Voices: An Inclusive Choir in Dortmund, Germany
Directory of Open Access Journals (Sweden)
Irmgard Merkt
2012-01-01
Full Text Available The article describes the concept and work with an inclusive choir, in which students of the Faculty of Rehabilitation Sciences at TU Dortmund University sing together with adult mentally challengedpeople. The choir ‘Voices’ was founded in 2010, as a part of the project Dortmunder Modell: Musik (DOMO: Musik. The choir and project are committed to realising the United Nations’ Convention on the Rights of Persons with Disabilities, particularly in developing models of cultural participation, relevant both for people with and without disabilities. After describing the DOMO: Musik project and its principles, newly developed ideas for inclusive choir work are presented, together with imminent difficulties and positive results. Special attention is drawn to the selection of the pieces under the aspect of artistic variety. Five pieces of the artistic interdisciplinary repertoire are presented. Finally, the student choirmembers reflect on their experiences in the inclusive choir and make clear the importance of joint activities leading to an inclusive society.
Application of Interval Type-2 Fuzzy Logic System in Short Term Load Forecasting on Special Days
Directory of Open Access Journals (Sweden)
Agus Dharma
2011-05-01
Full Text Available This paper presents the application of Interval Type-2 fuzzy logic systems (Interval Type-2 FLS in short term load forecasting (STLF on special days, study case in Bali Indonesia. Type-2 FLS is characterized by a concept called footprint of uncertainty (FOU that provides the extra mathematical dimension that equips Type-2 FLS with the potential to outperform their Type-1 counterparts. While a Type-2 FLS has the capability to model more complex relationships, the output of a Type-2 fuzzy inference engine needs to be type-reduced. Type reduction is used by applying the Karnik-Mendel (KM iterative algorithm. This type reduction maps the output of Type-2 FSs into Type-1 FSs then the defuzzification with centroid method converts that Type-1 reduced FSs into a number. The proposed method was tested with the actual load data of special days using 4 days peak load before special days and at the time of special day for the year 2002-2006. There are 20 items of special days in Bali that are used to be forecasted in the year 2005 and 2006 respectively. The test results showed an accurate forecasting with the mean average percentage error of 1.0335% and 1.5683% in the year 2005 and 2006 respectively.
Gas load forecasting based on optimized fuzzy c-mean clustering analysis of selecting similar days
Directory of Open Access Journals (Sweden)
Qiu Jing
2017-08-01
Full Text Available Traditional fuzzy c-means (FCM clustering in short term load forecasting method is easy to fall into local optimum and is sensitive to the initial cluster center.In this paper,we propose to use global search feature of particle swarm optimization (PSO algorithm to avoid these shortcomings,and to use FCM optimization to select similar date of forecast as training sample of support vector machines.This will not only strengthen the data rule of training samples,but also ensure the consistency of data characteristics.Experimental results show that the prediction accuracy of this prediction model is better than that of BP neural network and support vector machine (SVM algorithms.
Fuzzy Boundary and Fuzzy Semiboundary
M. Athar; B. Ahmad
2008-01-01
We present several properties of fuzzy boundary and fuzzy semiboundary which have been supported by examples. Properties of fuzzy semi-interior, fuzzy semiclosure, fuzzy boundary, and fuzzy semiboundary have been obtained in product-related spaces. We give necessary conditions for fuzzy continuous (resp., fuzzy semicontinuous, fuzzy irresolute) functions. Moreover, fuzzy continuous (resp., fuzzy semicontinuous, fuzzy irresolute) functions have been characterized via fuzzy-derived (resp., fuzz...
Wittig, Roland
2002-01-01
Die vorliegende Arbeit befasst sich mit der Untersuchung der Gruppenbeitragsmethoden UNIFAC und Modified UNIFAC (Dortmund). Diese Modelle ermöglichen es, Phasengleichgewichte und Exzessgrößen vorherzusagen, auch wenn das betrachtete System bisher nicht experimentell untersucht wurde. Basis für die Anpassung der UNIFAC-Wechselwirkungsparameter sind experimentelle Daten. Da aber bei einigen Stoffklassen ein Mangel an experimentellen Gemischdaten herrscht, wurde im experimentellen Teil dieser Di...
Prediction of electrolyte vapor-liquid equilibrium by UNIFAC-Dortmund
Aznar, M.; Telles, A.S.
2001-01-01
The modified UNIFAC-Dortmund group contribution model is used for the correlation and prediction of salt effects in binary solvent-salt and ternary mixed solvent-salt systems. The long-range electrostatic interaction contribution, usually represented by a Debye-Hückel term, was empirically dropped. Previously published parameters for interactions between solvent groups (CH2, OH, CH3OH, H2O and CH3CO) were used, and group interactions between ions (Li+, Na+, K+, Ca+2, Cl-, Br-, NO3- and ACE-) ...
Improvements to the muon veto of the Dortmund Low Background Facility.
Nitsch, Christian; Gerhardt, Marcel; Gößling, Claus; Kröninger, Kevin
2017-08-01
The Dortmund Low Background Facility is a germanium gamma-ray spectrometry laboratory situated above ground. A massive artificial shielding, corresponding to 10m of water equivalent in combination with an active muon veto results in a background level comparable to laboratories situated underground. Due to the recent completion of the muon veto, the background is lowered by 20% compared to previously reported values (Gastrich et al., 2016). Additionally, Monte Carlo simulations of the cosmic muon induced components of the background spectrum are described. Copyright © 2017 Elsevier Ltd. All rights reserved.
Prediction of electrolyte vapor-liquid equilibrium by UNIFAC-Dortmund
Directory of Open Access Journals (Sweden)
M. Aznar
2001-06-01
Full Text Available The modified UNIFAC-Dortmund group contribution model is used for the correlation and prediction of salt effects in binary solvent-salt and ternary mixed solvent-salt systems. The long-range electrostatic interaction contribution, usually represented by a Debye-Hückel term, was empirically dropped. Previously published parameters for interactions between solvent groups (CH2, OH, CH3OH, H2O and CH3CO were used, and group interactions between ions (Li+, Na+, K+, Ca+2, Cl-, Br-, NO3- and ACE- and between ions and solvent groups have been estimated. The data base includes 29 binary and 56 ternary systems, used in part for the calculation of group interactions and in part for the testing of predictions.
'H-Bahn' - Dortmund demonstration system. Automatic vehicle protection system
Energy Technology Data Exchange (ETDEWEB)
Rosenkranz
1984-01-01
The automatic vehicle protection system of the H-Bahn at the Universtiy of Dortmund is responsible for fail-safe operating of the automatic vehicles. Its functions are protection of vehicle operation and protection of passengers boarding and leaving the vehicles. These functions are managed decentrally by two fail-safe operating controllers. Besides the well-known relay-techniques of railway-fail-safe systems, electronics are applied which are based on safe operating URTL-microcontrollers. These are controlled by software stored in EPROMs. A connection link using glass-fibres serves for safe data-exchange between the two fail-safe operating controllers. The experts' favourable reports on 'train protection and safety during passenger processing' were completed in March 84; thus, transportation of passengers could start in April 84.
Directory of Open Access Journals (Sweden)
Ping Jiang
2016-08-01
Full Text Available The day-ahead electricity market is closely related to other commodity markets such as the fuel and emission markets and is increasingly playing a significant role in human life. Thus, in the electricity markets, accurate electricity price forecasting plays significant role for power producers and consumers. Although many studies developing and proposing highly accurate forecasting models exist in the literature, there have been few investigations on improving the forecasting effectiveness of electricity price from the perspective of reducing the volatility of data with satisfactory accuracy. Based on reducing the volatility of the electricity price and the forecasting nature of the radial basis function network (RBFN, this paper successfully develops a two-stage model to forecast the day-ahead electricity price, of which the first stage is particle swarm optimization (PSO-core mapping (CM with self-organizing-map and fuzzy set (PCMwSF, and the second stage is selection rule (SR. The PCMwSF stage applies CM, fuzzy set and optimized weights to obtain the future price, and the SR stage is inspired by the forecasting nature of RBFN and effectively selects the best forecast during the test period. The proposed model, i.e., CM-PCMwSF-SR, not only overcomes the difficulty of reducing the high volatility of the electricity price but also leads to a superior forecasting effectiveness than benchmarks.
Noori, Roohollah; Safavi, Salman; Nateghi Shahrokni, Seyyed Afshin
2013-07-01
The five-day biochemical oxygen demand (BOD5) is one of the key parameters in water quality management. In this study, a novel approach, i.e., reduced-order adaptive neuro-fuzzy inference system (ROANFIS) model was developed for rapid estimation of BOD5. In addition, an uncertainty analysis of adaptive neuro-fuzzy inference system (ANFIS) and ROANFIS models was carried out based on Monte-Carlo simulation. Accuracy analysis of ANFIS and ROANFIS models based on both developed discrepancy ratio and threshold statistics revealed that the selected ROANFIS model was superior. Pearson correlation coefficient (R) and root mean square error for the best fitted ROANFIS model were 0.96 and 7.12, respectively. Furthermore, uncertainty analysis of the developed models indicated that the selected ROANFIS had less uncertainty than the ANFIS model and accurately forecasted BOD5 in the Sefidrood River Basin. Besides, the uncertainty analysis also showed that bracketed predictions by 95% confidence bound and d-factor in the testing steps for the selected ROANFIS model were 94% and 0.83, respectively.
Chapman, Neil; Stahl, Ola
2014-01-01
Contribution for a publication by Nico Dockx & Clara Meister entitled, 'A Poem A Day'.\\ud \\ud "When in 2012, Nico and I talked about utopias and the upcoming Utopia Station exhibition, our conversation quickly turned towards his poster A Poem a Day (2003). Very soon our verbal exchange turned into an idea, into a plan, into an open invitation to friends, asking them to respond to this idea of a poem for every day of the year. Open in the sense that poetry—especially in daily situations—an hap...
Directory of Open Access Journals (Sweden)
Sanping Rao
2013-01-01
Full Text Available This paper is an attempt to develop quantitative domain theory over frames. Firstly, we propose the notion of a fuzzy basis, and several equivalent characterizations of fuzzy bases are obtained. Furthermore, the concept of a fuzzy algebraic domain is introduced, and a relationship between fuzzy algebraic domains and fuzzy domains is discussed from the viewpoint of fuzzy basis. We finally give an application of fuzzy bases, where the image of a fuzzy domain can be preserved under some special kinds of fuzzy Galois connections.
Hartanto, Dhoni; Mustain, Asalil; Nugroho, Febry Dwi
2017-03-01
The vapor-liquid equilibria for eight systems of alcohols + glycerol at 101.325 kPa have been predicted in this study using UNIFAC and Modified UNIFAC (Dortmund) group contribution methods. The investigated alcohols were methanol, ethanol, 1-propanol, 2-propanol, 1-butanol, 2-butanol, 2-methyl-1-propanol and 2-methyl-2-propanol. In order to study the accuracy of both contribution methods, the predicted data obtained from both approaches were compared to the experimental data from the literature. The prediction accuracy using modified UNIFAC (Dortmund) give better results compared to the UNIFAC method for (ethanol, 1-propanol, 2-propanol and 1-butanol) + glycerol but UNIFAC method show better accuracy for methanol + glycerol system. In addition, the influences of carbon chain length on the phase behaviours of alcohol + glycerol systems were also discussed as well.
Fuzzy Set Field and Fuzzy Metric
Gebray, Gebru; Reddy, B. Krishna
2014-01-01
The notation of fuzzy set field is introduced. A fuzzy metric is redefined on fuzzy set field and on arbitrary fuzzy set in a field. The metric redefined is between fuzzy points and constitutes both fuzziness and crisp property of vector. In addition, a fuzzy magnitude of a fuzzy point in a field is defined.
The Only Way Is Up? Match Outcome And Stock Price Reactions Of Borussia Dortmund GmbH & Co. KGaA
DEFF Research Database (Denmark)
Stadtmann, Georg; Ruelke, Jan Christoph
2008-01-01
We use stock market data for Borussia Dortmund GmbH & Co. KGaA - one of the leading German football clubs - for an application of the news model. Due to the specific characteristics of the news generating process, the case of a publicly traded sport club is a very appropriate candidate for testing...... this model. By applying a traditional as well as a reversed news model we elaborate whether new information can explain subsequent changes in the stock price of Borussia Dortmund. We find that sport as well as corporate governance related variables are important drivers of the stock price....
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.
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.
Fuzzy Cores and Fuzzy Balancedness
van Gulick, G.; Norde, H.W.
2011-01-01
We study the relation between the fuzzy core and balancedness for fuzzy games. For regular games, this relation has been studied by Bondareva (1963) and Shapley (1967). First, we gain insight in this relation when we analyse situations where the fuzzy game is continuous. Our main result shows that
Intuitionistic fuzzy proximity spaces
Eun Pyo Lee; Seok Jong Lee
2004-01-01
We introduce the concept of the intuitionistic fuzzy proximity as a generalization of fuzzy proximity, and investigate its properties. Also we investigate the relationship among intuitionistic fuzzy proximity and fuzzy proximity, and intuitionistic fuzzy topology.
Relational Demonic Fuzzy Refinement
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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.
Fuzzy Riesz subspaces, fuzzy ideals, fuzzy bands and fuzzy band projections
Hong, Liang
2015-01-01
Fuzzy ordered linear spaces, Riesz spaces, fuzzy Archimedean spaces and $\\sigma$-complete fuzzy Riesz spaces were defined and studied in several works. Following the efforts along this line, we define fuzzy Riesz subspaces, fuzzy ideals, fuzzy bands and fuzzy band projections and establish their fundamental properties.
DEFF Research Database (Denmark)
Anker, Thomas Boysen; Kappel, Klemens; Eadie, Douglas
2012-01-01
This article clarifies the commonplace assumption that brands make promises by developing definitions of brand promise delivery. Distinguishing between clear and fuzzy brand promises, we develop definitions of what it is for a brand to deliver on fuzzy functional, symbolic, and experiential...
DEFF Research Database (Denmark)
Berks, G.; Keyserlingk, Diedrich Graf von; Jantzen, Jan
2000-01-01
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...
Fuzzy cores and fuzzy balancedness
van Gulick, G.; Norde, H.W.
2013-01-01
We study the relation between the fuzzy core and balancedness for fuzzy games. For regular games, this relation has been studied by Bondareva (Problemy Kibernet 10:119–139, 1963) and Shapley (Naval Res Logist Q 14: 453–460, 1967). First, we gain insight in this relation when we analyse situations
AL-Hawary, Talal Ali
2012-01-01
The aim of this paper is to discuss properties of fuzzy regular-flats, fuzzy C- flats, fuzzy alternative-sets and fuzzy i-flats. Moreover, we characterize some peculiar fuzzy matroids via these notions. Finally, we provide a decomposition of fuzzy strong maps.
Directory of Open Access Journals (Sweden)
Halis Aygün
2008-01-01
Full Text Available We introduce definitions of fuzzy inverse compactness, fuzzy inverse countable compactness, and fuzzy inverse Lindelöfness on arbitrary -fuzzy sets in -fuzzy topological spaces. We prove that the proposed definitions are good extensions of the corresponding concepts in ordinary topology and obtain different characterizations of fuzzy inverse compactness.
Onken, U.; Rarey-Nies, J.; Gmehling, J.
1989-05-01
The Dortmund Data Bank (DDB) was started in 1973 with the intention to employ the vast store of vapor-liquid equilibrium (VLE) data from the literature for the development of models for the prediction of VLE. From the beginning, the structure of the DDB has been organized in such a way that it was possible to take advantage of the full potential of electronic computers. With the experience gained in fitting and processing VLE data, we extended the DDB system to other types of mixture properties, i.e., liquid-liquid equilibria (LLE), gas solubilities (GLE), activity coefficients at infinite dilution γ∞, heats of mixing ( h E), and excess heat capacities. Besides the files for mixture properties, the DDB contains pure-component data and program packages for various applications. New experimental data are checked for consistency before they are stored. For data retrieval user-specified search masks can be used. The data files are available via an online data service and through the Dechema Chemistry Data Series. For the purpose of data correlation and model testing, parameter fitting is performed with an optimization routine (Nelder-Mead). In the past years the DDB system has been successfully employed for the development of prediction methods for VLE, LLE, GLE, γ∞, and h E (UNIFAC, mod. UNIFAC, etc.).
Nguyen, Hung T
2005-01-01
THE CONCEPT OF FUZZINESS Examples Mathematical modeling Some operations on fuzzy sets Fuzziness as uncertainty Exercises SOME ALGEBRA OF FUZZY SETS Boolean algebras and lattices Equivalence relations and partitions Composing mappings Isomorphisms and homomorphisms Alpha-cuts Images of alpha-level sets Exercises FUZZY QUANTITIES Fuzzy quantities Fuzzy numbers Fuzzy intervals Exercises LOGICAL ASPECTS OF FUZZY SETS Classical two-valued logic A three-valued logic Fuzzy logic Fuzzy and Lukasiewi
Intuitionistic fuzzy metric spaces
International Nuclear Information System (INIS)
Park, Jin Han
2004-01-01
Using the idea of intuitionistic fuzzy set due to Atanassov [Intuitionistic fuzzy sets. in: V. Sgurev (Ed.), VII ITKR's Session, Sofia June, 1983; Fuzzy Sets Syst. 20 (1986) 87], we define the notion of intuitionistic fuzzy metric spaces as a natural generalization of fuzzy metric spaces due to George and Veeramani [Fuzzy Sets Syst. 64 (1994) 395] and prove some known results of metric spaces including Baire's theorem and the Uniform limit theorem for intuitionistic fuzzy metric spaces
Energy Technology Data Exchange (ETDEWEB)
Mackey, Lester [Department of Statistics, Stanford University,Stanford, CA 94305 (United States); Nachman, Benjamin [Department of Physics, Stanford University,Stanford, CA 94305 (United States); SLAC National Accelerator Laboratory, Stanford University,2575 Sand Hill Rd, Menlo Park, CA 94025 (United States); Schwartzman, Ariel [SLAC National Accelerator Laboratory, Stanford University,2575 Sand Hill Rd, Menlo Park, CA 94025 (United States); Stansbury, Conrad [Department of Physics, Stanford University,Stanford, CA 94305 (United States)
2016-06-01
Collimated streams of particles produced in high energy physics experiments are organized using clustering algorithms to form jets. To construct jets, the experimental collaborations based at the Large Hadron Collider (LHC) primarily use agglomerative hierarchical clustering schemes known as sequential recombination. We propose a new class of algorithms for clustering jets that use infrared and collinear safe mixture models. These new algorithms, known as fuzzy jets, are clustered using maximum likelihood techniques and can dynamically determine various properties of jets like their size. We show that the fuzzy jet size adds additional information to conventional jet tagging variables in boosted topologies. Furthermore, we study the impact of pileup and show that with some slight modifications to the algorithm, fuzzy jets can be stable up to high pileup interaction multiplicities.
Intuitionistic Fuzzy Hyperhomomorphism and Intuitionistic Fuzzy Normal Subhypergroups
Abdulmula, Karema S; Salleh, Abdul Razak
2012-01-01
The purpose of this paper is to introduce some basic concepts of intuitionistic fuzzy hyperalgebra. We continue our study of intuitionistic fuzzy hypergroups, by generalising the concept of fuzzy homomorphism and fuzzy normal subgroup based on fuzzy spaces to intuitionistic fuzzy hyperhomomorphism based on intuitionstic fuzzy spaces. We will introduce the notion of an intuitionistic fuzzy quotient hypergroup induced by an intuitionistic fuzzy normal subhypergroup under intuitionistic fuzzy hy...
International Nuclear Information System (INIS)
Watanabe, K.
1990-01-01
Studies have been made on fuzzy diagnosis using inverse problem solutions of the fuzzy relational equation of ao R=b, where a is the failure vector, R the fuzzy relation matrix and b the sympton vector. Four phases of analyses were carried out in this study. First, fault tree analysis was undertaken to investigate what kind of causes produce fall of water level in a steam drum of ATR (Advanced Thermal Reactor), which is heavy-water-moderated boiling-water-cooled pressure-tube-type reactor. Next, simulation for 100 seconds was executed to determine how plant parameters respond to an occurrence of a transient induced by the cause. Third, the simulation data was analysed utilizing an autoregressive model. From this analysis, a total of 36 coherency functions up to 0.5 Hz in each transient were computed among nine important and detectable plant parameters, that is neutron flux, flow rate of coolant, steam and feed water, water level in the steam drum, pressure and opening area of control valve in a steam pipe, feed water temperature and electrical power. Last, the inverse problem of the fuzzy relational equation was solved. Relation matrices were adjusted from 0.00 to 1.00, after nine membership functions following the Gussian distribution for the symptom vector were estimated from correlation values of the coherency functions
Relational Demonic Fuzzy Refinement
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...
Intuitionistic Fuzzy Cycles and Intuitionistic Fuzzy Trees
Alshehri, N. O.
2014-01-01
Connectivity has an important role in neural networks, computer network, and clustering. In the design of a network, it is important to analyze connections by the levels. The structural properties of intuitionistic fuzzy graphs provide a tool that allows for the solution of operations research problems. In this paper, we introduce various types of intuitionistic fuzzy bridges, intuitionistic fuzzy cut vertices, intuitionistic fuzzy cycles, and intuitionistic fuzzy trees in intuitionistic fuzzy graphs and investigate some of their interesting properties. Most of these various types are defined in terms of levels. We also describe comparison of these types. PMID:24701155
Lenders, T; Kuster, J; Bispinck, R
2015-12-01
To develop an intervention concept for the management of uninhabitable homes. Retrospective analysis of 186 cases of the community mental health service in Dortmund (Germany) presenting with a destitute situation of the domestic environment as core problem. All patients suffered from psychiatric illnesses, mainly from addiction (F1: 41 %), psychosis (F2: 17 %), depression (F3: 17 %), and hoarding disorder (F63.8: 12 %). Main socio-demographic characteristics of our sample are: middle age (45-65 years, 48 %), male gender (73 %), isolated situation (only 7 % married, 84 % living alone), normal schooling (only 4 % without completion of schooling, 7 % attended a school for special needs), after initial integration into employment nearly all patients suffered vocational disintegration (5 % employed, 44 % unemployment benefit, 7 % welfare, 39 % pension or invalidity benefit).Psychosocial interventions differed between the 4 main diagnostic groups: F1: treatment of dependence (rehab) and treatment of concomitant somatic diseases; F2: admission to a psychiatric hospital and implementation of guardianship; F3: mediation of conflicts with neighbours/landlords and implementation of guardianship; F63.8: direct practical help by members of the community mental health team and organisation of home help/waste disposal. In all diagnostic groups, acceptance of help was impaired due to social withdrawal, resistance and psychiatric symptoms. At 13 %, compliance with help and interventions was lowest in the hoarder group (F1: 27 %, F2: 26 %, F3: 38 %). Consequently, in this group the poor outcome categories "nothing accomplished" and "lost flat/eviction" were more frequent (44 %, F1: 27 %, F2: 26 %, F3: 38 %). Concurrent to the deterioration of the domestic situation, patients suffer vocational disintegration as well as family and social isolation. Uninhabitable homes occur in the course of various severe and chronic psychiatric diseases
Alkouri, Abd Ulazeez M.; Salleh, Abdul Razak
2014-09-01
In this paper we combine two definitions, namely fuzzy soft multiset and complex fuzzy set to construct the definition of a complex fuzzy soft multiset and study its properties. In other words, we study the extension of a fuzzy soft multiset from real numbers to complex numbers. We also introduce its basic operations, namely complement, union and intersection. Some examples are given.
Some Additions to the Fuzzy Convergent and Fuzzy Bounded Sequence Spaces of Fuzzy Numbers
Şengönül, M.; Zararsız, Z.
2011-01-01
Some properties of the fuzzy convergence and fuzzy boundedness of a sequence of fuzzy numbers were studied in Choi (1996). In this paper, we have consider, some important problems on these spaces and shown that these spaces are fuzzy complete module spaces. Also, the fuzzy α-, fuzzy β-, and fuzzy γ-duals of the fuzzy module spaces of fuzzy numbers have been computeded, and some matrix transformations are given.
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
Directory of Open Access Journals (Sweden)
S. Nazmul
2014-03-01
Full Text Available Notions of Lowen type fuzzy soft topological space are introduced and some of their properties are established in the present paper. Besides this, a combined structure of a fuzzy soft topological space and a fuzzy soft group, which is termed here as fuzzy soft topological group is introduced. Homomorphic images and preimages are also examined. Finally, some definitions and results on fuzzy soft set are studied.
Coupland, Simon
2006-01-01
There has recently been a significant increase in academic interest in the field oftype-2 fuzzy sets and systems. Type-2 fuzzy systems offer the ability to model and reason with uncertain concepts. When faced with uncertainties type-2 fuzzy systems should, theoretically, give an increase in performance over type-l fuzzy systems. However, the computational complexity of generalised type-2 fuzzy systems is significantly higher than type-l systems. A direct consequence of this is that, prior to ...
Hierarchization process by possibilistic fuzzy clustering of fuzzy rules
Salgado, Paulo; Cunha, Manuela; Pavão, João; Igrejas, Getúlio
2010-01-01
This paper presents a possibilistic fuzzy clustering algorithm that is applied to a multidimensional fuzzy set or fuzzy rules. This method can be used to decompose the fuzzy system into an hierarchical structure. The methodology presented leads to a fuzzy partition of the fuzzy rules, one for each cluster, which corresponds to a new set of fuzzy sub-systems. This technique is tested to organize the fuzzy model into a new and more comprehensive structure.
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
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...
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...
International Nuclear Information System (INIS)
Abbas, S.E.
2004-01-01
In this paper, fuzzy SP-irresolute, fuzzy SP-irresolute open and fuzzy SP-irresolute closed functions between fuzzy topological spaces in Sostak sense are defined. Their properties and the relationships between these functions and other functions introduced previously are investigated. Next fuzzy SP-connectedness is introduced and studied with the help of r-fuzzy strongly preopen sets
Czech Academy of Sciences Publication Activity Database
Běhounek, Libor; Cintula, Petr
2005-01-01
Roč. 154, - (2005), s. 34-55 ISSN 0165-0114 R&D Projects: GA AV ČR IAA1030004; GA MŠk OC 274.001 Grant - others:COST(EU) Action 274 TARSKI Institutional research plan: CEZ:AV0Z10300504 Keywords : formal fuzzy logic * fuzzy set * foundations of fuzzy mathematics * LPi logic * higher-order fuzzy logic * fuzzy type theory * multi-sorted fuzzy logic Subject RIV: BA - General Mathematics Impact factor: 1.039, year: 2005
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
Construction of Fuzzy Ontologies from Fuzzy UML Models
Directory of Open Access Journals (Sweden)
Fu Zhang
2013-05-01
Full Text Available The success and proliferation of the Semantic Web depends heavily on construction of Web ontologies. However, classical ontology construction approaches are not sufficient for handling imprecise and uncertain information that is commonly found in many application domains. Therefore, great efforts on construction of fuzzy ontologies have been made in recent years. In this paper, we propose a formal approach and develop an automated tool for constructing fuzzy ontologies from fuzzy UML models. , we propose formalization methods of fuzzy UML models and fuzzy ontologies, where fuzzy UML models and fuzzy ontologies can be represented and interpreted by their respective formal definitions and semantic interpretation methods. , we propose an approach for constructing fuzzy ontologies from fuzzy UML models, i.e., transforming fuzzy UML models (including the structure and instance information of fuzzy UML models into fuzzy ontologies. , following the proposed approach, we implement a prototype transformation tool called that can construct fuzzy ontologies from fuzzy UML models. Constructing fuzzy ontologies from fuzzy UML models will facilitate the development of Web ontologies. , in order to show that the constructed fuzzy ontologies may be useful for reasoning on fuzzy UML models, we investigate how to reason on fuzzy UML models based on the constructed fuzzy ontologies, and it turns out that the reasoning tasks of fuzzy UML models can be checked by means of the reasoning mechanism of fuzzy ontologies.
