS'. This neuro-fuzzy is destined to replace the speed fuzzy sliding mode controller after its training process. Simulation results reveal some very interesting features. .

  16. 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

  17. Fuzzy logic algorithm for quantitative tissue characterization of diffuse liver diseases from ultrasound images.

    Science.gov (United States)

    Badawi, A M; Derbala, A S; Youssef, A M

    1999-08-01

    Computerized ultrasound tissue characterization has become an objective means for diagnosis of liver diseases. It is difficult to differentiate diffuse liver diseases, namely cirrhotic and fatty liver by visual inspection from the ultrasound images. The visual criteria for differentiating diffused diseases are rather confusing and highly dependent upon the sonographer's experience. This often causes a bias effects in the diagnostic procedure and limits its objectivity and reproducibility. Computerized tissue characterization to assist quantitatively the sonographer for the accurate differentiation and to minimize the degree of risk is thus justified. Fuzzy logic has emerged as one of the most active area in classification. In this paper, we present an approach that employs Fuzzy reasoning techniques to automatically differentiate diffuse liver diseases using numerical quantitative features measured from the ultrasound images. Fuzzy rules were generated from over 140 cases consisting of normal, fatty, and cirrhotic livers. The input to the fuzzy system is an eight dimensional vector of feature values: the mean gray level (MGL), the percentile 10%, the contrast (CON), the angular second moment (ASM), the entropy (ENT), the correlation (COR), the attenuation (ATTEN) and the speckle separation. The output of the fuzzy system is one of the three categories: cirrhosis, fatty or normal. The steps done for differentiating the pathologies are data acquisition and feature extraction, dividing the input spaces of the measured quantitative data into fuzzy sets. Based on the expert knowledge, the fuzzy rules are generated and applied using the fuzzy inference procedures to determine the pathology. Different membership functions are developed for the input spaces. This approach has resulted in very good sensitivities and specificity for classifying diffused liver pathologies. This classification technique can be used in the diagnostic process, together with the history

  18. 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.

  19. Multi-dimensional Fuzzy Euler Approximation

    Directory of Open Access Journals (Sweden)

    Yangyang Hao

    2017-05-01

    Full Text Available Multi-dimensional Fuzzy differential equations driven by multi-dimen-sional Liu process, have been intensively applied in many fields. However, we can not obtain the analytic solution of every multi-dimensional fuzzy differential equation. Then, it is necessary for us to discuss the numerical results in most situations. This paper focuses on the numerical method of multi-dimensional fuzzy differential equations. The multi-dimensional fuzzy Taylor expansion is given, based on this expansion, a numerical method which is designed for giving the solution of multi-dimensional fuzzy differential equation via multi-dimensional Euler method will be presented, and its local convergence also will be discussed.

  20. Processing multilevel secure test and evaluation information

    Science.gov (United States)

    Hurlburt, George; Hildreth, Bradley; Acevedo, Teresa

    1994-07-01

    The Test and Evaluation Community Network (TECNET) is building a Multilevel Secure (MLS) system. This system features simultaneous access to classified and unclassified information and easy access through widely available communications channels. It provides the necessary separation of classification levels, assured through the use of trusted system design techniques, security assessments and evaluations. This system enables cleared T&E users to view and manipulate classified and unclassified information resources either using a single terminal interface or multiple windows in a graphical user interface. TECNET is in direct partnership with the National Security Agency (NSA) to develop and field the MLS TECNET capability in the near term. The centerpiece of this partnership is a state-of-the-art Concurrent Systems Security Engineering (CSSE) process. In developing the MLS TECNET capability, TECNET and NSA are providing members, with various expertise and diverse backgrounds, to participate in the CSSE process. The CSSE process is founded on the concepts of both Systems Engineering and Concurrent Engineering. Systems Engineering is an interdisciplinary approach to evolve and verify an integrated and life cycle balanced set of system product and process solutions that satisfy customer needs (ASD/ENS-MIL STD 499B 1992). Concurrent Engineering is design and development using the simultaneous, applied talents of a diverse group of people with the appropriate skills. Harnessing diverse talents to support CSSE requires active participation by team members in an environment that both respects and encourages diversity.