Fuzzy Neuroidal Nets and Recurrent Fuzzy Computations
Czech Academy of Sciences Publication Activity Database
Wiedermann, Jiří
2001-01-01
Roč. 11, č. 6 (2001), s. 675-686 ISSN 1210-0552. [SOFSEM 2001 Workshop on Soft Computing. Piešťany, 29.11.2001-30.11.2001] R&D Projects: GA ČR GA201/00/1489; GA AV ČR KSK1019101 Institutional research plan: AV0Z1030915 Keywords : fuzzy computing * fuzzy neural nets * fuzzy Turing machines * non-uniform computational complexity Subject RIV: BA - General Mathematics
Arockiarani; J. Martina Jency
2017-01-01
The focus of this paper is to present the concept of fuzzy neutrosophic relations. Further we study the composition of fuzzy neutrosophic relations with the choice of t-norms and tconorms and characterize their properties.
Fuzzy logic controller optimization
Sepe, Jr., Raymond B; Miller, John Michael
2004-03-23
A method is provided for optimizing a rotating induction machine system fuzzy logic controller. The fuzzy logic controller has at least one input and at least one output. Each input accepts a machine system operating parameter. Each output produces at least one machine system control parameter. The fuzzy logic controller generates each output based on at least one input and on fuzzy logic decision parameters. Optimization begins by obtaining a set of data relating each control parameter to at least one operating parameter for each machine operating region. A model is constructed for each machine operating region based on the machine operating region data obtained. The fuzzy logic controller is simulated with at least one created model in a feedback loop from a fuzzy logic output to a fuzzy logic input. Fuzzy logic decision parameters are optimized based on the simulation.
Fuzzy Optimization of Option Pricing Model and Its Application in Land Expropriation
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Aimin Heng
2014-01-01
Full Text Available Option pricing is irreversible, fuzzy, and flexible. The fuzzy measure which is used for real option pricing is a useful supplement to the traditional real option pricing method. Based on the review of the concepts of the mean and variance of trapezoidal fuzzy number and the combination with the Carlsson-Fuller model, the trapezoidal fuzzy variable can be used to represent the current price of land expropriation and the sale price of land on the option day. Fuzzy Black-Scholes option pricing model can be constructed under fuzzy environment and problems also can be solved and discussed through numerical examples.
Czech Academy of Sciences Publication Activity Database
Mesiar, Radko
2005-01-01
Roč. 28, č. 156 (2005), s. 365-370 ISSN 0165-0114 R&D Projects: GA ČR(CZ) GA402/04/1026 Institutional research plan: CEZ:AV0Z10750506 Keywords : fuzzy measures * fuzzy integral * regular fuzzy integral Subject RIV: BA - General Mathematics Impact factor: 1.039, year: 2005
DEFF Research Database (Denmark)
Rodríguez, J. Tinguaro; Franco de los Ríos, Camilo; Gómez, Daniel
2015-01-01
In this paper we want to stress the relevance of paired fuzzy sets, as already proposed in previous works of the authors, as a family of fuzzy sets that offers a unifying view for different models based upon the opposition of two fuzzy sets, simply allowing the existence of different types...
Howard, Ayanna
2005-01-01
The Fuzzy Logic Engine is a software package that enables users to embed fuzzy-logic modules into their application programs. Fuzzy logic is useful as a means of formulating human expert knowledge and translating it into software to solve problems. Fuzzy logic provides flexibility for modeling relationships between input and output information and is distinguished by its robustness with respect to noise and variations in system parameters. In addition, linguistic fuzzy sets and conditional statements allow systems to make decisions based on imprecise and incomplete information. The user of the Fuzzy Logic Engine need not be an expert in fuzzy logic: it suffices to have a basic understanding of how linguistic rules can be applied to the user's problem. The Fuzzy Logic Engine is divided into two modules: (1) a graphical-interface software tool for creating linguistic fuzzy sets and conditional statements and (2) a fuzzy-logic software library for embedding fuzzy processing capability into current application programs. The graphical- interface tool was developed using the Tcl/Tk programming language. The fuzzy-logic software library was written in the C programming language.
Intuitionistic Fuzzy Subbialgebras and Duality
Directory of Open Access Journals (Sweden)
Wenjuan Chen
2014-01-01
Full Text Available We investigate connections between bialgebras and Atanassov’s intuitionistic fuzzy sets. Firstly we define an intuitionistic fuzzy subbialgebra of a bialgebra with an intuitionistic fuzzy subalgebra structure and also with an intuitionistic fuzzy subcoalgebra structure. Secondly we investigate the related properties of intuitionistic fuzzy subbialgebras. Finally we prove that the dual of an intuitionistic fuzzy strong subbialgebra is an intuitionistic fuzzy strong subbialgebra.
Some weakly mappings on intuitionistic fuzzy topological spaces
Zhen-Guo Xu; Fu-Gui Shi
2008-01-01
In this paper, we shall introduce concepts of fuzzy semiopen set, fuzzy semiclosed set, fuzzy semiinterior, fuzzy semiclosure on intuitionistic fuzzy topological space and fuzzy open (fuzzy closed) mapping, fuzzy irresolute mapping, fuzzy irresolute open (closed) mapping, fuzzy semicontinuous mapping and fuzzy semiopen (semiclosed) mapping between two intuitionistic fuzzy topological spaces. Moreover, we shall discuss their some properties.
Optimality Conditions for Fuzzy Number Quadratic Programming with Fuzzy Coefficients
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Xue-Gang Zhou
2014-01-01
Full Text Available The purpose of the present paper is to investigate optimality conditions and duality theory in fuzzy number quadratic programming (FNQP in which the objective function is fuzzy quadratic function with fuzzy number coefficients and the constraint set is fuzzy linear functions with fuzzy number coefficients. Firstly, the equivalent quadratic programming of FNQP is presented by utilizing a linear ranking function and the dual of fuzzy number quadratic programming primal problems is introduced. Secondly, we present optimality conditions for fuzzy number quadratic programming. We then prove several duality results for fuzzy number quadratic programming problems with fuzzy coefficients.
Countable Fuzzy Topological Space and Countable Fuzzy Topological Vector Space
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Apu Kumar Saha
2015-06-01
Full Text Available This paper deals with countable fuzzy topological spaces, a generalization of the notion of fuzzy topological spaces. A collection of fuzzy sets F on a universe X forms a countable fuzzy topology if in the definition of a fuzzy topology, the condition of arbitrary supremum is relaxed to countable supremum. In this generalized fuzzy structure, the continuity of fuzzy functions and some other related properties are studied. Also the class of countable fuzzy topological vector spaces as a generalization of the class of fuzzy topological vector spaces has been introduced and investigated.
Mathematics of Fuzzy Sets and Fuzzy Logic
Bede, Barnabas
2013-01-01
This book presents a mathematically-based introduction into the fascinating topic of Fuzzy Sets and Fuzzy Logic and might be used as textbook at both undergraduate and graduate levels and also as reference guide for mathematician, scientists or engineers who would like to get an insight into Fuzzy Logic. Fuzzy Sets have been introduced by Lotfi Zadeh in 1965 and since then, they have been used in many applications. As a consequence, there is a vast literature on the practical applications of fuzzy sets, while theory has a more modest coverage. The main purpose of the present book is to reduce this gap by providing a theoretical introduction into Fuzzy Sets based on Mathematical Analysis and Approximation Theory. Well-known applications, as for example fuzzy control, are also discussed in this book and placed on new ground, a theoretical foundation. Moreover, a few advanced chapters and several new results are included. These comprise, among others, a new systematic and constructive approach for fuzzy infer...
On generalized fuzzy strongly semiclosed sets in fuzzy topological spaces
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Oya Bedre Ozbakir
2002-01-01
semiclosed, generalized fuzzy almost-strongly semiclosed, generalized fuzzy strongly closed, and generalized fuzzy almost-strongly closed sets. In the light of these definitions, we also define some generalizations of fuzzy continuous functions and discuss the relations between these new classes of functions and other fuzzy continuous functions.
How we pass from fuzzy $po$-semigroups to fuzzy $po$-$\\Gamma$-semigroups
Kehayopulu, Niovi
2014-01-01
The results on fuzzy ordered semigroups (or on fuzzy semigroups) can be transferred to fuzzy ordered gamma (or to fuzzy gamma) semigroups. We show the way we pass from fuzzy ordered semigroups to fuzzy ordered gamma semigroups.
Recurrent fuzzy ranking methods
Hajjari, Tayebeh
2012-11-01
With the increasing development of fuzzy set theory in various scientific fields and the need to compare fuzzy numbers in different areas. Therefore, Ranking of fuzzy numbers plays a very important role in linguistic decision-making, engineering, business and some other fuzzy application systems. Several strategies have been proposed for ranking of fuzzy numbers. Each of these techniques has been shown to produce non-intuitive results in certain case. In this paper, we reviewed some recent ranking methods, which will be useful for the researchers who are interested in this area.
Myravyova, E. A.; Sharipov, M. I.; Radakina, D. S.
2017-10-01
During writing this work, the fuzzy controller with a double base of rules was studied, which was applied for the synthesis of the automated control system. A method for fuzzy controller adaptation has been developed. The adaptation allows the fuzzy controller to automatically compensate for parametric interferences that occur at the control object. Specifically, the fuzzy controller controlled the outlet steam temperature in the boiler unit BKZ-75-39 GMA. The software code was written in the programming support environment Unity Pro XL designed for fuzzy controller adaptation.
B Gibilisco, Michael; E Albert, Karen; N Mordeson, John; J Wierman, Mark; D Clark, Terry
2014-01-01
This book offers a comprehensive analysis of the social choice literature and shows, by applying fuzzy sets, how the use of fuzzy preferences, rather than that of strict ones, may affect the social choice theorems. To do this, the book explores the presupposition of rationality within the fuzzy framework and shows that the two conditions for rationality, completeness and transitivity, do exist with fuzzy preferences. Specifically, this book examines: the conditions under which a maximal set exists; the Arrow’s theorem; the Gibbard-Satterthwaite theorem; and the median voter theorem. After showing that a non-empty maximal set does exists for fuzzy preference relations, this book goes on to demonstrating the existence of a fuzzy aggregation rule satisfying all five Arrowian conditions, including non-dictatorship. While the Gibbard-Satterthwaite theorem only considers individual fuzzy preferences, this work shows that both individuals and groups can choose alternatives to various degrees, resulting in a so...
Special functions in Fuzzy Analysis
Angel Garrido
2006-01-01
In the treatment of Fuzzy Logic an useful tool appears: the membership function, with the information about the degree of completion of a condition which defines the respective Fuzzy Set or Fuzzy Relation. With their introduction, it is possible to prove some results on the foundations of Fuzzy Logic and open new ways in Fuzzy Analysis.
Special functions in Fuzzy Analysis
Directory of Open Access Journals (Sweden)
Angel Garrido
2006-01-01
Full Text Available In the treatment of Fuzzy Logic an useful tool appears: the membership function, with the information about the degree of completion of a condition which defines the respective Fuzzy Set or Fuzzy Relation. With their introduction, it is possible to prove some results on the foundations of Fuzzy Logic and open new ways in Fuzzy Analysis.
Approximate Reasoning with Fuzzy Booleans
van den Broek, P.M.; Noppen, J.A.R.
This paper introduces, in analogy to the concept of fuzzy numbers, the concept of fuzzy booleans, and examines approximate reasoning with the compositional rule of inference using fuzzy booleans. It is shown that each set of fuzzy rules is equivalent to a set of fuzzy rules with singleton crisp
On fuzzy almost continuous convergence in fuzzy function spaces
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A.I. Aggour
2013-10-01
Full Text Available In this paper, we study the fuzzy almost continuous convergence of fuzzy nets on the set FAC(X, Y of all fuzzy almost continuous functions of a fuzzy topological space X into another Y. Also, we introduce the notions of fuzzy splitting and fuzzy jointly continuous topologies on the set FAC(X, Y and study some of its basic properties.
A NOTE ON FUZZY CLOSURE OF A FUZZY SET
Directory of Open Access Journals (Sweden)
Bhimraj Basumatary
2015-10-01
Full Text Available In this article fuzzy closure has been discussed with the help of extended definition of fuzzy set on the assumption that the union of a fuzzy set and its complement is universal set and intersection of a fuzzy set and its complement is empty set. Also we have discussed some proposition of fuzzy closure with the help of numerical example on the basis of extended definition of fuzzy set.
Fuzzy soft connected sets in fuzzy soft topological spaces II
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A. Kandil
2017-04-01
Full Text Available In this paper, we introduce some different types of fuzzy soft connected components related to the different types of fuzzy soft connectedness and based on an equivalence relation defined on the set of fuzzy soft points of X. We have investigated some very interesting properties for fuzzy soft connected components. We show that the fuzzy soft C5-connected component may be not exists and if it exists, it may not be fuzzy soft closed set. Also, we introduced some very interesting properties for fuzzy soft connected components in discrete fuzzy soft topological spaces which is a departure from the general topology.
Probabilistic fuzzy clustering algorithm for fuzzy rules decomposition
Salgado, Paulo; Igrejas, Getúlio
2007-01-01
The Fuzzy C-Means (FCM) clustering algorithm is the best known and the most used method for fuzzy clustering and is generally applied to well defined sets of data. In this work a generalized Probabilistic Fuzzy C-Means (PFCM) algorithm is proposed and applied to fuzzy sets clustering. The methodology presented leads to a fuzzy partition of the fuzzy rules, one for each cluster, which corresponds to a new set of fuzzy sub-systems. When applied to the clustering of a flat fuzzy system the resul...
Flacke, Johannes; Schüle, Steffen Andreas; Köckler, Heike; Bolte, Gabriele
2016-01-01
Spatial differences in urban environmental conditions contribute to health inequalities within cities. The purpose of the paper is to map environmental inequalities relevant for health in the City of Dortmund, Germany, in order to identify needs for planning interventions. We develop suitable indicators for mapping socioeconomically-driven environmental inequalities at the neighborhood level based on published scientific evidence and inputs from local stakeholders. Relationships between socioeconomic and environmental indicators at the level of 170 neighborhoods were analyzed continuously with Spearman rank correlation coefficients and categorically applying chi-squared tests. Reclassified socioeconomic and environmental indicators were then mapped at the neighborhood level in order to determine multiple environmental burdens and hotspots of environmental inequalities related to health. Results show that the majority of environmental indicators correlate significantly, leading to multiple environmental burdens in specific neighborhoods. Some of these neighborhoods also have significantly larger proportions of inhabitants of a lower socioeconomic position indicating hotspots of environmental inequalities. Suitable planning interventions mainly comprise transport planning and green space management. In the conclusions, we discuss how the analysis can be used to improve state of the art planning instruments, such as clean air action planning or noise reduction planning towards the consideration of the vulnerability of the population. PMID:27420090
Flacke, Johannes; Schüle, Steffen Andreas; Köckler, Heike; Bolte, Gabriele
2016-07-13
Spatial differences in urban environmental conditions contribute to health inequalities within cities. The purpose of the paper is to map environmental inequalities relevant for health in the City of Dortmund, Germany, in order to identify needs for planning interventions. We develop suitable indicators for mapping socioeconomically-driven environmental inequalities at the neighborhood level based on published scientific evidence and inputs from local stakeholders. Relationships between socioeconomic and environmental indicators at the level of 170 neighborhoods were analyzed continuously with Spearman rank correlation coefficients and categorically applying chi-squared tests. Reclassified socioeconomic and environmental indicators were then mapped at the neighborhood level in order to determine multiple environmental burdens and hotspots of environmental inequalities related to health. Results show that the majority of environmental indicators correlate significantly, leading to multiple environmental burdens in specific neighborhoods. Some of these neighborhoods also have significantly larger proportions of inhabitants of a lower socioeconomic position indicating hotspots of environmental inequalities. Suitable planning interventions mainly comprise transport planning and green space management. In the conclusions, we discuss how the analysis can be used to improve state of the art planning instruments, such as clean air action planning or noise reduction planning towards the consideration of the vulnerability of the population.
Introduction to Fuzzy Set Theory
Kosko, Bart
1990-01-01
An introduction to fuzzy set theory is described. Topics covered include: neural networks and fuzzy systems; the dynamical systems approach to machine intelligence; intelligent behavior as adaptive model-free estimation; fuzziness versus probability; fuzzy sets; the entropy-subsethood theorem; adaptive fuzzy systems for backing up a truck-and-trailer; product-space clustering with differential competitive learning; and adaptive fuzzy system for target tracking.
Decomposition of fuzzy continuity and fuzzy ideal continuity via fuzzy idealization
International Nuclear Information System (INIS)
Zahran, A.M.; Abbas, S.E.; Abd El-baki, S.A.; Saber, Y.M.
2009-01-01
Recently, El-Naschie has shown that the notion of fuzzy topology may be relevant to quantum paretical physics in connection with string theory and E-infinity space time theory. In this paper, we study the concepts of r-fuzzy semi-I-open, r-fuzzy pre-I-open, r-fuzzy α-I-open and r-fuzzy β-I-open sets, which is properly placed between r-fuzzy openness and r-fuzzy α-I-openness (r-fuzzy pre-I-openness) sets regardless the fuzzy ideal topological space in Sostak sense. Moreover, we give a decomposition of fuzzy continuity, fuzzy ideal continuity and fuzzy ideal α-continuity, and obtain several characterization and some properties of these functions. Also, we investigate their relationship with other types of function.
FUZZY RINGS AND ITS PROPERTIES
Directory of Open Access Journals (Sweden)
Karyati Karyati
2017-01-01
One of algebraic structure that involves a binary operation is a group that is defined an un empty set (classical with an associative binary operation, it has identity elements and each element has an inverse. In the structure of the group known as the term subgroup, normal subgroup, subgroup and factor group homomorphism and its properties. Classical algebraic structure is developed to algebraic structure fuzzy by the researchers as an example semi group fuzzy and fuzzy group after fuzzy sets is introduced by L. A. Zadeh at 1965. It is inspired of writing about semi group fuzzy and group of fuzzy, a research on the algebraic structure of the ring is held with reviewing ring fuzzy, ideal ring fuzzy, homomorphism ring fuzzy and quotient ring fuzzy with its properties. The results of this study are obtained fuzzy properties of the ring, ring ideal properties fuzzy, properties of fuzzy ring homomorphism and properties of fuzzy quotient ring by utilizing a subset of a subset level and strong level as well as image and pre-image homomorphism fuzzy ring. Keywords: fuzzy ring, subset level, homomorphism fuzzy ring, fuzzy quotient ring
ON SOME DECOMPOSITIONS OF FUZZY SOFT CONTINUITY
Gain, Pradip Kumar; Mukherjee, Prakash; Chakraborty, Ramkrishna Prasad
2015-01-01
– In this article, some open-like fuzzy soft sets such as fuzzy soft semi-open set, fuzzy soft preopen set, fuzzy soft α-open set and corresponding variants of fuzzy soft continuous functions are introduced and discussed. Some other variants of fuzzy soft sets such as fuzzy soft semi-preclosed set, fuzzy soft t-set, fuzzy soft α*-set, fuzzy soft regular open set, fuzzy soft B-set, fuzzy soft C-set and fuzzy soft D(α)-set are defined and some properties of these sets are studied and investigat...
DEFF Research Database (Denmark)
Jantzen, Jan
The objective of this textbook is to acquire an understanding of the behaviour of fuzzy logic controllers. Under certain conditions a fuzzy controller is equivalent to a proportional-integral-derivative (PID) controller. Using that equivalence as a link, the book applies analysis methods from...... linear and nonlinear control theory. In the linear domain, PID tuning methods and stability analyses are transferred to linear fuzzy controllers. The Nyquist plot shows the robustness of different settings of the fuzzy gain parameters. As a result, a fuzzy controller is guaranteed to perform as well...... as any PID controller. In the nonlinear domain, the stability of four standard control surfaces is analysed by means of describing functions and Nyquist plots. The self-organizing controller (SOC) is shown to be a model reference adaptive controller. There is a possibility that a nonlinear fuzzy PID...
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.
Disjointness of Fuzzy Coalitions
Czech Academy of Sciences Publication Activity Database
Mareš, Milan; Vlach, M.
2008-01-01
Roč. 44, č. 3 (2008), s. 416-429 ISSN 0023-5954 R&D Projects: GA AV ČR IAA1075301; GA ČR GA402/04/1026; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : Fuzzy coalitionla game * Disjointness of fuzzy sets * Fuzzy coalition Subject RIV: BD - Theory of Information Impact factor: 0.281, year: 2008
Berenji, Hamid R.
1992-01-01
Fuzzy logic and neural networks provide new methods for designing control systems. Fuzzy logic controllers do not require a complete analytical model of a dynamic system and can provide knowledge-based heuristic controllers for ill-defined and complex systems. Neural networks can be used for learning control. In this chapter, we discuss hybrid methods using fuzzy logic and neural networks which can start with an approximate control knowledge base and refine it through reinforcement learning.
Metamathematics of fuzzy logic
Hájek, Petr
1998-01-01
This book presents a systematic treatment of deductive aspects and structures of fuzzy logic understood as many valued logic sui generis. Some important systems of real-valued propositional and predicate calculus are defined and investigated. The aim is to show that fuzzy logic as a logic of imprecise (vague) propositions does have well-developed formal foundations and that most things usually named `fuzzy inference' can be naturally understood as logical deduction.
DEFF Research Database (Denmark)
Dotoli, M.; Jantzen, Jan
1999-01-01
The tutorial concerns automatic control of an inverted pendulum, especially rule based control by means of fuzzy logic. A ball balancer, implemented in a software simulator in Matlab, is used as a practical case study. The objectives of the tutorial are to teach the basics of fuzzy control......, and to show how to apply fuzzy logic in automatic control. The tutorial is distance learning, where students interact one-to-one with the teacher using e-mail....
Fuzzy control and identification
Lilly, John H
2010-01-01
This book gives an introduction to basic fuzzy logic and Mamdani and Takagi-Sugeno fuzzy systems. The text shows how these can be used to control complex nonlinear engineering systems, while also also suggesting several approaches to modeling of complex engineering systems with unknown models. Finally, fuzzy modeling and control methods are combined in the book, to create adaptive fuzzy controllers, ending with an example of an obstacle-avoidance controller for an autonomous vehicle using modus ponendo tollens logic.
T Atanassov, Krassimir
2017-01-01
The book offers a comprehensive survey of intuitionistic fuzzy logics. By reporting on both the author’s research and others’ findings, it provides readers with a complete overview of the field and highlights key issues and open problems, thus suggesting new research directions. Starting with an introduction to the basic elements of intuitionistic fuzzy propositional calculus, it then provides a guide to the use of intuitionistic fuzzy operators and quantifiers, and lastly presents state-of-the-art applications of intuitionistic fuzzy sets. The book is a valuable reference resource for graduate students and researchers alike.
Advances in fuzzy implication functions
Beliakov, Gleb; Sola, Humberto; Pradera, Ana
2013-01-01
Fuzzy implication functions are one of the main operations in fuzzy logic. They generalize the classical implication, which takes values in the set {0,1}, to fuzzy logic, where the truth values belong to the unit interval [0,1]. These functions are not only fundamental for fuzzy logic systems, fuzzy control, approximate reasoning and expert systems, but they also play a significant role in mathematical fuzzy logic, in fuzzy mathematical morphology and image processing, in defining fuzzy subsethood measures and in solving fuzzy relational equations. This volume collects 8 research papers on fuzzy implication functions. Three articles focus on the construction methods, on different ways of generating new classes and on the common properties of implications and their dependencies. Two articles discuss implications defined on lattices, in particular implication functions in interval-valued fuzzy set theories. One paper summarizes the sufficient and necessary conditions of solutions for one distributivity equation...
Some Properties of Fuzzy Soft Proximity Spaces
Demir, İzzettin; Özbakır, Oya Bedre
2015-01-01
We study the fuzzy soft proximity spaces in Katsaras's sense. First, we show how a fuzzy soft topology is derived from a fuzzy soft proximity. Also, we define the notion of fuzzy soft δ-neighborhood in the fuzzy soft proximity space which offers an alternative approach to the study of fuzzy soft proximity spaces. Later, we obtain the initial fuzzy soft proximity determined by a family of fuzzy soft proximities. Finally, we investigate relationship between fuzzy soft proximities and proximities. PMID:25793224
On Intuitionistic Fuzzy Filters of Intuitionistic Fuzzy Coframes
Directory of Open Access Journals (Sweden)
Rajesh K. Thumbakara
2013-01-01
Full Text Available Frame theory is the study of topology based on its open set lattice, and it was studied extensively by various authors. In this paper, we study quotients of intuitionistic fuzzy filters of an intuitionistic fuzzy coframe. The quotients of intuitionistic fuzzy filters are shown to be filters of the given intuitionistic fuzzy coframe. It is shown that the collection of all intuitionistic fuzzy filters of a coframe and the collection of all intutionistic fuzzy quotient filters of an intuitionistic fuzzy filter are coframes.
Properties of Bipolar Fuzzy Hypergraphs
Akram, M.; Dudek, W. A.; Sarwar, S.
2013-01-01
In this article, we apply the concept of bipolar fuzzy sets to hypergraphs and investigate some properties of bipolar fuzzy hypergraphs. We introduce the notion of $A-$ tempered bipolar fuzzy hypergraphs and present some of their properties. We also present application examples of bipolar fuzzy hypergraphs.
Directory of Open Access Journals (Sweden)
Radko Mesiar
2017-11-01
Full Text Available A revised definition for fuzzy bags is reviewed, developing the concept of bags given by Delgado et al. 2009 from which each bag has two parts, function and summary information. Then, the definitions of fuzzy bag expected value, bag entropy and bag similarity are introduced. By some examples, the new concepts are illustrated.
Extended Fuzzy Clustering Algorithms
U. Kaymak (Uzay); M. Setnes
2000-01-01
textabstractFuzzy clustering is a widely applied method for obtaining fuzzy models from data. It has been applied successfully in various fields including finance and marketing. Despite the successful applications, there are a number of issues that must be dealt with in practical applications of
Clustering by fuzzy neural gas and evaluation of fuzzy clusters.
Geweniger, Tina; Fischer, Lydia; Kaden, Marika; Lange, Mandy; Villmann, Thomas
2013-01-01
We consider some modifications of the neural gas algorithm. First, fuzzy assignments as known from fuzzy c-means and neighborhood cooperativeness as known from self-organizing maps and neural gas are combined to obtain a basic Fuzzy Neural Gas. Further, a kernel variant and a simulated annealing approach are derived. Finally, we introduce a fuzzy extension of the ConnIndex to obtain an evaluation measure for clusterings based on fuzzy vector quantization.
Clustering by Fuzzy Neural Gas and Evaluation of Fuzzy Clusters
Geweniger, Tina; Fischer, Lydia; Kaden, Marika; Lange, Mandy; Villmann, Thomas
2013-01-01
We consider some modifications of the neural gas algorithm. First, fuzzy assignments as known from fuzzy c-means and neighborhood cooperativeness as known from self-organizing maps and neural gas are combined to obtain a basic Fuzzy Neural Gas. Further, a kernel variant and a simulated annealing approach are derived. Finally, we introduce a fuzzy extension of the ConnIndex to obtain an evaluation measure for clusterings based on fuzzy vector quantization.
Statistical Methods for Fuzzy Data
Viertl, Reinhard
2011-01-01
Statistical data are not always precise numbers, or vectors, or categories. Real data are frequently what is called fuzzy. Examples where this fuzziness is obvious are quality of life data, environmental, biological, medical, sociological and economics data. Also the results of measurements can be best described by using fuzzy numbers and fuzzy vectors respectively. Statistical analysis methods have to be adapted for the analysis of fuzzy data. In this book, the foundations of the description of fuzzy data are explained, including methods on how to obtain the characterizing function of fuzzy m
Directory of Open Access Journals (Sweden)
Zoltan Erdei
2011-12-01
Full Text Available In this paper the authors present the usefulness of fuzzy logic in controlling engineering processes or applications. Although fuzzy logic does not represent a novelty for the scientific and engineering field, it enjoys a great appreciation from those involved in the two domains. The fact that fuzzy logic uses sentences kindred with the natural language make it easier to comprehend that a complex mathematical model required by the classic control theory. In MatLab software there are dedicated toolboxes to this subject that make the design of a fuzzy controller a facile one. In the paper design methods of a fuzzy controller are being presented both in Simulink and MatLab.
DEFF Research Database (Denmark)
Jantzen, Jan
1998-01-01
Design of a fuzzy controller requires more design decisions than usual, for example regarding rule base, inference engine, defuzzification, and data pre- and post processing. This tutorial paper identifies and describes the design choices related to single-loop fuzzy control, based on an internat...... on an international standard which is underway. The paper contains also a design approach, which uses a PID controller as a starting point. A design engineer can view the paper as an introduction to fuzzy controller design.......Design of a fuzzy controller requires more design decisions than usual, for example regarding rule base, inference engine, defuzzification, and data pre- and post processing. This tutorial paper identifies and describes the design choices related to single-loop fuzzy control, based...
Coordinated signal control for arterial intersections using fuzzy logic
Kermanian, Davood; Zare, Assef; Balochian, Saeed
2013-09-01
Every day growth of the vehicles has become one of the biggest problems of urbanism especially in major cities. This can waste people's time, increase the fuel consumption, air pollution, and increase the density of cars and vehicles. Fuzzy controllers have been widely used in many consumer products and industrial applications with success over the past two decades. This article proposes a comprehensive model of urban traffic network using state space equations and then using Fuzzy Logic Tool Box and SIMULINK Program MATLAB a fuzzy controller in order to optimize and coordinate signal control at two intersections at an arterial road. The fuzzy controller decides to extend, early cut or terminate a signal phase and phase sequence to ensure smooth flow of traffic with minimal waiting time and length of queue. Results show that the performance of the proposed traffic controller at novel fuzzy model is better that of conventional controllers under normal and abnormal traffic conditions.
COMPARISON OF MAMDANI & SUGENO TYPE FUZZY INFERENCE SYSTEM ON ENROLLMENT DATASETS
Mr. Vinay Barod, Ms. Shalini Modi, Ms.Yamini Bhavsar, Ms.Preetika Saxena y
2016-01-01
As the Application of Computer is increasing day by day. Computers are also used in the field of Business Analysis and Forecasting. There is various approaches in the field of forecasting. Fuzzy logic is the branch of Soft Computing that is widely used in the field of forecasting. Fuzzy Inference System is used to map inputs to outputs. In this Paper both the Mamdani and Sugeno model of Fuzzy Inference System are compared based on Performance and Error Rate.
Hesitant intuitionistic fuzzy soft sets
Nazra, Admi; Syafruddin; Lestari, Riri; Catur Wicaksono, Gandung
2017-09-01
This paper aims to extend the hesitant fuzzy soft sets to hesitant intuitionistic fuzzy soft sets by merging the concept of hesitant intuitionistic fuzzy sets and soft sets. The authors define some operations on hesitant intuitionistic fuzzy sets, such as complement, union and intersection, and obtain related properties. The similar operations are defined on hesitant intuitionistic fuzzy soft sets, and also some properties such as assosiative and De Morgan’s laws are obtained.
Construction of fuzzy automata by fuzzy experiments
International Nuclear Information System (INIS)
Mironov, A.
1994-01-01
The solving the problem of canonical realization of partial reaction morphisms (PRM) for automata in toposes and fuzzy automata is addressed. This problem extends the optimal construction problem for finite deterministic automata by experiments. In the present paper the conception of canonical realization of PRM for automata in toposes is introduced and the sufficient conditions for the existence of canonical realizations for PRM in toposes are presented. As a consequence of this result the existence of canonical realizations for PRM in the category of fuzzy sets over arbitrary complete chain is proven
Approximations of Fuzzy Systems
Directory of Open Access Journals (Sweden)
Vinai K. Singh
2013-03-01
Full Text Available A fuzzy system can uniformly approximate any real continuous function on a compact domain to any degree of accuracy. Such results can be viewed as an existence of optimal fuzzy systems. Li-Xin Wang discussed a similar problem using Gaussian membership function and Stone-Weierstrass Theorem. He established that fuzzy systems, with product inference, centroid defuzzification and Gaussian functions are capable of approximating any real continuous function on a compact set to arbitrary accuracy. In this paper we study a similar approximation problem by using exponential membership functions
Some Results on Fuzzy Soft Topological Spaces
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Cigdem Gunduz (Aras
2013-01-01
Full Text Available We introduce some important properties of fuzzy soft topological spaces. Furthermore, fuzzy soft continuous mapping, fuzzy soft open and fuzzy soft closed mappings, and fuzzy soft homeomorphism for fuzzy soft topological spaces are given and structural characteristics are discussed and studied.
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.
Malhas, Othman Qasim
1993-10-01
The concept of “abacus logic” has recently been developed by the author (Malhas, n.d.). In this paper the relation of abacus logic to the concept of fuzziness is explored. It is shown that if a certain “regularity” condition is met, concepts from fuzzy set theory arise naturally within abacus logics. In particular it is shown that every abacus logic then has a “pre-Zadeh orthocomplementation”. It is also shown that it is then possible to associate a fuzzy set with every proposition of abacus logic and that the collection of all such sets satisfies natural conditions expected in systems of fuzzy logic. Finally, the relevance to quantum mechanics is discussed.
Fuzzy stochastic multiobjective programming
Sakawa, Masatoshi; Katagiri, Hideki
2011-01-01
With a stress on interactive decision-making, this work breaks new ground by covering both the random nature of events related to environments, and the fuzziness of human judgements. The text runs from mathematical preliminaries to future research directions.
International Nuclear Information System (INIS)
Lee Chenjai.
1993-01-01
Air pollution, land price development and assessment of immission control needs in urban development plans. The impact of immission pollution by sulphur dioxide and dust precipitation on property prices in residential areas of Dortmund and Duisburg. The focus of this thesis is on studying the links between property prices and air pollution. The ground rent theory which goes back to the 16th century provides the theoretical basis for this work. RICARDO put forward the theory, that air may, under certain circumstances, - as for instance different local air pollution levels or sensitivity of locals to air quality -, which did not apply 200 years ago actually produce rent. These circumstances do indeed apply widely today - different air pollution levels in urban areas are just a case in point. Various empiricial studies in the U.S. proved that air pollution with different substances does actually influence the value of property. The ground rent influenced by air pollution is called ''air rent''. This study contains empirical studies on the influence of air pollution by sulphur dioxide SO 2 and dust precipitation on general property prices in residential areas of Dortmund between 1979 and 1989 and Duisburg between 1981 and 1989. (orig./UA) [de
Fuzzy Logic and Neuro-fuzzy Systems: A Systematic Introduction
Yue Wu; Biaobiao Zhang; Jiabin Lu; K. -L. Du
2011-01-01
Fuzzy logic is a rigorous mathematical field, and it provides an effective vehicle for modeling the uncertainty in human reasoning. In fuzzy logic, the knowledge of experts is modeled by linguistic rules represented in the form of IF-THEN logic. Like neural network models such as the multilayer perceptron (MLP) and the radial basis function network (RBFN), some fuzzy inference systems (FISs) have the capability of universal approximation. Fuzzy logic can be used in most areas where neural net...
Fuzzy variable linear programming with fuzzy technical coefficients
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Sanwar Uddin Ahmad
2012-11-01
Full Text Available Normal 0 false false false EN-US X-NONE X-NONE Fuzzy linear programming is an application of fuzzy set theory in linear decision making problems and most of these problems are related to linear programming with fuzzy variables. In this paper an approximate but convenient method for solving these problems with fuzzy non-negative technical coefficient and without using the ranking functions, is proposed. With the help of numerical examples, the method is illustrated.
From Fuzzy Logic to Fuzzy Mathematics: A Methodological Manifesto
Czech Academy of Sciences Publication Activity Database
Běhounek, Libor; Cintula, Petr
2006-01-01
Roč. 157, č. 5 (2006), s. 642-646 ISSN 0165-0114 R&D Projects: GA AV ČR KJB100300502 Institutional research plan: CEZ:AV0Z10300504 Keywords : non-classical logics * formal fuzzy logic * formal fuzzy mathematics * high-order fuzzy logic Subject RIV: BA - General Mathematics Impact factor: 1.181, year: 2006
On fuzzy multiset regular languages
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B. K. Sharma
2017-03-01
Full Text Available The purpose of present work is to study some algebraic aspect of fuzzy multiset regular languages. In between, we show the equivalence of multiset regular language and fuzzy multiset regular language. Finally, we introduce the concept of pumping lemma for fuzzy multiset regular languages, which we use to establish a necessary and sufficient condition for a fuzzy multiset language to be non-constant.
Shapley's value for fuzzy games
Directory of Open Access Journals (Sweden)
Raúl Alvarado Sibaja
2009-02-01
Full Text Available This is the continuation of a previous article titled "Fuzzy Games", where I defined a new type of games based on the Multilinear extensions f, of characteristic functions and most of standard theorems for cooperative games also hold for this new type of games: The fuzzy games. Now we give some other properties and the extension of the definition of Shapley¨s Value for Fuzzy Games Keywords: game theory, fuzzy sets, multiattribute decisions.
Fuzzy HRRN CPU Scheduling Algorithm
Bashir Alam; R. Biswas; M. Alam
2011-01-01
There are several scheduling algorithms like FCFS, SRTN, RR, priority etc. Scheduling decisions of these algorithms are based on parameters which are assumed to be crisp. However, in many circumstances these parameters are vague. The vagueness of these parameters suggests that scheduler should use fuzzy technique in scheduling the jobs. In this paper we have proposed a novel CPU scheduling algorithm Fuzzy HRRN that incorporates fuzziness in basic HRRN using fuzzy Technique FIS.
Compactness in fuzzy function spaces
African Journals Online (AJOL)
In [3] we defined a notion of compactness in FCS, the category of fuzzy convergence spaces as defined by Lowen/Lowen/Wuyts [8]. In their paper the latter also introduced a fuzzy convergence structure c-lim for fuzzy function spaces thus proving that FCS is a topological quasitopos. In this paper we start the investigation of ...
Clustering algorithms for fuzzy rules decomposition
Salgado, Paulo; Igrejas, Getúlio
2007-01-01
This paper presents the development, testing and evaluation of generalized Possibilistic fuzzy c-means (FCM) algorithms applied to fuzzy sets. Clustering is formulated as a constrained minimization problem, whose solution depends on the constraints imposed on the membership function of the cluster and on the relevance measure of the fuzzy rules. This fuzzy clustering of fuzzy rules leads to a fuzzy partition of the fuzzy rules, one for each cluster, which corresp...
Multiple Fuzzy Classification Systems
Scherer, Rafał
2012-01-01
Fuzzy classiﬁers are important tools in exploratory data analysis, which is a vital set of methods used in various engineering, scientiﬁc and business applications. Fuzzy classiﬁers use fuzzy rules and do not require assumptions common to statistical classiﬁcation. Rough set theory is useful when data sets are incomplete. It deﬁnes a formal approximation of crisp sets by providing the lower and the upper approximation of the original set. Systems based on rough sets have natural ability to work on such data and incomplete vectors do not have to be preprocessed before classiﬁcation. To achieve better performance than existing machine learning systems, fuzzy classifiers and rough sets can be combined in ensembles. Such ensembles consist of a ﬁnite set of learning models, usually weak learners. The present book discusses the three aforementioned ﬁelds – fuzzy systems, rough sets and ensemble techniques. As the trained ensemble should represent a single hypothesis, a lot of attention is placed o...
A neural fuzzy controller learning by fuzzy error propagation
Nauck, Detlef; Kruse, Rudolf
1992-01-01
In this paper, we describe a procedure to integrate techniques for the adaptation of membership functions in a linguistic variable based fuzzy control environment by using neural network learning principles. This is an extension to our work. We solve this problem by defining a fuzzy error that is propagated back through the architecture of our fuzzy controller. According to this fuzzy error and the strength of its antecedent each fuzzy rule determines its amount of error. Depending on the current state of the controlled system and the control action derived from the conclusion, each rule tunes the membership functions of its antecedent and its conclusion. By this we get an unsupervised learning technique that enables a fuzzy controller to adapt to a control task by knowing just about the global state and the fuzzy error.
The foundations of fuzzy control
Lewis, Harold W
1997-01-01
Harold Lewis applied a cross-disciplinary approach in his highly accessible discussion of fuzzy control concepts. With the aid of fifty-seven illustrations, he thoroughly presents a unique mathematical formalism to explain the workings of the fuzzy inference engine and a novel test plant used in the research. Additionally, the text posits a new viewpoint on why fuzzy control is more popular in some countries than in others. A direct and original view of Japanese thinking on fuzzy control methods, based on the author's personal knowledge of - and association with - Japanese fuzzy research, is also included.
Udupa, Jayaram K.; Odhner, Dewey; Falcao, Alexandre X.; Ciesielski, Krzysztof C.; Miranda, Paulo A. V.; Vaideeswaran, Pavithra; Mishra, Shipra; Grevera, George J.; Saboury, Babak; Torigian, Drew A.
2011-03-01
To make Quantitative Radiology (QR) a reality in routine clinical practice, computerized automatic anatomy recognition (AAR) becomes essential. As part of this larger goal, we present in this paper a novel fuzzy strategy for building bodywide group-wise anatomic models. They have the potential to handle uncertainties and variability in anatomy naturally and to be integrated with the fuzzy connectedness framework for image segmentation. Our approach is to build a family of models, called the Virtual Quantitative Human, representing normal adult subjects at a chosen resolution of the population variables (gender, age). Models are represented hierarchically, the descendents representing organs contained in parent organs. Based on an index of fuzziness of the models, 32 thorax data sets, and 10 organs defined in them, we found that the hierarchical approach to modeling can effectively handle the non-linear relationships in position, scale, and orientation that exist among organs in different patients.
The first order fuzzy predicate logic (I)
International Nuclear Information System (INIS)
Sheng, Y.M.
1986-01-01
Some analysis tools of fuzzy measures, Sugeno's integrals, etc. are introduced into the semantic of the first order predicate logic to explain the concept of fuzzy quantifiers. The truth value of a fuzzy quantification proposition is represented by Sugeno's integral. With this framework, several important notions of formation rules, fuzzy valutions and fuzzy validity are discussed
Fuzzy linear programming approach for solving transportation ...
Indian Academy of Sciences (India)
ALI EBRAHIMNEJAD
fuzzy modified distribution method to obtain the optimal solution in terms of fuzzy numbers. Pandian & Natarajan. [13] introduced a new algorithm namely, fuzzy zero point method for finding fuzzy optimal solution for such FTP in which the transportation cost, supply and demand are represented by trapezoidal fuzzy numbers.
Directory of Open Access Journals (Sweden)
Fu-Gui Shi
2010-01-01
Full Text Available The notion of (L,M-fuzzy σ-algebras is introduced in the lattice value fuzzy set theory. It is a generalization of Klement's fuzzy σ-algebras. In our definition of (L,M-fuzzy σ-algebras, each L-fuzzy subset can be regarded as an L-measurable set to some degree.
Directory of Open Access Journals (Sweden)
Shawkat Alkhazaleh
2012-01-01
Full Text Available In 1999 Molodtsov introduced the concept of soft set theory as a general mathematical tool for dealing with uncertainty. Alkhazaleh et al. in 2011 introduced the definition of a soft multiset as a generalization of Molodtsov's soft set. In this paper we give the definition of fuzzy soft multiset as a combination of soft multiset and fuzzy set and study its properties and operations. We give examples for these concepts. Basic properties of the operations are also given. An application of this theory in decision-making problems is shown.
Fuzzy efficiency without convexity
DEFF Research Database (Denmark)
Hougaard, Jens Leth; Balezentis, Tomas
2014-01-01
In this paper we develop a fuzzy version of the crisp Free Disposal Hull (FDH) method for measuring technical efficiency for samples of similar production units. The FDH-method is basically Data Envelopment Analysis (DEA) without the underlying assumption of convexity of the technology set. Our...... approach builds directly upon the definition of Farrell's indexes of technical efficiency used in crisp FDH. Therefore we do not require the use of fuzzy programming techniques but only utilize ranking probabilities of intervals as well as a related definition of dominance between pairs of intervals. We...
DEFF Research Database (Denmark)
Franco de los Rios, Camilo Andres; Hougaard, Jens Leth; Nielsen, Kurt
for decision support and multidimensional interval analysis. First, the original approach is extended using fuzzy set theory which makes it possible to handle both non-interval and interval data. Second, we re-examine the ranking procedure based on semi-equivalence classes and suggest a new complementary...
Fuzzy knowledge management for the semantic web
Ma, Zongmin; Yan, Li; Cheng, Jingwei
2014-01-01
This book goes to great depth concerning the fast growing topic of technologies and approaches of fuzzy logic in the Semantic Web. The topics of this book include fuzzy description logics and fuzzy ontologies, queries of fuzzy description logics and fuzzy ontology knowledge bases, extraction of fuzzy description logics and ontologies from fuzzy data models, storage of fuzzy ontology knowledge bases in fuzzy databases, fuzzy Semantic Web ontology mapping, and fuzzy rules and their interchange in the Semantic Web. The book aims to provide a single record of current research in the fuzzy knowledge representation and reasoning for the Semantic Web. The objective of the book is to provide the state of the art information to researchers, practitioners and graduate students of the Web intelligence and at the same time serve the knowledge and data engineering professional faced with non-traditional applications that make the application of conventional approaches difficult or impossible.
Hierarchical type-2 fuzzy aggregation of fuzzy controllers
Cervantes, Leticia
2016-01-01
This book focuses on the fields of fuzzy logic, granular computing and also considering the control area. These areas can work together to solve various control problems, the idea is that this combination of areas would enable even more complex problem solving and better results. In this book we test the proposed method using two benchmark problems: the total flight control and the problem of water level control for a 3 tank system. When fuzzy logic is used it make it easy to performed the simulations, these fuzzy systems help to model the behavior of a real systems, using the fuzzy systems fuzzy rules are generated and with this can generate the behavior of any variable depending on the inputs and linguistic value. For this reason this work considers the proposed architecture using fuzzy systems and with this improve the behavior of the complex control problems.
Word Similarity from Dictionaries: Inferring Fuzzy Measures from Fuzzy Graphs
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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.
COMPACTNESS IN INTUITIONISTIC FUZZY MULTISET TOPOLOGY
Kunnambath, Shinoj Thekke; John, Sunil Jacob
2017-01-01
– In this paper, we discussVarious properties of Compact and Homeomorphic Intuitionistic Fuzzy Multiset Topological spacesarious properties of Compact and Homeomorphic Intuitionistic Fuzzy Multiset Topological spaces
Probabilistic clustering algorithms for fuzzy rules decomposition
Salgado, Paulo; Igrejas, Getúlio
2007-01-01
The fuzzy c-means (FCM) clustering algorithm is the best known and used method in fuzzy clustering and is generally applied to well defined set of data. In this paper a generalized Probabilistic fuzzy c-means (FCM) algorithm is proposed and applied to clustering fuzzy sets. This technique leads to a fuzzy partition of the fuzzy rules, one for each cluster, which corresponds to a new set of fuzzy sub-systems. When applied to the clustering of a flat fuzzy system results a set of...
Fuzzy logic particle tracking velocimetry
Wernet, Mark P.
1993-01-01
Fuzzy logic has proven to be a simple and robust method for process control. Instead of requiring a complex model of the system, a user defined rule base is used to control the process. In this paper the principles of fuzzy logic control are applied to Particle Tracking Velocimetry (PTV). Two frames of digitally recorded, single exposure particle imagery are used as input. The fuzzy processor uses the local particle displacement information to determine the correct particle tracks. Fuzzy PTV is an improvement over traditional PTV techniques which typically require a sequence (greater than 2) of image frames for accurately tracking particles. The fuzzy processor executes in software on a PC without the use of specialized array or fuzzy logic processors. A pair of sample input images with roughly 300 particle images each, results in more than 200 velocity vectors in under 8 seconds of processing time.
Inner Product over Fuzzy Matrices
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A. Nagoor Gani
2016-01-01
Full Text Available The purpose of this study was to introduce the inner product over fuzzy matrices. By virtue of this definition, α-norm is defined and the parallelogram law is proved. Again the relative fuzzy norm with respect to the inner product over fuzzy matrices is defined. Moreover Cauchy Schwarz inequality, Pythagoras, and Fundamental Minimum Principle are established. Some equivalent conditions are also proved.
Intuitionistic fuzzy aggregation and clustering
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.
Fuzzy Objects and Noncommutative Solitons
Kobayashi, Shinpei; Asakawa, Tsuguhiko
2015-01-01
The fuzzy disc is a disc-shaped region in a noncommutative plane, and is a fuzzy approximation of a commutative disc. We showed that one can introduce a concept of angles to the fuzzy disc, by using the phase operator and phase states known in quantum optics. We also constructed fan-shaped soliton solutions, which would be identified with D-branes, of a scalar field theory on the fuzzy disc and applied this concept to a theory of noncommutative gravity. This proceeding is based on our previous work.
Fuzzy algebraic hyperstructures an introduction
Davvaz, Bijan
2015-01-01
This book is intended as an introduction to fuzzy algebraic hyperstructures. As the first in its genre, it includes a number of topics, most of which reflect the authors’ past research and thus provides a starting point for future research directions. The book is organized in five chapters. The first chapter introduces readers to the basic notions of algebraic structures and hyperstructures. The second covers fuzzy sets, fuzzy groups and fuzzy polygroups. The following two chapters are concerned with the theory of fuzzy Hv-structures: while the third chapter presents the concept of fuzzy Hv-subgroup of Hv-groups, the fourth covers the theory of fuzzy Hv-ideals of Hv-rings. The final chapter discusses several connections between hypergroups and fuzzy sets, and includes a study on the association between hypergroupoids and fuzzy sets endowed with two membership functions. In addition to providing a reference guide to researchers, the book is also intended as textbook for undergraduate and graduate students.
International Nuclear Information System (INIS)
Baron, Jorge H.; Rivera, S.S.
2000-01-01
The so-called vulnerability matrix is used in the evaluation part of the probabilistic safety assessment for a nuclear power plant, during the containment event trees calculations. This matrix is established from what is knows as Numerical Categories for Engineering Judgement. This matrix is usually established with numerical values obtained with traditional arithmetic using the set theory. The representation of this matrix with fuzzy numbers is much more adequate, due to the fact that the Numerical Categories for Engineering Judgement are better represented with linguistic variables, such as 'highly probable', 'probable', 'impossible', etc. In the present paper a methodology to obtain a Fuzzy Vulnerability Matrix is presented, starting from the recommendations on the Numerical Categories for Engineering Judgement. (author)
Fuzzy Perfect Mappings and Q-Compactness in Smooth Fuzzy Topological Spaces
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C. Kalaivani
2014-03-01
Full Text Available We point out that the product of two fuzzy closed sets of smooth fuzzy topological spaces need not be fuzzy closed with respect to the the existing notion of product smooth fuzzy topology. To get this property, we introduce a new suitable product smooth fuzzy topology. We investigate whether F1×F2 and (F,H are weakly smooth fuzzy continuity whenever F1, F2, F and H are weakly smooth fuzzy continuous. Using this new product smooth fuzzy topology, we define smooth fuzzy perfect mapping and prove that composition of two smooth fuzzy perfect mappings is smooth fuzzy perfect under some additional conditions. We also introduce two new notions of compactness called Q-compactness and Q-α-compactness; and discuss the compactness of the image of a Q-compact set (Q-α-compact set under a weakly smooth fuzzy continuous function ((α,β-weakly smooth fuzzy continuous function.
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
Heinrich, Berthold
Neben der klassischen Regelungstechnik gewinnt heute eine andere Art der Herangehensweise an Regelungsaufgaben Bedeutung, die mit vermeintlich unscharfen (engl.: fuzzy) Begriffen wie ‚Temperatur ist viel zu hoch`, ‚Laufkatze ist weit weg`, ‚Ventil wird weit geöffnet` arbeitet. Zufällig oder unscharf ist diese Art der Regelung nicht, sondern sie führt über ein präzises Regelwerk zu genau determinierten Ergebnissen.
Multiple Instance Fuzzy Inference
2015-12-02
and learn the fuzzy inference system’s parameters [24, 25]. In this later technique, supervised and unsupervised learning algorithms are devised to...algorithm ( unsupervised learning ) can be used to identify local contexts of the input space, and a linear classifier (supervised learning ) can be used...instance level (patch-level) labels and would require the image to be correctly segmented and labeled prior to learning . Figure 1.1: Example of an image
Performance comparison of fuzzy and non-fuzzy classification methods
Directory of Open Access Journals (Sweden)
B. Simhachalam
2016-07-01
Full Text Available In data clustering, partition based clustering algorithms are widely used clustering algorithms. Among various partition algorithms, fuzzy algorithms, Fuzzy c-Means (FCM, Gustafson–Kessel (GK and non-fuzzy algorithm, k-means (KM are most popular methods. k-means and Fuzzy c-Means use standard Euclidian distance measure and Gustafson–Kessel uses fuzzy covariance matrix in their distance metrics. In this work, a comparative study of these algorithms with different famous real world data sets, liver disorder and wine from the UCI repository is presented. The performance of the three algorithms is analyzed based on the clustering output criteria. The results were compared with the results obtained from the repository. The results showed that Gustafson–Kessel produces close results to Fuzzy c-Means. Further, the experimental results demonstrate that k-means outperforms the Fuzzy c-Means and Gustafson–Kessel algorithms. Thus the efficiency of k-means is better than that of Fuzzy c-Means and Gustafson–Kessel algorithms.
Fuzzy Logic in Medicine and Bioinformatics
Directory of Open Access Journals (Sweden)
Angela Torres
2006-01-01
Full Text Available The purpose of this paper is to present a general view of the current applications of fuzzy logic in medicine and bioinformatics. We particularly review the medical literature using fuzzy logic. We then recall the geometrical interpretation of fuzzy sets as points in a fuzzy hypercube and present two concrete illustrations in medicine (drug addictions and in bioinformatics (comparison of genomes.
Algebraic Aspects of Families of Fuzzy Languages
Asveld, P.R.J.; Heylen, Dirk K.J.; Nijholt, Antinus; Scollo, Giuseppe
2000-01-01
We study operations on fuzzy languages such as union, concatenation,Kleene $\\star$, intersection with regular fuzzy languages, and several kinds of (iterated) fuzzy substitution. Then we consider families of fuzzy languages, closed under a fixed collection of these operations, which results in the
Algebraic Aspects of Families of Fuzzy Languages
Asveld, P.R.J.
We study operations on fuzzy languages such as union, concatenation, Kleene $\\star$, intersection with regular fuzzy languages, and several kinds of (iterated) fuzzy substitution. Then we consider families of fuzzy languages, closed under a fixed collection of these operations, which results in the
On Fuzzy Ideals of BL-Algebras
Xin, Xiao Long
2014-01-01
In this paper we investigate further properties of fuzzy ideals of a BL-algebra. The notions of fuzzy prime ideals, fuzzy irreducible ideals, and fuzzy Gödel ideals of a BL-algebra are introduced and their several properties are investigated. We give a procedure to generate a fuzzy ideal by a fuzzy set. We prove that every fuzzy irreducible ideal is a fuzzy prime ideal but a fuzzy prime ideal may not be a fuzzy irreducible ideal and prove that a fuzzy prime ideal ω is a fuzzy irreducible ideal if and only if ω(0) = 1 and |Im(ω)| = 2. We give the Krull-Stone representation theorem of fuzzy ideals in BL-algebras. Furthermore, we prove that the lattice of all fuzzy ideals of a BL-algebra is a complete distributive lattice. Finally, it is proved that every fuzzy Boolean ideal is a fuzzy Gödel ideal, but the converse implication is not true. PMID:24892085
Efficient adaptive fuzzy control scheme
Papp, Z.; Driessen, B.J.F.
1995-01-01
The paper presents an adaptive nonlinear (state-) feedback control structure, where the nonlinearities are implemented as smooth fuzzy mappings defined as rule sets. The fine tuning and adaption of the controller is realized by an indirect adaptive scheme, which modifies the parameters of the fuzzy
Fuzzy linguistic model for interpolation
International Nuclear Information System (INIS)
Abbasbandy, S.; Adabitabar Firozja, M.
2007-01-01
In this paper, a fuzzy method for interpolating of smooth curves was represented. We present a novel approach to interpolate real data by applying the universal approximation method. In proposed method, fuzzy linguistic model (FLM) applied as universal approximation for any nonlinear continuous function. Finally, we give some numerical examples and compare the proposed method with spline method
FINDCLUS : Fuzzy INdividual Differences CLUStering
Giordani, Paolo; Kiers, Henk A. L.
ADditive CLUStering (ADCLUS) is a tool for overlapping clustering of two-way proximity matrices (objects x objects). In Simple Additive Fuzzy Clustering (SAFC), a variant of ADCLUS is introduced providing a fuzzy partition of the objects, that is the objects belong to the clusters with the so-called
Qing Hu, Bao
2015-11-01
The fuzzy rough set model and interval-valued fuzzy rough set model have been introduced to handle databases with real values and interval values, respectively. Variable precision rough set was advanced by Ziarko to overcome the shortcomings of misclassification and/or perturbation in Pawlak rough sets. By combining fuzzy rough set and variable precision rough set, a variety of fuzzy variable precision rough sets were studied, which cannot only handle numerical data, but are also less sensitive to misclassification. However, fuzzy variable precision rough sets cannot effectively handle interval-valued data-sets. Research into interval-valued fuzzy rough sets for interval-valued fuzzy data-sets has commenced; however, variable precision problems have not been considered in interval-valued fuzzy rough sets and generalized interval-valued fuzzy rough sets based on fuzzy logical operators nor have interval-valued fuzzy sets been considered in variable precision rough sets and fuzzy variable precision rough sets. These current models are incapable of wide application, especially on misclassification and/or perturbation and on interval-valued fuzzy data-sets. In this paper, these models are generalized to a more integrative approach that not only considers interval-valued fuzzy sets, but also variable precision. First, we review generalized interval-valued fuzzy rough sets based on two fuzzy logical operators: interval-valued fuzzy triangular norms and interval-valued fuzzy residual implicators. Second, we propose generalized interval-valued fuzzy variable precision rough sets based on the above two fuzzy logical operators. Finally, we confirm that some existing models, including rough sets, fuzzy variable precision rough sets, interval-valued fuzzy rough sets, generalized fuzzy rough sets and generalized interval-valued fuzzy variable precision rough sets based on fuzzy logical operators, are special cases of the proposed models.
Radiation protection and fuzzy set theory
International Nuclear Information System (INIS)
Nishiwaki, Y.
1993-01-01
In radiation protection we encounter a variety of sources of uncertainties which are due to fuzziness in our cognition or perception of objects. For systematic treatment of this type of uncertainty, the concepts of fuzzy sets or fuzzy measures could be applied to construct system models, which may take into consideration both subjective or intrinsic fuzziness and objective or extrinsic fuzziness. The theory of fuzzy sets and fuzzy measures is still in a developing stage, but its concept may be applied to various problems of subjective perception of risk, nuclear safety, radiation protection and also to the problems of man-machine interface and human factor engineering or ergonomic
Igrejas, Getúlio; Salgado, Paulo
2007-01-01
This paper presents a fuzzy c-means clustering method for partitioning symbolic interval data, namely the T-S fuzzy rules. The proposed method furnish a fuzzy partition and prototype for each cluster by optimizing an adequacy criterion based on suitable squared Euclidean distances between vectors of intervals. This methodology leads to a fuzzy partition of the TS-fuzzy rules, one for each cluster, which corresponds to a new set of fuzzy sub-systems. When applied to the clustering of TS-fuzzy ...
Rutkowski, L; Cpalka, K
2003-01-01
In this paper, we derive new neuro-fuzzy structures called flexible neuro-fuzzy inference systems or FLEXNFIS. Based on the input-output data, we learn not only the parameters of the membership functions but also the type of the systems (Mamdani or logical). Moreover, we introduce: 1) softness to fuzzy implication operators, to aggregation of rules and to connectives of antecedents; 2) certainty weights to aggregation of rules and to connectives of antecedents; and 3) parameterized families of T-norms and S-norms to fuzzy implication operators, to aggregation of rules and to connectives of antecedents. Our approach introduces more flexibility to the structure and design of neuro-fuzzy systems. Through computer simulations, we show that Mamdani-type systems are more suitable to approximation problems, whereas logical-type systems may be preferred for classification problems.
Fuzzy control in environmental engineering
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...
On Intuitionistic Fuzzy Sets Theory
Atanassov, Krassimir T
2012-01-01
This book aims to be a comprehensive and accurate survey of state-of-art research on intuitionistic fuzzy sets theory and could be considered a continuation and extension of the author´s previous book on Intuitionistic Fuzzy Sets, published by Springer in 1999 (Atanassov, Krassimir T., Intuitionistic Fuzzy Sets, Studies in Fuzziness and soft computing, ISBN 978-3-7908-1228-2, 1999). Since the aforementioned book has appeared, the research activity of the author within the area of intuitionistic fuzzy sets has been expanding into many directions. The results of the author´s most recent work covering the past 12 years as well as the newest general ideas and open problems in this field have been therefore collected in this new book.
Solving Rectangular Fuzzy Games through
Directory of Open Access Journals (Sweden)
Chaudhuri Arindam
2017-12-01
Full Text Available Fuzzy set theory has been applied in many fields such as operations research, control theory and decision sciences. In particular, an application of this theory in decision making problems has a remarkable significance. In this paper, we consider a solution of rectangular fuzzy game with pay-off as imprecise numbers instead of crisp numbers viz., interval and LR-type trapezoidal fuzzy numbers. The solution of such fuzzy games with pure strategies by minimax-maximin principle is discussed. The algebraic method to solve 2 × 2 fuzzy games without saddle point by using mixed strategies is also illustrated. Here m × n payoff matrix is reduced to 2 × 2 pay-off matrix by dominance method. This fact is illustrated by means of numerical example.
Design of interpretable fuzzy systems
Cpałka, Krzysztof
2017-01-01
This book shows that the term “interpretability” goes far beyond the concept of readability of a fuzzy set and fuzzy rules. It focuses on novel and precise operators of aggregation, inference, and defuzzification leading to flexible Mamdani-type and logical-type systems that can achieve the required accuracy using a less complex rule base. The individual chapters describe various aspects of interpretability, including appropriate selection of the structure of a fuzzy system, focusing on improving the interpretability of fuzzy systems designed using both gradient-learning and evolutionary algorithms. It also demonstrates how to eliminate various system components, such as inputs, rules and fuzzy sets, whose reduction does not adversely affect system accuracy. It illustrates the performance of the developed algorithms and methods with commonly used benchmarks. The book provides valuable tools for possible applications in many fields including expert systems, automatic control and robotics.
Kalman-fuzzy algorithm in short term load forecasting
International Nuclear Information System (INIS)
Shah Baki, S.R.; Saibon, H.; Lo, K.L.
1996-01-01
A combination of Kalman-Fuzzy-Neural is developed to forecast the next 24 hours load. The input data fed to neural network are presented with training data set composed of historical load data, weather, day of the week, month of the year and holidays. The load data is fed through Kalman-Fuzzy filter before being applied to Neural Network for training. With this techniques Neural Network converges faster and the mean percentage error of predicted load is reduced as compared to the classical ANN technique
Fuzzy Hypotheses Testing in the Framework of Fuzzy Logic
Czech Academy of Sciences Publication Activity Database
Holeňa, Martin
2004-01-01
Roč. 145, - (2004), s. 229-252 ISSN 0165-0114 R&D Projects: GA AV ČR IAA1030004; GA MŠk OC 274.001 Grant - others:COST(XE) Action 274 TARSKI Institutional research plan: CEZ:AV0Z1030915 Keywords : non-classical logics * fuzzy predicate calculus * basic fuzzy logic * generalized quantifiers * fuzzy statistics and data analysis * vague hypotheses * vague significance level * method Guha Subject RIV: BB - Applied Statistics , Operational Research Impact factor: 0.734, year: 2004
Decomposition and Intersection of Two Fuzzy Numbers for Fuzzy Preference Relations
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Hui-Chin Tang
2017-10-01
Full Text Available In fuzzy decision problems, the ordering of fuzzy numbers is the basic problem. The fuzzy preference relation is the reasonable representation of preference relations by a fuzzy membership function. This paper studies Nakamura’s and Kołodziejczyk’s preference relations. Eight cases, each representing different levels of overlap between two triangular fuzzy numbers are considered. We analyze the ranking behaviors of all possible combinations of the decomposition and intersection of two fuzzy numbers through eight extensive test cases. The results indicate that decomposition and intersection can affect the fuzzy preference relations, and thereby the final ranking of fuzzy numbers.
Simulation of fuzzy dynamical systems using the LU-representation of fuzzy numbers
International Nuclear Information System (INIS)
Stefanini, Luciano; Sorini, Laerte; Guerra, Maria Letizia
2006-01-01
We suggest the use of the parametric LU-representation of the fuzzy numbers, introduced in Gear and Sintofene [Gear Ml, Sintofene L. Approximate fuzzy arithmetic operations using monotonic interpolations. Fuzzy Sets Syst 2005;150:5-33] and improved in Sintofene et al. [Stefanini L, Sorini L, Guerra ML. Parametric representations of fuzzy numbers and applications. Working Paper Series EMS, 95, University of Urbino, 2004], in the simulation of fuzzy dynamical systems or fuzzy iterated maps. We show the computational advantages of the LU-representation in extending some well known standard maps to the fuzzy context, allowing the simulation by the Zadeh's extension principle in the general case of fuzzy parameters
On m-Neighbourly Irregular Instuitionistic Fuzzy Graphs
N.R.Santhi Maheswari; C.Sekar
2016-01-01
In this paper, m-neighbourly irregular intuitionistic fuzzy graphs and m- neighbourly totally irregular intuitionistic fuzzy graphs are defined. Relation between m-neighbourly irregular intuitionistic fuzzy graph and m-neighbourly totally irregular intuitionistic fuzzy graph are discussed.
DEFF Research Database (Denmark)
Bokhof, Beate; Günther, Anke L B; Berg-Beckhoff, Gabriele
2010-01-01
from a simultaneously collected 24 h urine sample. DESIGN: Cross-sectional analyses including 439 participants of the Dortmund Nutritional and Longitudinally Designed (DONALD) Study from four age groups (3-4, 7-8, 11-13 and 18-23 years). Mean differences, Pearson correlation coefficients (r), cross.......5 (95 % CI -18.7, -8.3) g/d at age 18-23 years. Correlation coefficients were r = 0.7 for the total study sample and ranged from r = 0.5 to 0.6 in the different age groups. Both methods classified 85 % into the same/adjacent quartile for the whole study group (83-86 % for the different age groups) and 2......-classifications and Bland-Altman plots were used to assess agreement between methods. RESULTS: Weighed dietary records significantly underestimated mean protein intake by -6.4 (95 % CI -8.2, -4.7) g/d or -11 %, with the difference increasing across the age groups from -0.6 (95 % CI -2.7, 1.5) g/d at age 3-4 years to -13...
Fuzzy expert systems using CLIPS
Le, Thach C.
1994-01-01
This paper describes a CLIPS-based fuzzy expert system development environment called FCLIPS and illustrates its application to the simulated cart-pole balancing problem. FCLIPS is a straightforward extension of CLIPS without any alteration to the CLIPS internal structures. It makes use of the object-oriented and module features in CLIPS version 6.0 for the implementation of fuzzy logic concepts. Systems of varying degrees of mixed Boolean and fuzzy rules can be implemented in CLIPS. Design and implementation issues of FCLIPS will also be discussed.
HIERARCHICAL NEURO-FUZZY MODELS
FLAVIO JOAQUIM DE SOUZA
1999-01-01
Esta dissertação apresenta uma nova proposta de sistemas (modelos) neuro-fuzzy que possuem, além do tradicional aprendizado dos parâmetros, comuns às redes neurais e aos sistemas nero-fuzzy, as seguintes características: aprendizado de estrutura, a partir do uso de particionamentos recursisvos; número maior de entradas que o comumente encontrado nos sistemas neuro-fuzzy; e regras com hierarquia. A definição da estrutura é uma necessidade que surge quando da imp...
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.
Fuzzy resource optimization for safeguards
International Nuclear Information System (INIS)
Zardecki, A.; Markin, J.T.
1991-01-01
Authorization, enforcement, and verification -- three key functions of safeguards systems -- form the basis of a hierarchical description of the system risk. When formulated in terms of linguistic rather than numeric attributes, the risk can be computed through an algorithm based on the notion of fuzzy sets. Similarly, this formulation allows one to analyze the optimal resource allocation by maximizing the overall detection probability, regarded as a linguistic variable. After summarizing the necessary elements of the fuzzy sets theory, we outline the basic algorithm. This is followed by a sample computation of the fuzzy optimization. 10 refs., 1 tab
Implementation of Steiner point of fuzzy set.
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.
Strong sum distance in fuzzy graphs.
Tom, Mini; Sunitha, Muraleedharan Shetty
2015-01-01
In this paper the idea of strong sum distance which is a metric, in a fuzzy graph is introduced. Based on this metric the concepts of eccentricity, radius, diameter, center and self centered fuzzy graphs are studied. Some properties of eccentric nodes, peripheral nodes and central nodes are obtained. A characterisation of self centered complete fuzzy graph is obtained and conditions under which a fuzzy cycle is self centered are established. We have proved that based on this metric, an eccentric node of a fuzzy tree G is a fuzzy end node of G and a node is an eccentric node of a fuzzy tree if and only if it is a peripheral node of G and the center of a fuzzy tree consists of either one or two neighboring nodes. The concepts of boundary nodes and interior nodes in a fuzzy graph based on strong sum distance are introduced. Some properties of boundary nodes, interior nodes and complete nodes are studied.
Application of Fuzzy theory to project scheduling with critical path ...
African Journals Online (AJOL)
Application of Fuzzy theory to project scheduling with critical path method. ... Journal of Applied Sciences and Environmental Management ... theory. The crisp activity durations are modeled as triangular fuzzy sets. Fuzzy forward pass was carried out to determine fuzzy activity earliest start, fuzzy event earliest time and fuzzy ...
Theta-Generalized closed sets in fuzzy topological spaces
International Nuclear Information System (INIS)
El-Shafei, M.E.; Zakari, A.
2006-01-01
In this paper we introduce the concepts of theta-generalized closed fuzzy sets and generalized fuzzy sets in topological spaces. Furthermore, generalized fuzzy sets are extended to theta-generalized fuzzy sets. Also, we introduce the concepts of fuzzy theta-generalized continuous and fuzzy theta-generalized irresolute mappings. (author)
A Bibliography on Fuzzy Automata, Grammars and Lanuages
Asveld, P.R.J.
1995-01-01
This bibliography contains references to papers on fuzzy formal languages, the generation of fuzzy languages by means of fuzzy grammars, the recognition of fuzzy languages by fuzzy automata and machines, as well as some applications of fuzzy set theory to syntactic pattern recognition, linguistics
A Bibliography on Fuzzy Automata, Grammars and Lanuages
Asveld, P.R.J.
1996-01-01
This bibliography contains references to papers on fuzzy formal languages, the generation of fuzzy languages by means of fuzzy grammars, the recognition of fuzzy languages by fuzzy automata and machines, as well as some applications of fuzzy set theory to syntactic pattern recognition, linguistics
Fuzzy random variables — I. definitions and theorems
Kwakernaak, H.
1978-01-01
Fuzziness is discussed in the context of multivalued logic, and a corresponding view of fuzzy sets is given. Fuzzy random variables are introduced as random variables whose values are not real but fuzzy numbers, and subsequently redefined as a particular kind of fuzzy set. Expectations of fuzzy
Comments on fuzzy control systems design via fuzzy Lyapunov functions.
Guelton, Kevin; Guerra, Thierry-Marie; Bernal, Miguel; Bouarar, Tahar; Manamanni, Noureddine
2010-06-01
This paper considers the work entitled "Fuzzy control systems design via fuzzy Lyapunov functions" and published in IEEE Transactions on Systems, Man, and Cybernetics-Part B , where the authors try to extend the work of Rhee and Won. Nevertheless, the results proposed by Li have been obtained without taking into account a necessary path independency condition to ensure the line integral function to be a Lyapunov function candidate, and consequently, the proposed global asymptotic stability and stabilization conditions are unsuitable.
Proceedings of the Third International Workshop on Neural Networks and Fuzzy Logic, volume 1
Culbert, Christopher J. (Editor)
1993-01-01
Documented here are papers presented at the Neural Networks and Fuzzy Logic Workshop sponsored by the National Aeronautics and Space Administration and cosponsored by the University of Houston, Clear Lake. The workshop was held June 1-3, 1992 at the Lyndon B. Johnson Space Center in Houston, Texas. During the three days approximately 50 papers were presented. Technical topics addressed included adaptive systems; learning algorithms; network architectures; vision; robotics; neurobiological connections; speech recognition and synthesis; fuzzy set theory and application, control, and dynamics processing; space applications; fuzzy logic and neural network computers; approximate reasoning; and multiobject decision making.
Proceedings of the Third International Workshop on Neural Networks and Fuzzy Logic, volume 2
Culbert, Christopher J. (Editor)
1993-01-01
Papers presented at the Neural Networks and Fuzzy Logic Workshop sponsored by the National Aeronautics and Space Administration and cosponsored by the University of Houston, Clear Lake, held 1-3 Jun. 1992 at the Lyndon B. Johnson Space Center in Houston, Texas are included. During the three days approximately 50 papers were presented. Technical topics addressed included adaptive systems; learning algorithms; network architectures; vision; robotics; neurobiological connections; speech recognition and synthesis; fuzzy set theory and application, control and dynamics processing; space applications; fuzzy logic and neural network computers; approximate reasoning; and multiobject decision making.
Completeness and regularity of generalized fuzzy graphs.
Samanta, Sovan; Sarkar, Biswajit; Shin, Dongmin; Pal, Madhumangal
2016-01-01
Fuzzy graphs are the backbone of many real systems like networks, image, scheduling, etc. But, due to some restriction on edges, fuzzy graphs are limited to represent for some systems. Generalized fuzzy graphs are appropriate to avoid such restrictions. In this study generalized fuzzy graphs are introduced. In this study, matrix representation of generalized fuzzy graphs is described. Completeness and regularity are two important parameters of graph theory. Here, regular and complete generalized fuzzy graphs are introduced. Some properties of them are discussed. After that, effective regular graphs are exemplified.
(r,s)-Fuzzy F-open sets and (r,s)-fuzzy F-closed spaces
International Nuclear Information System (INIS)
Azab Abd-Allah, M.; El-Saady, Kamal; Ghareeb, A.
2009-01-01
In this paper, we introduce the concepts of (r,s)-fuzzy F-open and (r,s)-fuzzy F-closed sets in double fuzzy topological spaces. We used them to explain the notions of (r,s)-fuzzy F-closed spaces. Also, we give some characterization of (r,s)-fuzzy F-closeness in terms of fuzzy filterbasis.
FUZZY LOGIC IN LEGAL EDUCATION
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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
2005-01-01
A new all-electronic Particle Image Velocimetry technique that can efficiently map high speed gas flows has been developed in-house at the NASA Lewis Research Center. Particle Image Velocimetry is an optical technique for measuring the instantaneous two component velocity field across a planar region of a seeded flow field. A pulsed laser light sheet is used to illuminate the seed particles entrained in the flow field at two instances in time. One or more charged coupled device (CCD) cameras can be used to record the instantaneous positions of particles. Using the time between light sheet pulses and determining either the individual particle displacements or the average displacement of particles over a small subregion of the recorded image enables the calculation of the fluid velocity. Fuzzy logic minimizes the required operator intervention in identifying particles and computing velocity. Using two cameras that have the same view of the illumination plane yields two single exposure image frames. Two competing techniques that yield unambiguous velocity vector direction information have been widely used for reducing the single-exposure, multiple image frame data: (1) cross-correlation and (2) particle tracking. Correlation techniques yield averaged velocity estimates over subregions of the flow, whereas particle tracking techniques give individual particle velocity estimates. For the correlation technique, the correlation peak corresponding to the average displacement of particles across the subregion must be identified. Noise on the images and particle dropout result in misidentification of the true correlation peak. The subsequent velocity vector maps contain spurious vectors where the displacement peaks have been improperly identified. Typically these spurious vectors are replaced by a weighted average of the neighboring vectors, thereby decreasing the independence of the measurements. In this work, fuzzy logic techniques are used to determine the true
Sistem Pakar Fuzzy Untuk Optimasi Penggunaan Bandwidth Jaringan Komputer
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Mustaziri Mustaziri
2014-02-01
Full Text Available The need for bandwidth availability today is very high along with the increase of infrastructural growth of internet network. Therefore, the presence of efficient, reliable, and economical service availability system is required. It can be achieved byperforming good and appropriate system planning. In providing efficient and reliable internet services, one of the supporting factors is the optimization of bandwidth using. To optimize the use of bandwidth, we use fuzzy expert system by Sugeno method. This fuzzy expert system use 3 input variables, such as lecture room, day, and t ime, with one output variable of the capacity of bandwidth used. Rule base being made based on the consultation with the expert to determine the rule base for fuzzy system input. The computation to determine the average error using the computation formula of MAPE (Means Absolute Percentage Error which is the error median of absolute percentage. The data of the research results on the optimization of bandwidth using in fuzzy expert system with Sugeno method obtain from verification, that is by comparing actual data to prediction data with fuzzy system. The average error result is 6,5142 %.Keywords: Fuzzy Expert System; Optimization; Bandwidth
On Fuzzy β-I-open sets and Fuzzy β-I-continuous functions
International Nuclear Information System (INIS)
Keskin, Aynur
2009-01-01
In this paper, first of all we obtain some properties and characterizations of fuzzy β-I-open sets. After that, we also define the notion of β-I-closed sets and obtain some properties. Lastly, we introduce the notions of fuzzy β-I-continuity with the help of fuzzy β-I-open sets to obtain decomposition of fuzzy continuity.
On Fuzzy {beta}-I-open sets and Fuzzy {beta}-I-continuous functions
Energy Technology Data Exchange (ETDEWEB)
Keskin, Aynur [Department of Mathematics, Faculty of Science and Arts, Selcuk University, Campus, 42075 Konya (Turkey)], E-mail: akeskin@selcuk.edu.tr
2009-11-15
In this paper, first of all we obtain some properties and characterizations of fuzzy {beta}-I-open sets. After that, we also define the notion of {beta}-I-closed sets and obtain some properties. Lastly, we introduce the notions of fuzzy {beta}-I-continuity with the help of fuzzy {beta}-I-open sets to obtain decomposition of fuzzy continuity.
Supply chain management under fuzziness recent developments and techniques
Öztayşi, Başar
2014-01-01
Supply Chain Management Under Fuzziness presents recently developed fuzzy models and techniques for supply chain management. These include: fuzzy PROMETHEE, fuzzy AHP, fuzzy ANP, fuzzy VIKOR, fuzzy DEMATEL, fuzzy clustering, fuzzy linear programming, and fuzzy inference systems. The book covers both practical applications and new developments concerning these methods. This book offers an excellent resource for researchers and practitioners in supply chain management and logistics, and will provide them with new suggestions and directions for future research. Moreover, it will support graduate students in their university courses, such as specialized courses on supply chains and logistics, as well as related courses in the fields of industrial engineering, engineering management and business administration.
Fuzzy relational calculus theory, applications and software
Peeva, Ketty
2004-01-01
This book examines fuzzy relational calculus theory with applications in various engineering subjects. The scope of the text covers unified and exact methods with algorithms for direct and inverse problem resolution in fuzzy relational calculus. Extensive engineering applications of fuzzy relation compositions and fuzzy linear systems (linear, relational and intuitionistic) are discussed. Some examples of such applications include solutions of equivalence, reduction and minimization problems in fuzzy machines, pattern recognition in fuzzy languages, optimization and inference engines in textile and chemical engineering, etc. A comprehensive overview of the authors' original work in fuzzy relational calculus is also provided in each chapter. The attached CD-Rom contains a toolbox with many functions for fuzzy calculations, together with an original algorithm for inverse problem resolution in MATLAB. This book is also suitable for use as a textbook in related courses at advanced undergraduate and graduate level...
Compound Option Pricing under Fuzzy Environment
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Xiandong Wang
2014-01-01
Full Text Available Considering the uncertainty of a financial market includes two aspects: risk and vagueness; in this paper, fuzzy sets theory is applied to model the imprecise input parameters (interest rate and volatility. We present the fuzzy price of compound option by fuzzing the interest and volatility in Geske’s compound option pricing formula. For each α, the α-level set of fuzzy prices is obtained according to the fuzzy arithmetics and the definition of fuzzy-valued function. We apply a defuzzification method based on crisp possibilistic mean values of the fuzzy interest rate and fuzzy volatility to obtain the crisp possibilistic mean value of compound option price. Finally, we present a numerical analysis to illustrate the compound option pricing under fuzzy environment.
A new Method for the Comparison of two fuzzy numbers extending Fuzzy Max Order
De Runz, Cyril; Desjardin, Éric; Herbin, Michel; Piantoni, Frederic
2006-01-01
International audience; To obtain archaeological simulated maps, we need to compare dates of excavation data, represented by fuzzy numbers. Fuzzy Max Order (FMO) is a partial order relation on the set of the fuzzy numbers. But FMO is not able to compare two fuzzy numbers in some situations. In this paper, we propose a new method, Possibilistic Variation Order, extending FMO. We build new indices to order two fuzzy numbers which give us a weighted indication of the order obtained.
Dhruba Das; Hemanta K. Baruah
2015-01-01
In this article, based on Zadeh’s extension principle we have apply the parametric programming approach to construct the membership functions of the performance measures when the interarrival time and the service time are fuzzy numbers based on the Baruah’s Randomness- Fuzziness Consistency Principle. The Randomness-Fuzziness Consistency Principle leads to defining a normal law of fuzziness using two different laws of randomness. In this article, two fuzzy queues FM...
An Intelligent Trading System with Fuzzy Rules and Fuzzy Capital Management
Naranjo, Rodrigo; Meco, Albert; Arroyo Gallardo, Javier; Santos Peñas, Matilde
2015-01-01
In this work we are proposing a trading system where fuzzy logic is applied not only for defining the trading rules, but also for managing the capital to invest. In fact, two fuzzy decision support systems are developed. The first one uses fuzzy logic to design the trading rules and to apply the stock market technical indicators. The second one enhances this fuzzy trading system adding a fuzzy strategy to manage the capital to trade. Additionally, a new technical market indicator that produce...
FuzzySRI-II A fuzzy rule induction algorithm for numerical output prediction
Afifi, A.
2014-01-01
Current inductive learning algorithms have difficulties handling attributes with numerical output values. This paper presents FuzzySRI-II, a new fuzzy rule induction algorithm for the prediction of numerical outputs. FuzzySRI-II integrates the comprehensibility and ease of application of rule induction algorithms with the uncertainty handling and approximate reasoning capabilities of fuzzy sets. The performance of the proposed FuzzySRI-II algorithm in two simulated control applications involv...
Fuzzy Arden Syntax: A fuzzy programming language for medicine.
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
FFLP problem with symmetric trapezoidal fuzzy numbers
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Reza Daneshrad
2015-04-01
Full Text Available The most popular approach for solving fully fuzzy linear programming (FFLP problems is to convert them into the corresponding deterministic linear programs. Khan et al. (2013 [Khan, I. U., Ahmad, T., & Maan, N. (2013. A simplified novel technique for solving fully fuzzy linear programming problems. Journal of Optimization Theory and Applications, 159(2, 536-546.] claimed that there had been no method in the literature to find the fuzzy optimal solution of a FFLP problem without converting it into crisp linear programming problem, and proposed a technique for the same. Others showed that the fuzzy arithmetic operation used by Khan et al. (2013 had some problems in subtraction and division operations, which could lead to misleading results. Recently, Ezzati et al. (2014 [Ezzati, R., Khorram, E., & Enayati, R. (2014. A particular simplex algorithm to solve fuzzy lexicographic multi-objective linear programming problems and their sensitivity analysis on the priority of the fuzzy objective functions. Journal of Intelligent and Fuzzy Systems, 26(5, 2333-2358.] defined a new operation on symmetric trapezoidal fuzzy numbers and proposed a new algorithm to find directly a lexicographic/preemptive fuzzy optimal solution of a fuzzy lexicographic multi-objective linear programming problem by using new fuzzy arithmetic operations, but their model was not fully fuzzy optimization. In this paper, a new method, by using Ezzati et al. (2014’s fuzzy arithmetic operation and a fuzzy version of simplex algorithm, is proposed for solving FFLP problem whose parameters are represented by symmetric trapezoidal fuzzy number without converting the given problem into crisp equivalent problem. By using the proposed method, the fuzzy optimal solution of FFLP problem can be easily obtained. A numerical example is provided to illustrate the proposed method.
A New Approach to Fuzzy Arithmetic
Popov, Antony
2010-01-01
This work shows an application of a generalized approach for constructing dilation-erosion adjunctions on fuzzy sets. More precisely, operations on fuzzy quantities and fuzzy numbers are considered. By the generalized approach an analogy with the well known interval computations could be drawn and thus we can define outer and inner operations on fuzzy objects. These operations are found to be useful in the control of bioprocesses, ecology and other domains where data uncerta...
Linear Design Approach to a Fuzzy Controller
DEFF Research Database (Denmark)
Jantzen, Jan
1999-01-01
A ball-balancer, basically an inverted pendulum problem, is stabilised by a linear controller. With certain design choices, a fuzzy controller is equivalent to a summation; thus it can replace the linear controller. It can be claimed, that the fuzzy controller performs at least as well...... as the linear controller, since the linear controller is contained in the fuzzy controller. The approach makes it somewhat easier to design a fuzzy controller....
Neuro-fuzzy Control of Integrating Processes
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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.
Consistent linguistic fuzzy preference relations method with ranking fuzzy numbers
Ridzuan, Siti Amnah Mohd; Mohamad, Daud; Kamis, Nor Hanimah
2014-12-01
Multi-Criteria Decision Making (MCDM) methods have been developed to help decision makers in selecting the best criteria or alternatives from the options given. One of the well known methods in MCDM is the Consistent Fuzzy Preference Relation (CFPR) method, essentially utilizes a pairwise comparison approach. This method was later improved to cater subjectivity in the data by using fuzzy set, known as the Consistent Linguistic Fuzzy Preference Relations (CLFPR). The CLFPR method uses the additive transitivity property in the evaluation of pairwise comparison matrices. However, the calculation involved is lengthy and cumbersome. To overcome this problem, a method of defuzzification was introduced by researchers. Nevertheless, the defuzzification process has a major setback where some information may lose due to the simplification process. In this paper, we propose a method of CLFPR that preserves the fuzzy numbers form throughout the process. In obtaining the desired ordering result, a method of ranking fuzzy numbers is utilized in the procedure. This improved procedure for CLFPR is implemented to a case study to verify its effectiveness. This method is useful for solving decision making problems and can be applied to many areas of applications.
Decomposed fuzzy systems and their application in direct adaptive fuzzy control.
Hsueh, Yao-Chu; Su, Shun-Feng; Chen, Ming-Chang
2014-10-01
In this paper, a novel fuzzy structure termed as the decomposed fuzzy system (DFS) is proposed to act as the fuzzy approximator for adaptive fuzzy control systems. The proposed structure is to decompose each fuzzy variable into layers of fuzzy systems, and each layer is to characterize one traditional fuzzy set. Similar to forming fuzzy rules in traditional fuzzy systems, layers from different variables form the so-called component fuzzy systems. DFS is proposed to provide more adjustable parameters to facilitate possible adaptation in fuzzy rules, but without introducing a learning burden. It is because those component fuzzy systems are independent so that it can facilitate minimum distribution learning effects among component fuzzy systems. It can be seen from our experiments that even when the rule number increases, the learning time in terms of cycles is still almost constant. It can also be found that the function approximation capability and learning efficiency of the DFS are much better than that of the traditional fuzzy systems when employed in adaptive fuzzy control systems. Besides, in order to further reduce the computational burden, a simplified DFS is proposed in this paper to satisfy possible real time constraints required in many applications. From our simulation results, it can be seen that the simplified DFS can perform fairly with a more concise decomposition structure.
Schröder, Maike; Müller, Katrin; Falkenstein, Michael; Stehle, Peter; Kersting, Mathilde; Libuda, Lars
2016-10-01
Studies about effects of school lunch on children's cognition are rare; two previous studies (CogniDo, CogniDo PLUS) generally found no negative effects of lunch on children's cognitive performance at the end of lunch break (i.e. 45 min after finishing lunch), but suggested potential beneficial effects for single parameters. Therefore, the present study investigated the hypothesis of potential positive effects of school lunch on cognitive performance at early afternoon (90 min after finishing lunch). A randomised, cross-over intervention trial was conducted at a comprehensive school with fifth and sixth grade students. Participants were randomised into two groups: On day 1, group 1 did not eat lunch, whereas group 2 received lunch ad libitum. On day 2 (1 week later), group 2 did not eat lunch and group 1 received lunch ad libitum. The cognitive parameters task switching, working memory updating and alertness were tested using a computerised test battery 90 min after finishing the meal. Of the 204 recruited children, fifty were excluded because of deviations from the study protocol or absence on one of the 2 test days, which resulted in 154 participants. Data showed no significant effects of lunch on task switching, working memory updating and alertness (P values between 0·07 and 0·79). The present study suggests that school lunch does not seem to have beneficial effects on children's cognitive functions regarding the conducted tests at early afternoon. Together with our previous studies, we conclude that school lunch in general has no negative effects on cognitive performance in children. However, beneficial effects seem to be restricted to a relatively short time period after eating lunch.
Effectiveness of Securities with Fuzzy Probabilistic Return
Directory of Open Access Journals (Sweden)
Krzysztof Piasecki
2011-01-01
Full Text Available The generalized fuzzy present value of a security is defined here as fuzzy valued utility of cash flow. The generalized fuzzy present value cannot depend on the value of future cash flow. There exists such a generalized fuzzy present value which is not a fuzzy present value in the sense given by some authors. If the present value is a fuzzy number and the future value is a random one, then the return rate is given as a probabilistic fuzzy subset on a real line. This kind of return rate is called a fuzzy probabilistic return. The main goal of this paper is to derive the family of effective securities with fuzzy probabilistic return. Achieving this goal requires the study of the basic parameters characterizing fuzzy probabilistic return. Therefore, fuzzy expected value and variance are determined for this case of return. These results are a starting point for constructing a three-dimensional image. The set of effective securities is introduced as the Pareto optimal set determined by the maximization of the expected return rate and minimization of the variance. Finally, the set of effective securities is distinguished as a fuzzy set. These results are obtained without the assumption that the distribution of future values is Gaussian. (original abstract
On the intuitionistic fuzzy inner product spaces
International Nuclear Information System (INIS)
Goudarzi, M.; Vaezpour, S.M.; Saadati, R.
2009-01-01
In this paper, the definition of intuitionistic fuzzy inner product is given. By virtue of this definition, some convergence theorems, Schwarts inequality and the orthogonal concept for intuitionistic fuzzy inner product spaces are established and introduced. Moreover the relationship between this kind of spaces and intuitionistic fuzzy normed spaces is considered.
Fuzzy Stability of Quadratic Functional Equations
Directory of Open Access Journals (Sweden)
Jang Sun-Young
2010-01-01
Full Text Available The fuzzy stability problems for the Cauchy additive functional equation and the Jensen additive functional equation in fuzzy Banach spaces have been investigated by Moslehian et al. In this paper, we prove the generalized Hyers-Ulam stability of the following quadratic functional equations and in fuzzy Banach spaces.
Fuzzy Stability of Quadratic Functional Equations
Dong Yun Shin; Choonkil Park; Sun-Young Jang; Jung Rye Lee
2010-01-01
The fuzzy stability problems for the Cauchy additive functional equation and the Jensen additive functional equation in fuzzy Banach spaces have been investigated by Moslehian et al. In this paper, we prove the generalized Hyers-Ulam stability of the following quadratic functional equations and in fuzzy Banach spaces.
Possible use of fuzzy logic in database
Directory of Open Access Journals (Sweden)
Vaclav Bezdek
2011-04-01
Full Text Available The article deals with fuzzy logic and its possible use in database systems. At first fuzzy thinking style is shown on a simple example. Next the advantages of the fuzzy approach to database searching are considered on the database of used cars in the Czech Republic.
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)
Fuzzy image processing in sun sensor
Mobasser, S.; Liebe, C. C.; Howard, A.
2003-01-01
This paper will describe how the fuzzy image processing is implemented in the instrument. Comparison of the Fuzzy image processing and a more conventional image processing algorithm is provided and shows that the Fuzzy image processing yields better accuracy then conventional image processing.
Somewhat Slightly Generalized Double Fuzzy Semicontinuous Functions
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Fatimah M. Mohammed
2014-01-01
Full Text Available The aim of this paper is to introduce the concepts of somewhat slightly generalized double fuzzy semicontinuous functions and somewhat slightly generalized double fuzzy semiopen functions in double fuzzy topological spaces. Some interesting properties and characterizations of these functions are introduced and discussed. Furthermore, the relationships among the new concepts are discussed with some necessary examples.
Full averaging of fuzzy impulsive differential inclusions
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Natalia V. Skripnik
2010-09-01
Full Text Available In this paper the substantiation of the method of full averaging for fuzzy impulsive differential inclusions is studied. We extend the similar results for impulsive differential inclusions with Hukuhara derivative (Skripnik, 2007, for fuzzy impulsive differential equations (Plotnikov and Skripnik, 2009, and for fuzzy differential inclusions (Skripnik, 2009.
The fuzzy approach to statistical analysis
Coppi, Renato; Gil, Maria A.; Kiers, Henk A. L.
2006-01-01
For the last decades, research studies have been developed in which a coalition of Fuzzy Sets Theory and Statistics has been established with different purposes. These namely are: (i) to introduce new data analysis problems in which the objective involves either fuzzy relationships or fuzzy terms;
CAPP MODEL OF FUZZY SYSTEMS AND FUZZY MANUFACTURABILITY
Directory of Open Access Journals (Sweden)
Radivoje Antić
2013-10-01
Full Text Available They give the soles of technological design process using fuzzy logic for metal cutting, referring to the determination of all the elements of production process: the dimensions and quality of the workpiece material, the sequence and scope of operations, the order and content of the procedures, the size of the type of machine types and tool types and gauges, regime and time of processing. It further explains manufacturability machine parts for robust design of a new product. He also offers manufacturability for cylindrical, prismatic workpieces and boxes. It explains the mathematical expressions of fuzzy logic which described above manufacturability. In fuzzy logic are used mathematical operations minimization and maximization. They are used to determine the critical solutions and choice of cost effective solutions. Provides an example of using the model to determine of the manufacturability.
Fuzzy logic of Aristotelian forms
Energy Technology Data Exchange (ETDEWEB)
Perlovsky, L.I. [Nichols Research Corp., Lexington, MA (United States)
1996-12-31
Model-based approaches to pattern recognition and machine vision have been proposed to overcome the exorbitant training requirements of earlier computational paradigms. However, uncertainties in data were found to lead to a combinatorial explosion of the computational complexity. This issue is related here to the roles of a priori knowledge vs. adaptive learning. What is the a-priori knowledge representation that supports learning? I introduce Modeling Field Theory (MFT), a model-based neural network whose adaptive learning is based on a priori models. These models combine deterministic, fuzzy, and statistical aspects to account for a priori knowledge, its fuzzy nature, and data uncertainties. In the process of learning, a priori fuzzy concepts converge to crisp or probabilistic concepts. The MFT is a convergent dynamical system of only linear computational complexity. Fuzzy logic turns out to be essential for reducing the combinatorial complexity to linear one. I will discuss the relationship of the new computational paradigm to two theories due to Aristotle: theory of Forms and logic. While theory of Forms argued that the mind cannot be based on ready-made a priori concepts, Aristotelian logic operated with just such concepts. I discuss an interpretation of MFT suggesting that its fuzzy logic, combining a-priority and adaptivity, implements Aristotelian theory of Forms (theory of mind). Thus, 2300 years after Aristotle, a logic is developed suitable for his theory of mind.
Fuzzy-Rough Cognitive Networks.
Nápoles, Gonzalo; Mosquera, Carlos; Falcon, Rafael; Grau, Isel; Bello, Rafael; Vanhoof, Koen
2018-01-01
Rough Cognitive Networks (RCNs) are a kind of granular neural network that augments the reasoning rule present in Fuzzy Cognitive Maps with crisp information granules coming from Rough Set Theory. While RCNs have shown promise in solving different classification problems, this model is still very sensitive to the similarity threshold upon which the rough information granules are built. In this paper, we cast the RCN model within the framework of fuzzy rough sets in an attempt to eliminate the need for a user-specified similarity threshold while retaining the model's discriminatory power. As far as we know, this is the first study that brings fuzzy sets into the domain of rough cognitive mapping. Numerical results in the presence of 140 well-known pattern classification problems reveal that our approach, referred to as Fuzzy-Rough Cognitive Networks, is capable of outperforming most traditional classifiers used for benchmarking purposes. Furthermore, we explore the impact of using different heterogeneous distance functions and fuzzy operators over the performance of our granular neural network. Copyright © 2017 Elsevier Ltd. All rights reserved.
Fuzzy Logic for Incidence Geometry
2016-01-01
The paper presents a mathematical framework for approximate geometric reasoning with extended objects in the context of Geography, in which all entities and their relationships are described by human language. These entities could be labelled by commonly used names of landmarks, water areas, and so forth. Unlike single points that are given in Cartesian coordinates, these geographic entities are extended in space and often loosely defined, but people easily perform spatial reasoning with extended geographic objects “as if they were points.” Unfortunately, up to date, geographic information systems (GIS) miss the capability of geometric reasoning with extended objects. The aim of the paper is to present a mathematical apparatus for approximate geometric reasoning with extended objects that is usable in GIS. In the paper we discuss the fuzzy logic (Aliev and Tserkovny, 2011) as a reasoning system for geometry of extended objects, as well as a basis for fuzzification of the axioms of incidence geometry. The same fuzzy logic was used for fuzzification of Euclid's first postulate. Fuzzy equivalence relation “extended lines sameness” is introduced. For its approximation we also utilize a fuzzy conditional inference, which is based on proposed fuzzy “degree of indiscernibility” and “discernibility measure” of extended points. PMID:27689133
Nakamura, Sandra; Baptiste, H. Prentice
2006-01-01
In this article, the authors describe how they capitalized on their first-grade students' love of dinosaurs by hosting a fun-filled Dinosaur Day in their classroom. On Dinosaur Day, students rotated through four dinosaur-related learning stations that integrated science content with art, language arts, math, and history in a fun and time-efficient…
Fuzzy Clustering Methods and their Application to Fuzzy Modeling
DEFF Research Database (Denmark)
Kroszynski, Uri; Zhou, Jianjun
1999-01-01
. A method to obtain an optimized number of clusters is outlined. Based upon the cluster's characteristics, a behavioural model is formulated in terms of a rule-base and an inference engine. The article reviews several variants for the model formulation. Some limitations of the methods are listed......Fuzzy modeling techniques based upon the analysis of measured input/output data sets result in a set of rules that allow to predict system outputs from given inputs. Fuzzy clustering methods for system modeling and identification result in relatively small rule-bases, allowing fast, yet accurate...
Assessment of Seismic Damage on The Exist Buildings Using Fuzzy Logic
Pınar, USTA; Nihat, MOROVA; EVCİ, Ahmet; ERGÜN, Serap
2018-01-01
Earthquake as a natural disaster could damage the lives of many people and buildings all over the world. These is micvulnerability of the buildings needs to be evaluated. Accurate evaluation of damage sustained by buildings during natural disaster events is critical to determine the buildings safety and their suitability for future occupancy. The earthquake is one of the disasters that structures face the most. There fore, there is a need to evaluate seismic damage and vulnerability of the buildings to protect them. These days fuzzy systems have been widely used in different fields of science because of its simpli city and efficiency. Fuzzy logic provides a suitable framework for reasoning, deduction, and decision making in fuzzy conditions. In this paper, studies on earthquake hazard evaluation of buildings by fuzzy logic modeling concepts in the literature have been investigated and evaluated, as a whole.
On Intuitionistic Fuzzy Context-Free Languages
Directory of Open Access Journals (Sweden)
Jianhua Jin
2013-01-01
automata theory. Additionally, we introduce the concepts of Chomsky normal form grammar (IFCNF and Greibach normal form grammar (IFGNF based on intuitionistic fuzzy sets. The results of our study indicate that intuitionistic fuzzy context-free languages generated by IFCFGs are equivalent to those generated by IFGNFs and IFCNFs, respectively, and they are also equivalent to intuitionistic fuzzy recognizable step functions. Then some operations on the family of intuitionistic fuzzy context-free languages are discussed. Finally, pumping lemma for intuitionistic fuzzy context-free languages is investigated.
Combining fuzzy mathematics with fuzzy logic to solve business management problems
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.
An improved robust fuzzy-PID controller with optimal fuzzy reasoning.
Li, Han-Xiong; Zhang, Lei; Cai, Kai-Yuan; Chen, Guanrong
2005-12-01
Many fuzzy control schemes used in industrial practice today are based on some simplified fuzzy reasoning methods, which are simple but at the expense of losing robustness, missing fuzzy characteristics, and having inconsistent inference. The concept of optimal fuzzy reasoning is introduced in this paper to overcome these shortcomings. The main advantage is that an integration of the optimal fuzzy reasoning with a PID control structure will generate a new type of fuzzy-PID control schemes with inherent optimal-tuning features for both local optimal performance and global tracking robustness. This new fuzzy-PID controller is then analyzed quantitatively and compared with other existing fuzzy-PID control methods. Both analytical and numerical studies clearly show the improved robustness of the new fuzzy-PID controller.
Fuzzy Logic Reliability Centered Maintenance
Directory of Open Access Journals (Sweden)
Felecia .
2014-01-01
Full Text Available Reliability Centered Maintenence (RCM is a systematic maintenence strategy based on system reliability. Application of RCM process will not always come out with a binary output of “yes” and “no”. Most of the time they are not supported with available detail information to calculate system reliability. The fuzzy logic method attempts to eliminate the uncertainty by providing “truth” in different degrees.Data and responses from maintenance department will be processed using the two methods (reliability centered maintenance and fuzzy logic to design maintenance strategy for the company. The results of the fuzzy logic RCM application are maintenance strategy which fit with current and future condition.
Fuzzy Morphological Polynomial Image Representation
Directory of Open Access Journals (Sweden)
Chin-Pan Huang
2010-01-01
Full Text Available A novel signal representation using fuzzy mathematical morphology is developed. We take advantage of the optimum fuzzy fitting and the efficient implementation of morphological operators to extract geometric information from signals. The new representation provides results analogous to those given by the polynomial transform. Geometrical decomposition of a signal is achieved by windowing and applying sequentially fuzzy morphological opening with structuring functions. The resulting representation is made to resemble an orthogonal expansion by constraining the results of opening to equate adapted structuring functions. Properties of the geometric decomposition are considered and used to calculate the adaptation parameters. Our procedure provides an efficient and flexible representation which can be efficiently implemented in parallel. The application of the representation is illustrated in data compression and fractal dimension estimation temporal signals and images.
International Nuclear Information System (INIS)
Schildt, G.H.
1996-01-01
After an introduction into safety terms a fuzzy controller for safety related process control will be presented, especially for applications in the field of NPPs. One can show that the size of necessary rules is relatively small. Thus, there exists a real chance for verification and validation of software due to the fact that the whole software can be structured into standard fuzzy software (like fuzzyfication, inference algorithms, and defuzzyfication), real-time operating system software, and the contents of the rule base. Furthermore, there is an excellent advantage due to real-time behaviour, because program execution time can be much more planned than for conventional PID-controller software. Additionally, up to now special know-how does exist to prove stability of fuzzy controller. Hardware design has been done due to fundamental principles of safety technique like watch dog function, dynamization principle, and quiescent current principle
International Nuclear Information System (INIS)
Schildt, G.H.
1997-01-01
A fuzzy controller for safety related process control is presented for applications in the field of NPPs. The size of necessary rules is relatively small. Thus, there exists a real chance for verification and validation of software due to the fact that the whole software can be structured into standard fuzzy software (like fuzzyfication, inference algorithms, and defuzzyfication), real-time operating system software, and the contents of the rule base. Furthermore, there is an excellent advantage fuel to real-time behaviour, because program execution time is much more predictable than for conventional PID-controller software. Additionally, up to now special know-how does exist to prove stability of fuzzy controller. Hardware design has been done due to fundamental principles of safety technique like watch dog function, dynamization principles, and quiescent current principle. (author). 3 refs, 5 figs
Application of fuzzy logic to social choice theory
Mordeson, John N; Clark, Terry D
2015-01-01
Fuzzy social choice theory is useful for modeling the uncertainty and imprecision prevalent in social life yet it has been scarcely applied and studied in the social sciences. Filling this gap, Application of Fuzzy Logic to Social Choice Theory provides a comprehensive study of fuzzy social choice theory.The book explains the concept of a fuzzy maximal subset of a set of alternatives, fuzzy choice functions, the factorization of a fuzzy preference relation into the ""union"" (conorm) of a strict fuzzy relation and an indifference operator, fuzzy non-Arrowian results, fuzzy versions of Arrow's
Designing boosting ensemble of relational fuzzy systems.
Scherer, Rafał
2010-10-01
A method frequently used in classification systems for improving classification accuracy is to combine outputs of several classifiers. Among various types of classifiers, fuzzy ones are tempting because of using intelligible fuzzy if-then rules. In the paper we build an AdaBoost ensemble of relational neuro-fuzzy classifiers. Relational fuzzy systems bond input and output fuzzy linguistic values by a binary relation; thus, fuzzy rules have additional, comparing to traditional fuzzy systems, weights - elements of a fuzzy relation matrix. Thanks to this the system is better adjustable to data during learning. In the paper an ensemble of relational fuzzy systems is proposed. The problem is that such an ensemble contains separate rule bases which cannot be directly merged. As systems are separate, we cannot treat fuzzy rules coming from different systems as rules from the same (single) system. In the paper, the problem is addressed by a novel design of fuzzy systems constituting the ensemble, resulting in normalization of individual rule bases during learning. The method described in the paper is tested on several known benchmarks and compared with other machine learning solutions from the literature.
Anaesthesia monitoring using fuzzy logic.
Baig, Mirza Mansoor; Gholamhosseini, Hamid; Kouzani, Abbas; Harrison, Michael J
2011-10-01
Humans have a limited ability to accurately and continuously analyse large amount of data. In recent times, there has been a rapid growth in patient monitoring and medical data analysis using smart monitoring systems. Fuzzy logic-based expert systems, which can mimic human thought processes in complex circumstances, have indicated potential to improve clinicians' performance and accurately execute repetitive tasks to which humans are ill-suited. The main goal of this study is to develop a clinically useful diagnostic alarm system based on fuzzy logic for detecting critical events during anaesthesia administration. The proposed diagnostic alarm system called fuzzy logic monitoring system (FLMS) is presented. New diagnostic rules and membership functions (MFs) are developed. In addition, fuzzy inference system (FIS), adaptive neuro fuzzy inference system (ANFIS), and clustering techniques are explored for developing the FLMS' diagnostic modules. The performance of FLMS which is based on fuzzy logic expert diagnostic systems is validated through a series of off-line tests. The training and testing data set are selected randomly from 30 sets of patients' data. The accuracy of diagnoses generated by the FLMS was validated by comparing the diagnostic information with the one provided by an anaesthetist for each patient. Kappa-analysis was used for measuring the level of agreement between the anaesthetist's and FLMS's diagnoses. When detecting hypovolaemia, a substantial level of agreement was observed between FLMS and the human expert (the anaesthetist) during surgical procedures. The diagnostic alarm system FLMS demonstrated that evidence-based expert diagnostic systems can diagnose hypovolaemia, with a substantial degree of accuracy, in anaesthetized patients and could be useful in delivering decision support to anaesthetists.
Fuzzy Clustering - Principles, Methods and Examples
DEFF Research Database (Denmark)
Kroszynski, Uri; Zhou, Jianjun
1998-01-01
of the methods. The examples were solved by hand and served as a test bench for exploration of the MATLAB capabilities included in the Fuzzy Control Toolbox. The fuzzy clustering methods described include Fuzzy c-means (FCM), Fuzzy c-lines (FCL) and Fuzzy c-elliptotypes (FCE).......One of the most remarkable advances in the field of identification and control of systems -in particular mechanical systems- whose behaviour can not be described by means of the usual mathematical models, has been achieved by the application of methods of fuzzy theory.In the framework of a study...... about identification of "black-box" properties by analysis of system input/output data sets, we have prepared an introductory note on the principles and the most popular data classification methods used in fuzzy modeling. This introductory note also includes some examples that illustrate the use...
Fuzzy Stochastic Optimization Theory, Models and Applications
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...
Introduction to fuzzy logic using Matlab
Sivanandam, SN; Deepa, S N
2006-01-01
Fuzzy Logic, at present is a hot topic, among academicians as well various programmers. This book is provided to give a broad, in-depth overview of the field of Fuzzy Logic. The basic principles of Fuzzy Logic are discussed in detail with various solved examples. The different approaches and solutions to the problems given in the book are well balanced and pertinent to the Fuzzy Logic research projects. The applications of Fuzzy Logic are also dealt to make the readers understand the concept of Fuzzy Logic. The solutions to the problems are programmed using MATLAB 6.0 and the simulated results are given. The MATLAB Fuzzy Logic toolbox is provided for easy reference.
Learning and Tuning of Fuzzy Rules
Berenji, Hamid R.
1997-01-01
In this chapter, we review some of the current techniques for learning and tuning fuzzy rules. For clarity, we refer to the process of generating rules from data as the learning problem and distinguish it from tuning an already existing set of fuzzy rules. For learning, we touch on unsupervised learning techniques such as fuzzy c-means, fuzzy decision tree systems, fuzzy genetic algorithms, and linear fuzzy rules generation methods. For tuning, we discuss Jang's ANFIS architecture, Berenji-Khedkar's GARIC architecture and its extensions in GARIC-Q. We show that the hybrid techniques capable of learning and tuning fuzzy rules, such as CART-ANFIS, RNN-FLCS, and GARIC-RB, are desirable in development of a number of future intelligent systems.
Enhancement of SAR images using fuzzy shrinkage technique in ...
Indian Academy of Sciences (India)
Shivakumara Swamy Puranik Math
2017-08-03
Aug 3, 2017 ... fuzzy techniques, such as fuzzy clustering, fuzzy rule-based approach, and fuzzy integration approach. In the proposed work, the fuzzy membership is modified using Eq. (12). After the membership value is modified defuzzification process is applied with the help of Eq. (13). Denoised coefficients are.
Gateaux and Frechet Derivative in Intuitionistic Fuzzy Normed Linear spaces
Dinda, B.; Samanta, T. K.; Bera, U. K.
2010-01-01
Intuitionistic Fuzzy derivative, Intuitionistic Fuzzy Gateaux derivative, Intuitionistic Fuzzy Fr\\'{e}chet derivative are defined and a few of their properties are studied. The relation between Intuitionistic Fuzzy Gateaux derivative and Intuitionistic Fuzzy Fr\\'{e}chet derivative are emphasized.
Some Operators on Families of Fuzzy Languages and Their Monoids
Asveld, P.R.J.
We study the structure of partially ordered monoids generated by certain operators on families of fuzzy languages. These operators are induced by simple, well-known operations on fuzzy languages, like fuzzy homomorphism, fuzzy finite substitution and intersection with regular fuzzy languages. The
Fuzzy simulation in concurrent engineering
Kraslawski, A.; Nystrom, L.
1992-01-01
Concurrent engineering is becoming a very important practice in manufacturing. A problem in concurrent engineering is the uncertainty associated with the values of the input variables and operating conditions. The problem discussed in this paper concerns the simulation of processes where the raw materials and the operational parameters possess fuzzy characteristics. The processing of fuzzy input information is performed by the vertex method and the commercial simulation packages POLYMATH and GEMS. The examples are presented to illustrate the usefulness of the method in the simulation of chemical engineering processes.
Outdoor altitude stabilization of QuadRotor based on type-2 fuzzy and fuzzy PID
Wicaksono, H.; Yusuf, Y. G.; Kristanto, C.; Haryanto, L.
2017-11-01
This paper presents a design of altitude stabilization of QuadRotor based on type-2 fuzzy and fuzzy PID. This practical design is implemented outdoor. Barometric and sonar sensor were used in this experiment as an input for the controller YoHe. The throttle signal as a control input was provided by the controller to leveling QuadRotor in particular altitude and known well as altitude stabilization. The parameter of type-2 fuzzy and fuzzy PID was tuned in several heights to get the best control parameter for any height. Type-2 fuzzy produced better result than fuzzy PID but had a slow response in the beginning.
Complex Fuzzy Set-Valued Complex Fuzzy Measures and Their Properties
Ma, Shengquan; Li, Shenggang
2014-01-01
Let F*(K) be the set of all fuzzy complex numbers. In this paper some classical and measure-theoretical notions are extended to the case of complex fuzzy sets. They are fuzzy complex number-valued distance on F*(K), fuzzy complex number-valued measure on F*(K), and some related notions, such as null-additivity, pseudo-null-additivity, null-subtraction, pseudo-null-subtraction, autocontionuous from above, autocontionuous from below, and autocontinuity of the defined fuzzy complex number-valued measures. Properties of fuzzy complex number-valued measures are studied in detail. PMID:25093202
fuzzy control technique fuzzy control technique applied to modified
African Journals Online (AJOL)
eobe
Keywords: Keywords: fuzzy control, malaria, drug effectiveness, mosquitoes, equilibrium state, dynamic equation. 1. INTRODUCTION. INTRODUCTION. INTRODUCTION. Malaria is a vector borne infectious disease that has affected the human race since earliest times and an estimated 40% of the world's population lives in.
On Fuzzy -Contractive Mappings in Fuzzy Metric Spaces
Directory of Open Access Journals (Sweden)
Miheţ Dorel
2007-01-01
Full Text Available We answer into affirmative an open question raised by A. Razani in 2005. An essential role in our proofs is played by the separation axiom in the definition of a fuzzy metric space in the sense of George and Veeramani.
Fuzzy Querying: Issues and Perspectives..
Czech Academy of Sciences Publication Activity Database
Kacprzyk, J.; Pasi, G.; Vojtáš, Peter; Zadrozny, S.
2000-01-01
Roč. 36, č. 6 (2000), s. 605-616 ISSN 0023-5954 Institutional research plan: AV0Z1030915 Keywords : flexible querying * information retrieval * fuzzy databases Subject RIV: BA - General Mathematics http://dml.cz/handle/10338.dmlcz/135376
Fuzzy Weighted Average: Analytical Solution
van den Broek, P.M.; Noppen, J.A.R.
2009-01-01
An algorithm is presented for the computation of analytical expressions for the extremal values of the α-cuts of the fuzzy weighted average, for triangular or trapeizoidal weights and attributes. Also, an algorithm for the computation of the inverses of these expressions is given, providing exact
Morpho (?) phono (?) logical fuzzy edges
African Journals Online (AJOL)
Open Access DOWNLOAD FULL TEXT Subscription or Fee Access. Morpho (?) phono (?) logical fuzzy edges: The case of {-/}/{-/U/} semantic (?) contrast in Shona. K. G. Mkangwanwi. Abstract. (ZAMBEZIA: Journal of Humanities of the Univ of Zimbabwe, 2000 27(1): 47-54). Full Text: EMAIL FULL TEXT EMAIL FULL TEXT
Czech Academy of Sciences Publication Activity Database
Kroupa, Tomáš
2008-01-01
Roč. 159, č. 14 (2008), s. 1773-1787 ISSN 0165-0114 R&D Projects: GA MŠk 1M0572; GA AV ČR KJB100300502 Institutional research plan: CEZ:AV0Z10750506 Keywords : filter * prime filter * fuzzy class theory Subject RIV: BA - General Mathematics Impact factor: 1.833, year: 2008
Structural Completeness in Fuzzy Logics
Czech Academy of Sciences Publication Activity Database
Cintula, Petr; Metcalfe, G.
2009-01-01
Roč. 50, č. 2 (2009), s. 153-183 ISSN 0029-4527 R&D Projects: GA MŠk(CZ) 1M0545 Institutional research plan: CEZ:AV0Z10300504 Keywords : structral logics * fuzzy logics * structural completeness * admissible rules * primitive variety * residuated lattices Subject RIV: BA - General Mathematics
Fuzzy audit risk modeling algorithm
Directory of Open Access Journals (Sweden)
Zohreh Hajihaa
2011-07-01
Full Text Available Fuzzy logic has created suitable mathematics for making decisions in uncertain environments including professional judgments. One of the situations is to assess auditee risks. During recent years, risk based audit (RBA has been regarded as one of the main tools to fight against fraud. The main issue in RBA is to determine the overall audit risk an auditor accepts, which impact the efficiency of an audit. The primary objective of this research is to redesign the audit risk model (ARM proposed by auditing standards. The proposed model of this paper uses fuzzy inference systems (FIS based on the judgments of audit experts. The implementation of proposed fuzzy technique uses triangular fuzzy numbers to express the inputs and Mamdani method along with center of gravity are incorporated for defuzzification. The proposed model uses three FISs for audit, inherent and control risks, and there are five levels of linguistic variables for outputs. FISs include 25, 25 and 81 rules of if-then respectively and officials of Iranian audit experts confirm all the rules.
Fuzzy control system for a mobile robot
International Nuclear Information System (INIS)
Hai Quan Dai; Dalton, G.R.; Tulenko, J.
1992-01-01
Since the first fuzzy logic control system was proposed by Mamdani, many studies have been carried out on industrial process and real-time controls. The key problem for the application of fuzzy logic control is to find a suitable set of fuzzy control rules. Three common modes of deriving fuzzy control rules are often distinguished and mentioned: (1) expert experience and knowledge; (2) modeling operator control actions; and (3) modeling a process. In cases where an operator's skill is important, it is very useful to derive fuzzy control rules by modeling an operator's control actions. It is possible to model an operator's control behaviors in terms of fuzzy implications using the input-output data concerned with his/her control actions. The authors use the model obtained in this way as the basis for a fuzzy controller. The authors use a finite number of fuzzy or approximate control rules. To control a robot in a cluttered reactor environment, it is desirable to combine all the methods. In this paper, the authors describe a general algorithm for a mobile robot control system with fuzzy logic reasoning. They discuss the way that knowledge of fuzziness will be represented in this control system. They also describe a simulation program interface to the K2A Cybermation mobile robot to be used to demonstrate the control system
Fuzzy Evidence in Identification, Forecasting and Diagnosis
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...
Fuzzy neural approach for colon cancer prediction | Obi | Scientia ...
African Journals Online (AJOL)
fuzzy inference procedure. The proposed system which is self-learning and adaptive is able to handle the uncertainties often associated with the diagnosis and analysis of colon cancer. Keywords: Neural Network, Fuzzy logic, Neuro Fuzzy System, ...
International Nuclear Information System (INIS)
Peiffert, D.
2002-01-01
The loco regional control of cancers stays the absolute objective of the treatment. The thought of these days has allowed to evaluate the equipment and the practices, and to consider the developments to undertake in harmony with the investments of external radiotherapy. (N.C.)
Learning fuzzy logic control system
Lung, Leung Kam
1994-01-01
The performance of the Learning Fuzzy Logic Control System (LFLCS), developed in this thesis, has been evaluated. The Learning Fuzzy Logic Controller (LFLC) learns to control the motor by learning the set of teaching values that are generated by a classical PI controller. It is assumed that the classical PI controller is tuned to minimize the error of a position control system of the D.C. motor. The Learning Fuzzy Logic Controller developed in this thesis is a multi-input single-output network. Training of the Learning Fuzzy Logic Controller is implemented off-line. Upon completion of the training process (using Supervised Learning, and Unsupervised Learning), the LFLC replaces the classical PI controller. In this thesis, a closed loop position control system of a D.C. motor using the LFLC is implemented. The primary focus is on the learning capabilities of the Learning Fuzzy Logic Controller. The learning includes symbolic representation of the Input Linguistic Nodes set and Output Linguistic Notes set. In addition, we investigate the knowledge-based representation for the network. As part of the design process, we implement a digital computer simulation of the LFLCS. The computer simulation program is written in 'C' computer language, and it is implemented in DOS platform. The LFLCS, designed in this thesis, has been developed on a IBM compatible 486-DX2 66 computer. First, the performance of the Learning Fuzzy Logic Controller is evaluated by comparing the angular shaft position of the D.C. motor controlled by a conventional PI controller and that controlled by the LFLC. Second, the symbolic representation of the LFLC and the knowledge-based representation for the network are investigated by observing the parameters of the Fuzzy Logic membership functions and the links at each layer of the LFLC. While there are some limitations of application with this approach, the result of the simulation shows that the LFLC is able to control the angular shaft position of the
Anna Pantelia
2013-01-01
8 October 2013 - Rolex Director- General G. Marini in the ATLAS Control Room with CERN Director-General R. Heuer and ATLAS Collaboration Senior Physicist C. Rembser; visiting the ATLAS experimental cavern at LHC Point 1. Were also present from the Directorate: S. Lettow, Director for Administration and General Infrastructure; from the ATLAS Collaboration: Technische Universitaet Dortmund (DE) J. Jentzsch and SLAC National Accelerator Laboratory (US) G. Piacquadio.
Minimal solution for inconsistent singular fuzzy matrix equations
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M. Nikuie
2013-10-01
Full Text Available The fuzzy matrix equations $Ailde{X}=ilde{Y}$ is called a singular fuzzy matrix equations while the coefficients matrix of its equivalent crisp matrix equations be a singular matrix. The singular fuzzy matrix equations are divided into two parts: consistent singular matrix equations and inconsistent fuzzy matrix equations. In this paper, the inconsistent singular fuzzy matrix equations is studied and the effect of generalized inverses in finding minimal solution of an inconsistent singular fuzzy matrix equations are investigated.
Consolidity analysis for fully fuzzy functions, matrices, probability and statistics
Walaa Ibrahim Gabr
2015-01-01
The paper presents a comprehensive review of the know-how for developing the systems consolidity theory for modeling, analysis, optimization and design in fully fuzzy environment. The solving of systems consolidity theory included its development for handling new functions of different dimensionalities, fuzzy analytic geometry, fuzzy vector analysis, functions of fuzzy complex variables, ordinary differentiation of fuzzy functions and partial fraction of fuzzy polynomials. On the other hand, ...
Advanced inference in fuzzy systems by rule base compression
Gegov, Alexander; Gobalakrishnan, N.
2007-01-01
This paper describes a method for rule base compression of fuzzy systems. The method compresses a fuzzy system with an arbitrarily large number of rules into a smaller fuzzy system by removing the redundancy in the fuzzy rule base. As a result of this compression, the number of on-line operations during the fuzzy inference process is significantly reduced without compromising the solution. This rule base compression method outperforms significantly other known methods for fuzzy rule base redu...
Maranhão, Geraldo Neves De A.; Brito, Alaan Ubaiara; Leal, Anderson Marques; Fonseca, Jéssica Kelly Silva; Macêdo, Wilson Negrão
2015-01-01
In the present paper, a fuzzy controller applied to a Variable-Speed Drive (VSD) for use in Photovoltaic Pumping Systems (PVPS) is proposed. The fuzzy logic system (FLS) used is embedded in a microcontroller and corresponds to a proportional-derivative controller. A Light-Dependent Resistor (LDR) is used to measure, approximately, the irradiance incident on the PV array. Experimental tests are executed using an Arduino board. The experimental results show that the fuzzy controller is capable of operating the system continuously throughout the day and controlling the direct current (DC) voltage level in the VSD with a good performance. PMID:26402688
Fuzzy Multiple Criteria Decision Making Model with Fuzzy Time Weight Scheme
Chin-Yao Low; Sung-Nung Lin
2013-01-01
In this study, we purpose a common fuzzy multiple criteria decision making model. A brand new concept - fuzzy time weighted scheme is adopted for considering in the model to establish a fuzzy multiple criteria decision making with time weight (FMCDMTW) model. A real case of fuzzy multiple criteria decision making (FMCDM) problems to be considering in this study. The performance evaluation of auction websites based on all criteria proposed in related literature. Obviously, the problem under in...
Tahriri, Farzad; Dawal, Siti Zawiah Md; Taha, Zahari
2014-01-01
A new multiobjective dynamic fuzzy genetic algorithm is applied to solve a fuzzy mixed-model assembly line sequencing problem in which the primary goals are to minimize the total make-span and minimize the setup number simultaneously. Trapezoidal fuzzy numbers are implemented for variables such as operation and travelling time in order to generate results with higher accuracy and representative of real-case data. An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA) is ...
Eastwood, Phil; Dunne, Chris; Fowler, Stephen
2017-01-01
Pamphlet Day: A Political Protest Pamphlet and Zine Event focused around the occupation of Loughborough Public Library, Granby Street, Loughborough, LE11 3DZ, UK. ABSTRACT “Throughout the 20th Century artists have engaged provocatively with text, images and performance, publishing writings, pamphlets, and manifestos that challenge the status quo.” (1) Loughborough Echo, May 2017 https://www.loughboroughecho.net/whats-on/arts-culture-news/pamphlet-art-feature-events-13038989 A s...
An Ensemble of Adaptive Neuro-Fuzzy Kohonen Networks for Online Data Stream Fuzzy Clustering
Hu, Zhengbing; Bodyanskiy, Yevgeniy V.; Tyshchenko, Oleksii K.; Boiko, Olena O.
2016-01-01
A new approach to data stream clustering with the help of an ensemble of adaptive neuro-fuzzy systems is proposed. The proposed ensemble is formed with adaptive neuro-fuzzy self-organizing Kohonen maps in a parallel processing mode. A final result is chosen by the best neuro-fuzzy self-organizing Kohonen map.
Combinational reasoning of quantitative fuzzy topological relations for simple fuzzy regions.
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Bo Liu
Full Text Available 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.
Combinational Reasoning of Quantitative Fuzzy Topological Relations for Simple Fuzzy Regions
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
A numerical algorithm of fuzzy reliability
International Nuclear Information System (INIS)
Jiang Qimi; Chen, C.-H.
2003-01-01
In this paper, a computational model of fuzzy reliability focusing on solving the engineering problems with random general stress-fuzzy general strength is presented. The mathematical basis of this computational model is that the fuzzy probability can be computed with the computational method of conventional probability by use of a mathematical transition. Based on this computational model, a numerical algorithm is given which can be applied to compute the fuzzy reliability of mechanical components, sensors, electronic units, etc. This establishes a basis for the reliability analysis of systems consisting of components with fuzzy reliability. As an example, a case study about the fuzzy reliability analysis of a kind of sensor used in railway systems is provided to verify the logic of this algorithm. The computation results show that this algorithm fits the engineering experience
Optical Generation of Fuzzy-Based Rules
Gur, Eran; Mendlovic, David; Zalevsky, Zeev
2002-08-01
In the last third of the 20th century, fuzzy logic has risen from a mathematical concept to an applicable approach in soft computing. Today, fuzzy logic is used in control systems for various applications, such as washing machines, train-brake systems, automobile automatic gear, and so forth. The approach of optical implementation of fuzzy inferencing was given by the authors in previous papers, giving an extra emphasis to applications with two dominant inputs. In this paper the authors introduce a real-time optical rule generator for the dual-input fuzzy-inference engine. The paper briefly goes over the dual-input optical implementation of fuzzy-logic inferencing. Then, the concept of constructing a set of rules from given data is discussed. Next, the authors show ways to implement this procedure optically. The discussion is accompanied by an example that illustrates the transformation from raw data into fuzzy set rules.
[Ambulatory vascular exercise training in Dortmund].
Koepchen, J; Roth, H J
2002-02-01
Peripheral arterial occlusive disease is chronic and progressive. One of the reasons is lack of movement. The pain-free walking distance can be increased permanently through walking exercises described in the guidelines of the German Society for Vascular Training. Form and order of the training are described. The pleasure in movement and preservation of the own activity increases the motivation of the participants.
Simulasi Kecepatan Kendaraan Dengan Menggunakan Logika Fuzzy
Lukas, Samuel; Aribowo, Arnold; Tjia, Yogih Suharta
2009-01-01
Artificial intelligence has been implemented widely. Many of household products are designed based on artificial intellegence concept. One of them is fuzzy logic system. This paper describes on how a fuzzy logic system can also be implemented in controling the speed of a car in the road. The fuzzy inference system was designed according to Tsukamoto inferencing method and for the defuzzyfication method is used weighted average method. There are three inputs for the system. The are distance b...
Simulasi Kecepatan Kendaraan dengan Menggunakan Logika Fuzzy
Lukas, Samuel; Aribowo, Arnold; Tjia, Yogih Suharta
2008-01-01
Artificial intelligence has been implemented widely. Many of household products are designed based on artificial intellegence concept. One of them is fuzzy logic system. This paper describes on how a fuzzy logic system can also be implemented in controling the speed of a car in the road. The fuzzy inference system was designed according to Tsukamoto inferencing method and for the defuzzyfication method is used weighted average method. There are three inputs for the system. The are distance b...
Fuzzy multiple linear regression: A computational approach
Juang, C. H.; Huang, X. H.; Fleming, J. W.
1992-01-01
This paper presents a new computational approach for performing fuzzy regression. In contrast to Bardossy's approach, the new approach, while dealing with fuzzy variables, closely follows the conventional regression technique. In this approach, treatment of fuzzy input is more 'computational' than 'symbolic.' The following sections first outline the formulation of the new approach, then deal with the implementation and computational scheme, and this is followed by examples to illustrate the new procedure.
Fuzzy Law and the Boundaries of Secularism
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W Menski
2010-12-01
Full Text Available The author delivered a speech at a Religare Conference. Showing his distaste for fuzzy law, he argues that "moderate secularism" is not merely another fuzzy concept, but it is "super-fuzzy", and that lawyers claiming to love certainty "have a tendency to sit in judgment over matters and even pre-judge things they know little about, including legal pluralism" leading to much irritation.
Fuzzy logic controller for weaning neonates from mechanical ventilation.
Hatzakis, G E; Davis, G M
2002-01-01
Weaning from mechanical ventilation is the gradual detachment from any ventilatory support till normal spontaneous breathing can be fully resumed. To date, we have developed a fuzzy logic controller for weaning COPD adults using pressure support ventilation (PS). However, adults and newborns differ in the pathophysiology of lung disease. We therefore used our fuzzy logic-based weaning platform to develop modularized components for weaning newborns with lung disease. Our controller uses the heart rate (HR), respiratory rate (RR), tidal volume (VT) and oxygen saturation (SaO2) and their trends deltaHR/deltat, deltaVT/deltat and deltaSaO2/deltat to evaluate, respectively, the Current and Trend weaning status of the newborn. Through appropriate fuzzification of these vital signs, Current and Trend weaning status can quantitatively determine the increase/decrease in the synchronized intermittent mandatory ventilation (SIMV) setting. The post-operative weaning courses of 10 newborns, 82+/-162 days old, were assessed at 2-hour intervals for 68+/-39 days. The SIMV levels, proposed by our algorithm, were matched to those levels actually applied. For 60% of the time both values coincided. For the remaining 40%, our algorithm suggested lower SIMV support than what was applied. The Area Under the Curve for integrated ventilatory support over time was 1203+/-846 for standard ventilatory strategies and 1152+/-802 for fuzzy controller. This suggests that the algorithm, approximates the actual weaning progression, and may advocate a more aggressive strategy. Moreover, the core of the fuzzy controller facilitates adaptation for body size and diversified disease patterns and sets the premises as an infant-weaning tool.
APPLICATION OF FUZZY LOGIC TOOLBOX FOR MODELLING FUZZY LOGIC CONTROLLERS
Olesiak, Krzysztof
2017-01-01
Computer technology, which has been developing very fast in the recent years, can be also fruitfully applied in teaching. For example, the software package Matlab is highly useful in teaching students at Bachelor Programs of Electrical Engineering and Automatics and Robotics. Fuzzy Logic Toolbox of the Matlab package can be used for designing and modelling controllers. Thanks to a large number of pre-defined elements available in the libraries, it is possible to create even highly complicated...
Word Similarity From Dictionaries: Inferring Fuzzy Measures From Fuzzy Graphs
Directory of Open Access Journals (Sweden)
Torra
2008-01-01
Full Text Available 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.
Fuzzy control of small servo motors
Maor, Ron; Jani, Yashvant
1993-01-01
To explore the benefits of fuzzy logic and understand the differences between the classical control methods and fuzzy control methods, the Togai InfraLogic applications engineering staff developed and implemented a motor control system for small servo motors. The motor assembly for testing the fuzzy and conventional controllers consist of servo motor RA13M and an encoder with a range of 4096 counts. An interface card was designed and fabricated to interface the motor assembly and encoder to an IBM PC. The fuzzy logic based motor controller was developed using the TILShell and Fuzzy C Development System on an IBM PC. A Proportional-Derivative (PD) type conventional controller was also developed and implemented in the IBM PC to compare the performance with the fuzzy controller. Test cases were defined to include step inputs of 90 and 180 degrees rotation, sine and square wave profiles in 5 to 20 hertz frequency range, as well as ramp inputs. In this paper we describe our approach to develop a fuzzy as well as PH controller, provide details of hardware set-up and test cases, and discuss the performance results. In comparison, the fuzzy logic based controller handles the non-linearities of the motor assembly very well and provides excellent control over a broad range of parameters. Fuzzy technology, as indicated by our results, possesses inherent adaptive features.
Fuzzy neural network theory and application
Liu, Puyin
2004-01-01
This book systematically synthesizes research achievements in the field of fuzzy neural networks in recent years. It also provides a comprehensive presentation of the developments in fuzzy neural networks, with regard to theory as well as their application to system modeling and image restoration. Special emphasis is placed on the fundamental concepts and architecture analysis of fuzzy neural networks. The book is unique in treating all kinds of fuzzy neural networks and their learning algorithms and universal approximations, and employing simulation examples which are carefully designed to he
DESIGN POWER SYSTEM STABILIZER MENGGUNAKAN FUZZY LOGIC
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Ivo Salvador Soares Miranda
2014-10-01
Full Text Available Stabiltas merupakan kemampuan sistem untuk menjaga kondisi operasi seimbang dan kembali kekondisi operasi normal ketika terjadi gangguan. Penerapan power system stabilizer pada sistem tenaga mampu memberikan sinyal respon yang cepat atas berbagai kondisi gangguan dan mengupayakan tidak meluasnya jangkauan gangguan. Dalam mendesign power system stabilizer menggunakan robust fuzzy logic, menggunakan satu sinyal input yaitu kecepatan deviasi rotor. Hasil simulasinya dibandingkan dengan metode fuzzy logic dan kovensional. Studi simulasi menunjukan, design power system stabilizer menggunakan robust fuzzy logic memiliki nilai sinyal peak time dan settling time relatif kecil dibandingkan dengan metode fuzzy logic dan konvensional.
Fuzzy set classifier for waste classification tracking
International Nuclear Information System (INIS)
Gavel, D.T.
1992-01-01
We have developed an expert system based on fuzzy logic theory to fuse the data from multiple sensors and make classification decisions for objects in a waste reprocessing stream. Fuzzy set theory has been applied in decision and control applications with some success, particularly by the Japanese. We have found that the fuzzy logic system is rather easy to design and train, a feature that can cut development costs considerably. With proper training, the classification accuracy is quite high. We performed several tests sorting radioactive test samples using a gamma spectrometer to compare fuzzy logic to more conventional sorting schemes
Fuzzy logic control and optimization system
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.
A fuzzy classifier system for process control
Karr, C. L.; Phillips, J. C.
1994-01-01
A fuzzy classifier system that discovers rules for controlling a mathematical model of a pH titration system was developed by researchers at the U.S. Bureau of Mines (USBM). Fuzzy classifier systems successfully combine the strengths of learning classifier systems and fuzzy logic controllers. Learning classifier systems resemble familiar production rule-based systems, but they represent their IF-THEN rules by strings of characters rather than in the traditional linguistic terms. Fuzzy logic is a tool that allows for the incorporation of abstract concepts into rule based-systems, thereby allowing the rules to resemble the familiar 'rules-of-thumb' commonly used by humans when solving difficult process control and reasoning problems. Like learning classifier systems, fuzzy classifier systems employ a genetic algorithm to explore and sample new rules for manipulating the problem environment. Like fuzzy logic controllers, fuzzy classifier systems encapsulate knowledge in the form of production rules. The results presented in this paper demonstrate the ability of fuzzy classifier systems to generate a fuzzy logic-based process control system.
A computationally efficient fuzzy control s
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Abdel Badie Sharkawy
2013-12-01
Full Text Available This paper develops a decentralized fuzzy control scheme for MIMO nonlinear second order systems with application to robot manipulators via a combination of genetic algorithms (GAs and fuzzy systems. The controller for each degree of freedom (DOF consists of a feedforward fuzzy torque computing system and a feedback fuzzy PD system. The feedforward fuzzy system is trained and optimized off-line using GAs, whereas not only the parameters but also the structure of the fuzzy system is optimized. The feedback fuzzy PD system, on the other hand, is used to keep the closed-loop stable. The rule base consists of only four rules per each DOF. Furthermore, the fuzzy feedback system is decentralized and simplified leading to a computationally efficient control scheme. The proposed control scheme has the following advantages: (1 it needs no exact dynamics of the system and the computation is time-saving because of the simple structure of the fuzzy systems and (2 the controller is robust against various parameters and payload uncertainties. The computational complexity of the proposed control scheme has been analyzed and compared with previous works. Computer simulations show that this controller is effective in achieving the control goals.
Fuzzy sets, rough sets, multisets and clustering
Dahlbom, Anders; Narukawa, Yasuo
2017-01-01
This book is dedicated to Prof. Sadaaki Miyamoto and presents cutting-edge papers in some of the areas in which he contributed. Bringing together contributions by leading researchers in the field, it concretely addresses clustering, multisets, rough sets and fuzzy sets, as well as their applications in areas such as decision-making. The book is divided in four parts, the first of which focuses on clustering and classification. The second part puts the spotlight on multisets, bags, fuzzy bags and other fuzzy extensions, while the third deals with rough sets. Rounding out the coverage, the last part explores fuzzy sets and decision-making.
Characterization of convergence in fuzzy topological spaces
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E. Lowen
1985-01-01
Full Text Available In a fuzzy topology on a set X, the limit of a prefilter (i.e. a filter in the lattice [0,1]X is calculated from the fuzzy closure. In this way convergence is derived from a fuzzy topology. In our paper we start with any rule lim which to any prefilter on X assigns, a function lim∈[0,1]X. We give necessary and sufficient conditions for the function →lim in order that it can be derived from a fuzzy topology.
A method for solving fully fuzzy linear system with trapezoidal fuzzy numbers
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A. Kumar
2010-03-01
Full Text Available Different methods have been proposed for finding the non-negative solution of fully fuzzy linear system (FFLS i.e. fuzzy linear system with fuzzy coefficients involving fuzzy variables. To the best of our knowledge, there is no method in the literature for finding the non-negative solution of a FFLS without any restriction on the coefficient matrix. In this paper a new computational method is proposed to solve FFLS without any restriction on the coefficient matrix by representing all the parameters as trapezoidal fuzzy numbers.
Fuzzy polynucleotide spaces and metrics.
Nieto, Juan J; Torres, A; Georgiou, D N; Karakasidis, T E
2006-04-01
The study of genetic sequences is of great importance in biology and medicine. Mathematics is playing an important role in the study of genetic sequences and, generally, in bioinformatics. In this paper, we extend the work concerning the Fuzzy Polynucleotide Space (FPS) introduced in Torres, A., Nieto, J.J., 2003. The fuzzy polynucleotide Space: Basic properties. Bioinformatics 19(5); 587-592 and Nieto, J.J., Torres, A., Vazquez-Trasande, M.M. 2003. A metric space to study differences between polynucleotides. Appl. Math. Lett. 27:1289-1294: by studying distances between nucleotides and some complete genomes using several metrics. We also present new results concerning the notions of similarity, difference and equality between polynucleotides. The results are encouraging since they demonstrate how the notions of distance and similarity between polynucleotides in the FPS can be employed in the analysis of genetic material.
Komal
2018-02-23
Nowadays power consumption is increasing day-by-day. To fulfill failure free power requirement, planning and implementation of an effective and reliable power management system is essential. Phasor measurement unit(PMU) is one of the key device in wide area measurement and control systems. The reliable performance of PMU assures failure free power supply for any power system. So, the purpose of the present study is to analyse the reliability of a PMU used for controllability and observability of power systems utilizing available uncertain data. In this paper, a generalized fuzzy lambda-tau (GFLT) technique has been proposed for this purpose. In GFLT, system components' uncertain failure and repair rates are fuzzified using fuzzy numbers having different shapes such as triangular, normal, cauchy, sharp gamma and trapezoidal. To select a suitable fuzzy number for quantifying data uncertainty, system experts' opinion have been considered. The GFLT technique applies fault tree, lambda-tau method, fuzzified data using different membership functions, alpha-cut based fuzzy arithmetic operations to compute some important reliability indices. Furthermore, in this study ranking of critical components of the system using RAM-Index and sensitivity analysis have also been performed. The developed technique may be helpful to improve system performance significantly and can be applied to analyse fuzzy reliability of other engineering systems. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
Intuitionistic H-fuzzy relations
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Kul Hur
2005-10-01
Full Text Available We introduce the category IRel(H consisting of intuitionistic fuzzy relational spaces on sets and we study structures of the category IRel(H in the viewpoint of the topological universe introduced by Nel. Thus we show that IRel(H satisfies all the conditions of a topological universe over Set except the terminal separator property and IRel(H is cartesian closed over Set.
Directory of Open Access Journals (Sweden)
Dhruba Das
2015-04-01
Full Text Available In this article, based on Zadeh’s extension principle we have apply the parametric programming approach to construct the membership functions of the performance measures when the interarrival time and the service time are fuzzy numbers based on the Baruah’s Randomness- Fuzziness Consistency Principle. The Randomness-Fuzziness Consistency Principle leads to defining a normal law of fuzziness using two different laws of randomness. In this article, two fuzzy queues FM/M/1 and M/FM/1 has been studied and constructed their membership functions of the system characteristics based on the aforesaid principle. The former represents a queue with fuzzy exponential arrivals and exponential service rate while the latter represents a queue with exponential arrival rate and fuzzy exponential service rate.
Chen, Shyi-Ming; Hsin, Wen-Chyuan
2015-07-01
In this paper, we propose a new weighted fuzzy interpolative reasoning method for sparse fuzzy rule-based systems based on the slopes of fuzzy sets. We also propose a particle swarm optimization (PSO)-based weights-learning algorithm to automatically learn the optimal weights of the antecedent variables of fuzzy rules for weighted fuzzy interpolative reasoning. We apply the proposed weighted fuzzy interpolative reasoning method using the proposed PSO-based weights-learning algorithm to deal with the computer activity prediction problem, the multivariate regression problems, and the time series prediction problems. The experimental results show that the proposed weighted fuzzy interpolative reasoning method using the proposed PSO-based weights-learning algorithm outperforms the existing methods for dealing with the computer activity prediction problem, the multivariate regression problems, and the time series prediction problems.
Fuzzy logic based robotic controller
Attia, F.; Upadhyaya, M.
1994-01-01
Existing Proportional-Integral-Derivative (PID) robotic controllers rely on an inverse kinematic model to convert user-specified cartesian trajectory coordinates to joint variables. These joints experience friction, stiction, and gear backlash effects. Due to lack of proper linearization of these effects, modern control theory based on state space methods cannot provide adequate control for robotic systems. In the presence of loads, the dynamic behavior of robotic systems is complex and nonlinear, especially where mathematical modeling is evaluated for real-time operators. Fuzzy Logic Control is a fast emerging alternative to conventional control systems in situations where it may not be feasible to formulate an analytical model of the complex system. Fuzzy logic techniques track a user-defined trajectory without having the host computer to explicitly solve the nonlinear inverse kinematic equations. The goal is to provide a rule-based approach, which is closer to human reasoning. The approach used expresses end-point error, location of manipulator joints, and proximity to obstacles as fuzzy variables. The resulting decisions are based upon linguistic and non-numerical information. This paper presents a solution to the conventional robot controller which is independent of computationally intensive kinematic equations. Computer simulation results of this approach as obtained from software implementation are also discussed.
van Lith, Pascal; van Lith, P.F.; Betlem, Bernardus H.L.; Roffel, B.
2002-01-01
Hybrid fuzzy-first principles models can be a good alternative if a complete physical model is difficult to derive. These hybrid models consist of a framework of dynamic mass and energy balances, supplemented by fuzzy submodels describing additional equations, such as mass transformation and
Lith, Pascal F. van; Betlem, Ben H.L.; Roffel, Brian
2002-01-01
Hybrid fuzzy-first principles models can be a good alternative if a complete physical model is difficult to derive. These hybrid models consist of a framework of dynamic mass and energy balances, supplemented by fuzzy submodels describing additional equations, such as mass transformation and
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.
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.
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.
A NEW APPROACH ON SHORTEST PATH IN FUZZY ENVIRONMENT
A. Nagoorgani; A. Mumtaj Begam
2010-01-01
This paper introduces a new type of fuzzy shortest path network problem using triangular fuzzy number. To find the smallest edge by the fuzzy distance using graded mean integration representation of generalized fuzzy number for every node. Thus the optimum shortest path for the given problem is obtained.
Solution of a System of Linear Equations with Fuzzy Numbers
Czech Academy of Sciences Publication Activity Database
Horčík, Rostislav
2008-01-01
Roč. 159, č. 14 (2008), s. 1788-1810 ISSN 0165-0114 R&D Projects: GA AV ČR KJB100300502 Institutional research plan: CEZ:AV0Z10300504 Keywords : fuzzy number * fuzzy interval * interval analysis * fuzzy arithmetic * fuzzy class theory * united solution set Subject RIV: BA - General Mathematics Impact factor: 1.833, year: 2008
The ternary-encoded fuzzy-neural networks
Semenova, Olena; Semenov, Andriy; Koval, Kostyantyn; Galka, Andriy
2012-01-01
When combining fuzzy logic and neural networks it is possible to get a hybrid system that can process uncertain values and can be trained. Fuzzy logic elements can be regarded as fuzzy-neural networks. In order to present a set of fuzzy values the ternary encoding is used.
Approximation properties of the neuro-fuzzy minimum function
Gottschling, Andreas; Kreuter, Christof
1999-01-01
The integration of fuzzy logic systems and neural networks in data driven nonlinear modeling applications has generally been limited to functions based upon the multiplicative fuzzy implication rule for theoretical and computational reasons. We derive a universal approximation result for the minimum fuzzy implication rule as well as a differentiable substitute function that allows fast optimization and function approximation with neuro-fuzzy networks.
On topological structures of fuzzy parametrized soft sets.
Atmaca, Serkan; Zorlutuna, Idris
2014-01-01
We introduce the topological structure of fuzzy parametrized soft sets and fuzzy parametrized soft mappings. We define the notion of quasi-coincidence for fuzzy parametrized soft sets and investigated its basic properties. We study the closure, interior, base, continuity, and compactness and properties of these concepts in fuzzy parametrized soft topological spaces.
Consolidity analysis for fully fuzzy functions, matrices, probability and statistics
Directory of Open Access Journals (Sweden)
Walaa Ibrahim Gabr
2015-03-01
Full Text Available The paper presents a comprehensive review of the know-how for developing the systems consolidity theory for modeling, analysis, optimization and design in fully fuzzy environment. The solving of systems consolidity theory included its development for handling new functions of different dimensionalities, fuzzy analytic geometry, fuzzy vector analysis, functions of fuzzy complex variables, ordinary differentiation of fuzzy functions and partial fraction of fuzzy polynomials. On the other hand, the handling of fuzzy matrices covered determinants of fuzzy matrices, the eigenvalues of fuzzy matrices, and solving least-squares fuzzy linear equations. The approach demonstrated to be also applicable in a systematic way in handling new fuzzy probabilistic and statistical problems. This included extending the conventional probabilistic and statistical analysis for handling fuzzy random data. Application also covered the consolidity of fuzzy optimization problems. Various numerical examples solved have demonstrated that the new consolidity concept is highly effective in solving in a compact form the propagation of fuzziness in linear, nonlinear, multivariable and dynamic problems with different types of complexities. Finally, it is demonstrated that the implementation of the suggested fuzzy mathematics can be easily embedded within normal mathematics through building special fuzzy functions library inside the computational Matlab Toolbox or using other similar software languages.
A method for unbalanced transportation problems in fuzzy ...
Indian Academy of Sciences (India)
Saad & Abbas (2003) discussed an algorithm for solving the transportation problems in fuzzy environment. Das & Baruah (2007) proposed vogel's approximation method to find the fuzzy initial basic feasible solution of fuzzy transportation problems in which all the parameters are represented by triangular fuzzy numbers.
Computing the eigenvalues and eigenvectors of a fuzzy matrix
Directory of Open Access Journals (Sweden)
A. Kumar
2012-08-01
Full Text Available Computation of fuzzy eigenvalues and fuzzy eigenvectors of a fuzzy matrix is a challenging problem. Determining the maximal and minimal symmetric solution can help to find the eigenvalues. So, we try to compute these eigenvalues by determining the maximal and minimal symmetric solution of the fully fuzzy linear system $widetilde{A}widetilde{X}= widetilde{lambda} widetilde{X}.$
Aggregation Operator Based Fuzzy Pattern Classifier Design
DEFF Research Database (Denmark)
Mönks, Uwe; Larsen, Henrik Legind; Lohweg, Volker
2009-01-01
This paper presents a novel modular fuzzy pattern classifier design framework for intelligent automation systems, developed on the base of the established Modified Fuzzy Pattern Classifier (MFPC) and allows designing novel classifier models which are hardware-efficiently implementable. The perfor...
A physical analogy to fuzzy clustering
DEFF Research Database (Denmark)
Jantzen, Jan
2004-01-01
This tutorial paper provides an interpretation of the membership assignment in the fuzzy clustering algorithm fuzzy c-means. The membership of a data point to several clusters is shown to be analogous to the gravitational forces between bodies of mass. This provides an alternative way to explain...
On the Power of Fuzzy Markup Language
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...
IMPLEMENTATION OF FUZZY LOGIC BASED TEMPERATURE ...
African Journals Online (AJOL)
The “center of gravity” or the “centroid” method of defuzzification was chosen, since it weighs the effect of each input variable towards the calculation of the output [5]. Input fuzzy sets and rules are converted into an output fuzzy set, and then into a crisp output for controlling the steam control valve. All the rules that have any ...
A Fuzzy Neural Tree for Possibilistic Reliability
Ciftcioglu, O.
2008-01-01
An innovative neural fuzzy system is considered for possibilistic reliability using a neural tree structure with nodes of neuronal type. The total tree structure works effectively as a fuzzy logic system where the possibility theory plays important role with Gaussian possibility distribution at the
Bounded Rationality of Generalized Abstract Fuzzy Economies
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Lei Wang
2014-01-01
Full Text Available By using a nonlinear scalarization technique, the bounded rationality model M for generalized abstract fuzzy economies in finite continuous spaces is established. Furthermore, by using the model M, some new theorems for structural stability and robustness to (λ,ϵ-equilibria of generalized abstract fuzzy economies are proved.
Fuzziness and randomness in an optimization framework
International Nuclear Information System (INIS)
Luhandjula, M.K.
1994-03-01
This paper presents a semi-infinite approach for linear programming in the presence of fuzzy random variable coefficients. As a byproduct a way for dealing with optimization problems including both fuzzy and random data is obtained. Numerical examples are provided for the sake of illustration. (author). 13 refs
Homeopathic drug selection using Intuitionistic fuzzy sets.
Kharal, Athar
2009-01-01
Using intuitionistic fuzzy set theory, Sanchez's approach to medical diagnosis has been applied to the problem of selection of single remedy from homeopathic repertorization. Two types of Intuitionistic Fuzzy Relations (IFRs) and three types of selection indices are discussed. I also propose a new repertory exploiting the benefits of soft-intelligence.
Mathematical Fuzzy Logic - State of Art 2001
Czech Academy of Sciences Publication Activity Database
Hájek, Petr
2003-01-01
Roč. 24, - (2003), s. 71-89 ISSN 0103-9059. [WOLLIC'2001. Brasília, 31.07.2001-03.08.2001] R&D Projects: GA MŠk LN00A056 Keywords : fuzzy logic * many valued logic * basic fuzzy logic BL Subject RIV: BA - General Mathematics http://www.mat.unb.br/~matcont/24_4.pdf
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.
Fuzzy t-filters and their Properties
Czech Academy of Sciences Publication Activity Database
Víta, Martin
2014-01-01
Roč. 247, 16 July (2014), s. 127-134 ISSN 0165-0114 R&D Projects: GA ČR GAP202/10/1826 Institutional support: RVO:67985807 Keywords : non-classical logics * algebra * fuzzy t-filters * t-filters * fuzzy filters * residuated lattices Subject RIV: BA - General Mathematics Impact factor: 1.986, year: 2014
FUZZY SLIDING MODE CONTROLLER FOR DOUBLY FED ...
African Journals Online (AJOL)
2010-12-31
Dec 31, 2010 ... Hence it is found to be very effective in controlling electric drives systems. Large torque chattering at steady state may be considered as the main drawback for such a control scheme [6]. One way to improve sliding mode controller performance is to combine it with Fuzzy Logic (FL) to form a Fuzzy Sliding ...
Contraction theorems in fuzzy metric space
International Nuclear Information System (INIS)
Farnoosh, R.; Aghajani, A.; Azhdari, P.
2009-01-01
In this paper, the results on fuzzy contractive mapping proposed by Dorel Mihet will be proved for B-contraction and C-contraction in the case of George and Veeramani fuzzy metric space. The existence of fixed point with weaker conditions will be proved; that is, instead of the convergence of subsequence, p-convergence of subsequence is used.
Fuzzy Query Processing Using Clustering Techniques.
Kamel, M.; And Others
1990-01-01
Discusses the problem of processing fuzzy queries in databases and information retrieval systems and presents a prototype of a fuzzy query processing system for databases that is based on data clustering and uses Pascal programing language. Clustering schemes are explained, and the system architecture that uses natural language is described. (14…
Parallel fuzzy connected image segmentation on GPU
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...
Fuzzy Logic and Arithmetical Hierarchy III
Czech Academy of Sciences Publication Activity Database
Hájek, Petr
2001-01-01
Roč. 68, č. 1 (2001), s. 129-142 ISSN 0039-3215 R&D Projects: GA AV ČR IAA1030004 Institutional research plan: AV0Z1030915 Keywords : fuzzy logic * basic fuzzy logic * Lukasiewicz logic * Godel logic * product logic * arithmetical hierarchy Subject RIV: BA - General Mathematics
Modeling Research Project Risks with Fuzzy Maps
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…
On Preferential sylow fuzzy subgroups | Makamba | Quaestiones ...
African Journals Online (AJOL)
In this paper, for a prime p, we propose some plausible denitions for the notion of Sylow fuzzy p-subgroup of a nite group. We derive a number of results for nite fuzzy groups using one of the proposed denitions. We also discuss some of the relationships between various proposed denitions for suitability, including the crisp ...
Mezey, Paul G
2014-09-16
Conspectus Just as complete molecules have no boundaries and have "fuzzy" electron density clouds approaching zero density exponentially at large distances from the nearest nucleus, a physically justified choice for electron density fragments exhibits similar behavior. Whereas fuzzy electron densities, just as any fuzzy object, such as a thicker cloud on a foggy day, do not lend themselves to easy visualization, one may partially overcome this by using isocontours. Whereas a faithful representation of the complete fuzzy density would need infinitely many such isocontours, nevertheless, by choosing a selected few, one can still obtain a limited pictorial representation. Clearly, such images are of limited value, and one better relies on more complete mathematical representations, using, for example, density matrices of fuzzy fragment densities. A fuzzy density fragmentation can be obtained in an exactly additive way, using the output from any of the common quantum chemical computational techniques, such as Hartree-Fock, MP2, and various density functional approaches. Such "fuzzy" electron density fragments properly represented have proven to be useful in a rather wide range of applications, for example, (a) using them as additive building blocks leading to efficient linear scaling macromolecular quantum chemistry computational techniques, (b) the study of quantum chemical functional groups, (c) using approximate fuzzy fragment information as allowed by the holographic electron density theorem, (d) the study of correlations between local shape and activity, including through-bond and through-space components of interactions between parts of molecules and relations between local molecular shape and substituent effects, (e) using them as tools of density matrix extrapolation in conformational changes, (f) physically valid averaging and statistical distribution of several local electron densities of common stoichiometry, useful in electron density databank mining, for
Transportation optimization with fuzzy trapezoidal numbers based on possibility theory.
He, Dayi; Li, Ran; Huang, Qi; Lei, Ping
2014-01-01
In this paper, a parametric method is introduced to solve fuzzy transportation problem. Considering that parameters of transportation problem have uncertainties, this paper develops a generalized fuzzy transportation problem with fuzzy supply, demand and cost. For simplicity, these parameters are assumed to be fuzzy trapezoidal numbers. Based on possibility theory and consistent with decision-makers' subjectiveness and practical requirements, the fuzzy transportation problem is transformed to a crisp linear transportation problem by defuzzifying fuzzy constraints and objectives with application of fractile and modality approach. Finally, a numerical example is provided to exemplify the application of fuzzy transportation programming and to verify the validity of the proposed methods.
Fuzzy modeling and control theory and applications
Matía, Fernando; Jiménez, Emilio
2014-01-01
Much work on fuzzy control, covering research, development and applications, has been developed in Europe since the 90's. Nevertheless, the existing books in the field are compilations of articles without interconnection or logical structure or they express the personal point of view of the author. This book compiles the developments of researchers with demonstrated experience in the field of fuzzy control following a logic structure and a unified the style. The first chapters of the book are dedicated to the introduction of the main fuzzy logic techniques, where the following chapters focus on concrete applications. This book is supported by the EUSFLAT and CEA-IFAC societies, which include a large number of researchers in the field of fuzzy logic and control. The central topic of the book, Fuzzy Control, is one of the main research and development lines covered by these associations.
Artificial Hydrocarbon Networks Fuzzy Inference System
Directory of Open Access Journals (Sweden)
Hiram Ponce
2013-01-01
Full Text Available This paper presents a novel fuzzy inference model based on artificial hydrocarbon networks, a computational algorithm for modeling problems based on chemical hydrocarbon compounds. In particular, the proposed fuzzy-molecular inference model (FIM-model uses molecular units of information to partition the output space in the defuzzification step. Moreover, these molecules are linguistic units that can be partially understandable due to the organized structure of the topology and metadata parameters involved in artificial hydrocarbon networks. In addition, a position controller for a direct current (DC motor was implemented using the proposed FIM-model in type-1 and type-2 fuzzy inference systems. Experimental results demonstrate that the fuzzy-molecular inference model can be applied as an alternative of type-2 Mamdani’s fuzzy control systems because the set of molecular units can deal with dynamic uncertainties mostly present in real-world control applications.
Markowitz portfolio optimization model employing fuzzy measure
Ramli, Suhailywati; Jaaman, Saiful Hafizah
2017-04-01
Markowitz in 1952 introduced the mean-variance methodology for the portfolio selection problems. His pioneering research has shaped the portfolio risk-return model and become one of the most important research fields in modern finance. This paper extends the classical Markowitz's mean-variance portfolio selection model applying the fuzzy measure to determine the risk and return. In this paper, we apply the original mean-variance model as a benchmark, fuzzy mean-variance model with fuzzy return and the model with return are modeled by specific types of fuzzy number for comparison. The model with fuzzy approach gives better performance as compared to the mean-variance approach. The numerical examples are included to illustrate these models by employing Malaysian share market data.
Flows in networks under fuzzy conditions
Bozhenyuk, Alexander Vitalievich; Kacprzyk, Janusz; Rozenberg, Igor Naymovich
2017-01-01
This book offers a comprehensive introduction to fuzzy methods for solving flow tasks in both transportation and networks. It analyzes the problems of minimum cost and maximum flow finding with fuzzy nonzero lower flow bounds, and describes solutions to minimum cost flow finding in a network with fuzzy arc capacities and transmission costs. After a concise introduction to flow theory and tasks, the book analyzes two important problems. The first is related to determining the maximum volume for cargo transportation in the presence of uncertain network parameters, such as environmental changes, measurement errors and repair work on the roads. These parameters are represented here as fuzzy triangular, trapezoidal numbers and intervals. The second problem concerns static and dynamic flow finding in networks under fuzzy conditions, and an effective method that takes into account the network’s transit parameters is presented here. All in all, the book provides readers with a practical reference guide to state-of-...
Optimization of Neuro-Fuzzy System
Directory of Open Access Journals (Sweden)
M. Sarosa
2007-05-01
Full Text Available Neuro-fuzzy system has been shown to provide a good performance on chromosome classification but does not offer a simple method to obtain the accurate parameter values required to yield the best recognition rate. This paper presents a neuro-fuzzy system where its parameters can be automatically adjusted using genetic algorithms. The approach combines the advantages of fuzzy logic theory, neural networks, and genetic algorithms. The structure consists of a four layer feed-forward neural network that uses a GBell membership function as the output function. The proposed methodology has been applied and tested on banded chromosome classification from the Copenhagen Chromosome Database. Simulation result showed that the proposed neuro-fuzzy system optimized by genetic algorithms offers advantages in setting the parameter values, improves the recognition rate significantly and decreases the training/testing time which makes genetic neuro-fuzzy system suitable for chromosome classification.
Molecular processors: from qubits to fuzzy logic.
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.
Integrated development environment for fuzzy logic applications
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.
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.
SISTEM PENGENDALI LAMPU LALULINTAS BERBASIS LOGIKA FUZZY
Directory of Open Access Journals (Sweden)
Emmanuel Agung Nugroho
2017-04-01
Full Text Available Fuzzy Logic Control sebagai salah satu aplikasi kecerdasan buatan telah mampu memberikan kontribusi untuk menyelesaikan masalah traffic system di jalan raya. Salah satu implementasi sistem fuzzy logic control adalah untuk mengendalikan lampu indikator lalulintas. System lampu lalulintas yang dikendalikan dengan menggunakan fuzzy logic control sangat efektif untuk menguraikan permasalahan kemacetan yang terlalu lama karena menunggu waktu lampu hijau menyala. Untuk merealisasikan fuzzy logic control pada sistem pengendalian lampu lalu lintas maka memerlukan tools yaitu sensor photoelectric pada setiap ruas persimpangan dan mikrokontroller Arduino Mega 2560 untuk mengimplementasikan sistem fuzzy kedalam bahasa program yang bisa diterima oleh hardware yaitu lampu lalulintas. Pada penelitian ini menggunakan simulasi 4 buah persilangan jalan sebagai model dengan jumlah kendaraan yang dimodelkan terbanyak adalah 25 kendaraan dengan waktu paling lama 60 detik. Pada hasil pengujian telah dapat membuktikan perubahan jumlah kendaraan pada setiap persimpangan menentukan lama waktu lampu hijau menyala pada persimpangan terpadat kendaraan tersebut.
Fuzzy statistical decision-making theory and applications
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...
Chaira, Tamalika
2014-06-01
In this paper automatic leukocyte segmentation in pathological blood cell images is proposed using intuitionistic fuzzy and interval Type II fuzzy set theory. This is done to count different types of leukocytes for disease detection. Also, the segmentation should be accurate so that the shape of the leukocytes is preserved. So, intuitionistic fuzzy set and interval Type II fuzzy set that consider either more number of uncertainties or a different type of uncertainty as compared to fuzzy set theory are used in this work. As the images are considered fuzzy due to imprecise gray levels, advanced fuzzy set theories may be expected to give better result. A modified Cauchy distribution is used to find the membership function. In intuitionistic fuzzy method, non-membership values are obtained using Yager's intuitionistic fuzzy generator. Optimal threshold is obtained by minimizing intuitionistic fuzzy divergence. In interval type II fuzzy set, a new membership function is generated that takes into account the two levels in Type II fuzzy set using probabilistic T co norm. Optimal threshold is selected by minimizing a proposed Type II fuzzy divergence. Though fuzzy techniques were applied earlier but these methods failed to threshold multiple leukocytes in images. Experimental results show that both interval Type II fuzzy and intuitionistic fuzzy methods perform better than the existing non-fuzzy/fuzzy methods but interval Type II fuzzy thresholding method performs little bit better than intuitionistic fuzzy method. Segmented leukocytes in the proposed interval Type II fuzzy method are observed to be distinct and clear. Copyright © 2014 Elsevier Ltd. All rights reserved.
East West Fuzzy colloquium 2000. 8. Zittau Fuzzy colloquium. Proceedings
Energy Technology Data Exchange (ETDEWEB)
Wagenknecht, M.; Chaker, N.; Hampel, R. [comps.
2000-07-01
The Zittau Colloquium is organized annually with the objective to stimulate contacts between scientists in academic research, industrial development and university teaching from Eastern and Western European countries and from other parts of the world. A further aim of the colloquium is the exchange of information about the state-of-the-art in the field of Fuzzy Logic basic investigation and application in connection with other theories, for example Neuronal Networks. Therefore, we want to stimulate the discussion about proposals for common national, bilateral and international supported projects to incite research, teaching, as well as mobility of students and teachers. (orig.)
About Projections of Solutions for Fuzzy Differential Equations
Directory of Open Access Journals (Sweden)
Moiseis S. Cecconello
2013-01-01
Full Text Available In this paper we propose the concept of fuzzy projections on subspaces of , obtained from Zadeh's extension of canonical projections in , and we study some of the main properties of such projections. Furthermore, we will review some properties of fuzzy projection solution of fuzzy differential equations. As we will see, the concept of fuzzy projection can be interesting for the graphical representation of fuzzy solutions.
The Programming Language for Fuzzy Control and It's Application
古川, 万寿夫; 三浦, 健史; 松田, 孝史
1994-01-01
We designed the programming language for fuzzy control using micro processor. This language permits to describe if-then rule into the program for fuzzy control. This language is easy to understand for fuzzy control engineer. We developed the Fuzzy to C translator which translates this programming language into C language. The program generated by the translator is compiled by C compiler to apply to target for fuzzy control.
Designing PID-Fuzzy Controller for Pendubot System
Directory of Open Access Journals (Sweden)
Ho Trong Nguyen
2017-12-01
Full Text Available In the paper, authors analize dynamic equation of a pendubot system. Familiar kinds of controller – PID, fuzzy controllers – are concerned. Then, a structure of PID-FUZZY is presented. The comparison of three kinds of controllers – PID, fuzzy and PID-FUZZY shows the better response of system under PID-FUZZY controller. Then, the experiments on the real model also prove the better stabilization of the hybrid controller which is combined between linear and intelligent controller.
Fuzzy methods and design; Fuzzy shuho to sekkei
Energy Technology Data Exchange (ETDEWEB)
Furuta, H. [Kwansei Gakuin Univ., Hyogo (Japan)
1996-03-05
This paper explains the application of the fuzzy theory to a design. A rational decision in design with only an objective logic requires conditions such that a set of selectable alternative plans and the results of executing them are known, and that a rule or a sequential relation exists to decide the order of preference of the alternative plans. In a case where the optimum anti-earthquake design was applied, for example, the seismic motion, subsoil and properties of materials or the like used to be treated stochastically and statistically as being of random nature. However, elements of uncertainty are actually involved other than the randomness, in consideration of cost effectiveness, safety and such. In the problems of anti-earthquake design by the fuzzy theory, the restrictive conditions are stipulated with a membership function respectively, such that the design earthquake motion is in a range larger than the maximum motion, and that the stress or displacement is each in the range smaller than the allowable stress or displacement of members; in addition, the weight is expressed to be the minimum as the objective function. 9 refs., 1 fig.
Uncertainty analysis of flexible rotors considering fuzzy parameters and fuzzy-random parameters
Directory of Open Access Journals (Sweden)
Fabian Andres Lara-Molina
Full Text Available Abstract The components of flexible rotors are subjected to uncertainties. The main sources of uncertainties include the variation of mechanical properties. This contribution aims at analyzing the dynamics of flexible rotors under uncertain parameters modeled as fuzzy and fuzzy random variables. The uncertainty analysis encompasses the modeling of uncertain parameters and the numerical simulation of the corresponding flexible rotor model by using an approach based on fuzzy dynamic analysis. The numerical simulation is accomplished by mapping the fuzzy parameters of the deterministic flexible rotor model. Thereby, the flexible rotor is modeled by using both the Fuzzy Finite Element Method and the Fuzzy Stochastic Finite Element Method. Numerical simulations illustrate the methodology conveyed in terms of orbits and frequency response functions subject to uncertain parameters.
Epsilon-insensitive fuzzy c-regression models: introduction to epsilon-insensitive fuzzy modeling.
Leski, Jacek M
2004-02-01
This paper introduces a new epsilon-insensitive fuzzy c-regression models (epsilonFCRM), that can be used in fuzzy modeling. To fit these regression models to real data, a weighted epsilon-insensitive loss function is used. The proposed method make it possible to exclude an intrinsic inconsistency of fuzzy modeling, where crisp loss function (usually quadratic) is used to match real data and the fuzzy model. The epsilon-insensitive fuzzy modeling is based on human thinking and learning. This method allows easy control of generalization ability and outliers robustness. This approach leads to c simultaneous quadratic programming problems with bound constraints and one linear equality constraint. To solve this problem, computationally efficient numerical method, called incremental learning, is proposed. Finally, examples are given to demonstrate the validity of introduced approach to fuzzy modeling.
Intuitionistic Fuzzy Time Series Forecasting Model Based on Intuitionistic Fuzzy Reasoning
Directory of Open Access Journals (Sweden)
Ya’nan Wang
2016-01-01
Full Text Available Fuzzy sets theory cannot describe the data comprehensively, which has greatly limited the objectivity of fuzzy time series in uncertain data forecasting. In this regard, an intuitionistic fuzzy time series forecasting model is built. In the new model, a fuzzy clustering algorithm is used to divide the universe of discourse into unequal intervals, and a more objective technique for ascertaining the membership function and nonmembership function of the intuitionistic fuzzy set is proposed. On these bases, forecast rules based on intuitionistic fuzzy approximate reasoning are established. At last, contrast experiments on the enrollments of the University of Alabama and the Taiwan Stock Exchange Capitalization Weighted Stock Index are carried out. The results show that the new model has a clear advantage of improving the forecast accuracy.
Fuzzy Logic Based Automatic Door Control System
Directory of Open Access Journals (Sweden)
Harun SUMBUL
2017-12-01
Full Text Available In this paper, fuzzy logic based an automatic door control system is designed to provide for heat energy savings. The heat energy loss usually occurs in where outomotic doors are used. Designed fuzzy logic system’s Input statuses (WS: Walking Speed and DD: Distance Door and the output status (DOS: Door Opening Speed is determined. According to these cases, rule base (25 rules is created; the rules are processed by a fuzzy logic and by appyled to control of an automatic door. An interface program is prepared by using Matlab Graphical User Interface (GUI programming language and some sample results are checked on Matlab using fuzzy logic toolbox. Designed fuzzy logic controller is tested at different speed cases and the results are plotted. As a result; in this study, we have obtained very good results in control of an automatic door with fuzzy logic. The results of analyses have indicated that the controls performed with fuzzy logic provided heat energy savings, less heat energy loss and reliable, consistent controls and that are feasible to in real.
Sputtering properties of tungsten 'fuzzy' surfaces
International Nuclear Information System (INIS)
Nishijima, D.; Baldwin, M.J.; Doerner, R.P.; Yu, J.H.
2011-01-01
Sputtering yields of He-induced W 'fuzzy' surfaces bombarded by Ar have been measured in the linear divertor plasma simulator PISCES-B. It is found that the sputtering yield of a fuzzy surface, Y fuzzy , decreases with increasing fuzzy layer thickness, L, and saturates at ∼10% of that of a smooth surface, Y smooth , at L > 1 μm. The reduction in the sputtering yield is suspected to be due mainly to the porous structure of fuzz, since the ratio, Y fuzzy /Y smooth follows (1 - p fuzz ), where p fuzz is the fuzz porosity. Further, Y fuzzy /Y smooth is observed to increase with incident ion energy, E i . This may be explained by an energy dependent change in the angular distribution of sputtered W atoms, since at lower E i , the angular distribution is observed to become more butterfly-shaped. That is, a larger fraction of sputtered W atoms can line-of-sight deposit/stick onto neighboring fuzz nanostructures for lower E i butterfly distributions, resulting in lower ratio of Y fuzzy /Y smooth .
Development of a new fuzzy exposure model
International Nuclear Information System (INIS)
Vasconcelos, Wagner Eustaquio de; Lira, Carlos Alberto Brayner de Oliveira; Texeira, Marcello Goulart
2007-01-01
The main topic of this study is the development of an exposure fuzzy model to evaluate the exposure of inhabitants in an area containing uranium, which present a high natural background. In this work, a fuzzy model was created, based on some of the following main factors: activity concentration of uranium, physiological factors and characteristic customs of the exposed individuals. An inference block was created to evaluate some factors of radiation exposure. For this, AHP-fuzzy technique (Analytic Hierarchic Process) was used and its application was demonstrated for a subjected population to the radiation of the natural uranium. The Mandami type fuzzy model was also created from the opinion of specialists. The Monte Carlo method was used to generate a statistics of input data and the daily average exposure served as comparison parameter between the three techniques. The output fuzzy sets were expressed in form of linguistic variables, such as high, medium and low. In the qualitative analysis, the obtained results were satisfactory when translating the opinion of the specialists. In the quantitative analysis, the obtained values are part of the same fuzzy set as the values found in literature. The global results suggest that this type of fuzzy model is highly promising for analysis of exposure to ionizing radiation. (author)
Towards the future of fuzzy logic
Trillas, Enric; Kacprzyk, Janusz
2015-01-01
This book provides readers with a snapshot of the state-of-the art in fuzzy logic. Throughout the chapters, key theories developed in the last fifty years as well as important applications to practical problems are presented and discussed from different perspectives, as the authors hail from different disciplines and therefore use fuzzy logic for different purposes. The book aims at showing how fuzzy logic has evolved since the first theory formulation by Lotfi A. Zadeh in his seminal paper on Fuzzy Sets in 1965. Fuzzy theories and implementation grew at an impressive speed and achieved significant results, especially on the applicative side. The study of fuzzy logic and its practice spread all over the world, from Europe to Asia, America and Oceania. The editors believe that, thanks to the drive of young researchers, fuzzy logic will be able to face the challenging goals posed by computing with words. New frontiers of knowledge are waiting to be explored. In order to motivate young people to engage in the ...
Automatic approach to deriving fuzzy slope positions
Zhu, Liang-Jun; Zhu, A.-Xing; Qin, Cheng-Zhi; Liu, Jun-Zhi
2018-03-01
Fuzzy characterization of slope positions is important for geographic modeling. Most of the existing fuzzy classification-based methods for fuzzy characterization require extensive user intervention in data preparation and parameter setting, which is tedious and time-consuming. This paper presents an automatic approach to overcoming these limitations in the prototype-based inference method for deriving fuzzy membership value (or similarity) to slope positions. The key contribution is a procedure for finding the typical locations and setting the fuzzy inference parameters for each slope position type. Instead of being determined totally by users in the prototype-based inference method, in the proposed approach the typical locations and fuzzy inference parameters for each slope position type are automatically determined by a rule set based on prior domain knowledge and the frequency distributions of topographic attributes. Furthermore, the preparation of topographic attributes (e.g., slope gradient, curvature, and relative position index) is automated, so the proposed automatic approach has only one necessary input, i.e., the gridded digital elevation model of the study area. All compute-intensive algorithms in the proposed approach were speeded up by parallel computing. Two study cases were provided to demonstrate that this approach can properly, conveniently and quickly derive the fuzzy slope positions.
Design of supply chain in fuzzy environment
Rao, Kandukuri Narayana; Subbaiah, Kambagowni Venkata; Singh, Ganja Veera Pratap
2013-05-01
Nowadays, customer expectations are increasing and organizations are prone to operate in an uncertain environment. Under this uncertain environment, the ultimate success of the firm depends on its ability to integrate business processes among supply chain partners. Supply chain management emphasizes cross-functional links to improve the competitive strategy of organizations. Now, companies are moving from decoupled decision processes towards more integrated design and control of their components to achieve the strategic fit. In this paper, a new approach is developed to design a multi-echelon, multi-facility, and multi-product supply chain in fuzzy environment. In fuzzy environment, mixed integer programming problem is formulated through fuzzy goal programming in strategic level with supply chain cost and volume flexibility as fuzzy goals. These fuzzy goals are aggregated using minimum operator. In tactical level, continuous review policy for controlling raw material inventories in supplier echelon and controlling finished product inventories in plant as well as distribution center echelon is considered as fuzzy goals. A non-linear programming model is formulated through fuzzy goal programming using minimum operator in the tactical level. The proposed approach is illustrated with a numerical example.
Fuzzy Object Skeletonization: Theory, Algorithms, and Applications.
K Saha, Punam; Jin, Dakai; Liu, Yinxiao; E Christensen, Gary; Chen, Cheng
2017-08-10
Skeletonization offers a compact representation of an object while preserving important topological and geometrical features. Literature on skeletonization of binary objects is quite mature. However, challenges involved with skeletonization of fuzzy objects are mostly unanswered. This paper presents a new theory and algorithm of skeletonization for fuzzy objects, evaluates its performance, and demonstrates its applications. A formulation of fuzzy grassfire propagation is introduced; its relationships with fuzzy distance functions, level sets, and geodesics are discussed; and new results are presented. A notion of collision-impact of fire-fronts at skeletal points is introduced, and its role in filtering noisy skeletal points is demonstrated. A fuzzy object skeletonization algorithm is developed using new ideas of surface- and curve-skeletal voxels, digital collision-impact, and continuity of skeletal surfaces. A skeletal noise pruning algorithm is presented using branch-level significance. Accuracy and robustness of the new algorithm are examined on computer-generated phantoms and micro- and conventional CT imaging of trabecular bone specimens. An application of fuzzy object skeletonization to compute structure-width at a low image resolution is demonstrated, and its ability to predict bone strength is examined. Finally, the performance of the new fuzzy object skeletonization algorithm is compared with two binary object skeletonization methods.
CONSTRUCTION OF FUZZY C CONTROL CHARTS BASED ON FUZZY RULE METHOD
ŞENTÜRK, Sevil
2017-01-01
A control chart is a tool thatis used for representing and monitoring the process. Also control chartdetected process shifts and abnormal conditions in a process. In a processmonitored the c control charts, due to the uncertainty of the attribute data, ccontrol chart may not applicable for the process since it’s required certaininformation. Many papers of fuzzy control charts with type-1 fuzzy sets basedon transformation techniques are exist in literature. This paper constructedthe fuzzy c co...
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)
A new fuzzy Monte Carlo method for solving SLAE with ergodic fuzzy Markov chains
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Maryam Gharehdaghi
2015-05-01
Full Text Available In this paper we introduce a new fuzzy Monte Carlo method for solving system of linear algebraic equations (SLAE over the possibility theory and max-min algebra. To solve the SLAE, we first define a fuzzy estimator and prove that this is an unbiased estimator of the solution. To prove unbiasedness, we apply the ergodic fuzzy Markov chains. This new approach works even for cases with coefficients matrix with a norm greater than one.
Fuzzy clustering of web documents using equivalence relations and fuzzy hierarchical clustering
kumar, Satendra; kathuria, Mamta; Gupta, Alok Kumar; Rani, Monika
2014-01-01
The conventional clustering algorithms have difficulties in handling the challenges posed by the collection of natural data which is often vague and uncertain. Fuzzy clustering methods have the potential to manage such situations efficiently. Fuzzy clustering method is offered to construct clusters with uncertain boundaries and allows that one object belongs to one or more clusters with some membership degree. In this paper, an algorithm and experimental results are presented for fuzzy cluste...
Fuzziness and fuzzy modelling in Bulgaria's energy policy decision-making dilemma
Energy Technology Data Exchange (ETDEWEB)
Wang Xingquan [GREGOR, University Paris I, Pantheon-Sorbonne, Paris (France)]. E-mail: wangxingquan@gmail.com
2006-07-01
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)
Enric Trillas a passion for fuzzy sets : a collection of recent works on fuzzy logic
Verdegay, Jose; Esteva, Francesc
2015-01-01
This book presents a comprehensive collection of the latest and most significant research advances and applications in the field of fuzzy logic. It covers fuzzy structures, rules, operations and mathematical formalisms, as well as important applications of fuzzy logic in a number of fields, like decision-making, environmental prediction and prevention, communication, controls and many others. Dedicated to Enric Trillas in recognition of his pioneering research in the field, the book also includes a foreword by Lotfi A. Zadeh and an outlook on the future of fuzzy logic.
Directory of Open Access Journals (Sweden)
Fajar Ibnu Tufeil
2009-06-01
Full Text Available Model fuzzy memiliki kemampuan untuk menjelaskan secara linguistik suatu sistem yang terlalu kompleks. Aturan-aturan dalam model fuzzy pada umumnya dibangun berdasarkan keahlian manusia dan pengetahuan heuristik dari sistem yang dimodelkan. Teknik ini selanjutnya dikembangkan menjadi teknik yang dapat mengidentifikasi aturan-aturan dari suatu basis data yang telah dikelompokkan berdasarkan persamaan strukturnya. Dalam hal ini metode pengelompokan fuzzy berfungsi untuk mencari kelompok-kelompok data. Informasi yang dihasilkan dari metode pengelompokan ini, yaitu informasi tentang pusat kelompok, digunakan untuk membentuk aturan-aturan dalam sistem penalaran fuzzy. Dalam skripsi ini dibahas mengenai penerapan fuzzy infereance system dengan metode pengelompokan fuzzy subtractive clustering, yaitu untuk membentuk sistem penalaran fuzzy dengan menggunakan model fuzzy Takagi-Sugeno orde satu. Selanjutnya, metode pengelompokan fuzzy subtractive clustering diterapkan dalam memodelkan masalah dibidang pemasaran, yaitu untuk memprediksi permintaan pasar terhadap suatu produk susu. Aplikasi ini dibangun menggunakan Borland Delphi 6.0. Dari hasil pengujian diperoleh tingkat error prediksi terkecil yaitu dengan Error Average 0.08%.
Shah, Mazlina Muzafar; Wahab, Abdul Fatah
2017-08-01
Epilepsy disease occurs because of there is a temporary electrical disturbance in a group of brain cells (nurons). The recording of electrical signals come from the human brain which can be collected from the scalp of the head is called Electroencephalography (EEG). EEG then considered in digital format and in fuzzy form makes it a fuzzy digital space data form. The purpose of research is to identify the area (curve and surface) in fuzzy digital space affected by inside epilepsy seizure in epileptic patient's brain. The main focus for this research is to generalize fuzzy topological digital space, definition and basic operation also the properties by using digital fuzzy set and the operations. By using fuzzy digital space, the theory of digital fuzzy spline can be introduced to replace grid data that has been use previously to get better result. As a result, the flat of EEG can be fuzzy topological digital space and this type of data can be use to interpolate the digital fuzzy spline.
Characterization of the Equilibrium Strategy of Fuzzy Bimatrix Games Based on L-R Fuzzy Variables
Directory of Open Access Journals (Sweden)
Cun-lin Li
2012-01-01
variable. In this paper, we generalized Maeda’s model to the non-symmetrical environment. In other words, we investigated the fuzzy bimatrix games based on nonsymmetrical L-R fuzzy variables. Then the pseudoinverse of a nonconstant monotone function was given and the concept of crisp parametric bimatrix games was introduced. At last, the existence condition of Nash equilibrium strategies of the fuzzy bimatrix games is proposed and (weak Pareto equilibrium of the fuzzy bimatrix games was obtained through the Nash equilibrium of the crisp parametric bimatrix.
Tahriri, Farzad; Dawal, Siti Zawiah Md; Taha, Zahari
2014-01-01
A new multiobjective dynamic fuzzy genetic algorithm is applied to solve a fuzzy mixed-model assembly line sequencing problem in which the primary goals are to minimize the total make-span and minimize the setup number simultaneously. Trapezoidal fuzzy numbers are implemented for variables such as operation and travelling time in order to generate results with higher accuracy and representative of real-case data. An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA) is proposed in order to solve this optimization model. In establishing the FAGA, five dynamic fuzzy parameter controllers are devised in which fuzzy expert experience controller (FEEC) is integrated with automatic learning dynamic fuzzy controller (ALDFC) technique. The enhanced algorithm dynamically adjusts the population size, number of generations, tournament candidate, crossover rate, and mutation rate compared with using fixed control parameters. The main idea is to improve the performance and effectiveness of existing GAs by dynamic adjustment and control of the five parameters. Verification and validation of the dynamic fuzzy GA are carried out by developing test-beds and testing using a multiobjective fuzzy mixed production assembly line sequencing optimization problem. The simulation results highlight that the performance and efficacy of the proposed novel optimization algorithm are more efficient than the performance of the standard genetic algorithm in mixed assembly line sequencing model.
Directory of Open Access Journals (Sweden)
Farzad Tahriri
2014-01-01
Full Text Available A new multiobjective dynamic fuzzy genetic algorithm is applied to solve a fuzzy mixed-model assembly line sequencing problem in which the primary goals are to minimize the total make-span and minimize the setup number simultaneously. Trapezoidal fuzzy numbers are implemented for variables such as operation and travelling time in order to generate results with higher accuracy and representative of real-case data. An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA is proposed in order to solve this optimization model. In establishing the FAGA, five dynamic fuzzy parameter controllers are devised in which fuzzy expert experience controller (FEEC is integrated with automatic learning dynamic fuzzy controller (ALDFC technique. The enhanced algorithm dynamically adjusts the population size, number of generations, tournament candidate, crossover rate, and mutation rate compared with using fixed control parameters. The main idea is to improve the performance and effectiveness of existing GAs by dynamic adjustment and control of the five parameters. Verification and validation of the dynamic fuzzy GA are carried out by developing test-beds and testing using a multiobjective fuzzy mixed production assembly line sequencing optimization problem. The simulation results highlight that the performance and efficacy of the proposed novel optimization algorithm are more efficient than the performance of the standard genetic algorithm in mixed assembly line sequencing model.
Tahriri, Farzad; Dawal, Siti Zawiah Md; Taha, Zahari
2014-01-01
A new multiobjective dynamic fuzzy genetic algorithm is applied to solve a fuzzy mixed-model assembly line sequencing problem in which the primary goals are to minimize the total make-span and minimize the setup number simultaneously. Trapezoidal fuzzy numbers are implemented for variables such as operation and travelling time in order to generate results with higher accuracy and representative of real-case data. An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA) is proposed in order to solve this optimization model. In establishing the FAGA, five dynamic fuzzy parameter controllers are devised in which fuzzy expert experience controller (FEEC) is integrated with automatic learning dynamic fuzzy controller (ALDFC) technique. The enhanced algorithm dynamically adjusts the population size, number of generations, tournament candidate, crossover rate, and mutation rate compared with using fixed control parameters. The main idea is to improve the performance and effectiveness of existing GAs by dynamic adjustment and control of the five parameters. Verification and validation of the dynamic fuzzy GA are carried out by developing test-beds and testing using a multiobjective fuzzy mixed production assembly line sequencing optimization problem. The simulation results highlight that the performance and efficacy of the proposed novel optimization algorithm are more efficient than the performance of the standard genetic algorithm in mixed assembly line sequencing model. PMID:24982962
Construction of Fuzzy Sets and Applying Aggregation Operators for Fuzzy Queries
DEFF Research Database (Denmark)
Hudec, Miroslav; Sudzina, Frantisek
Flexible query conditions could use linguistic terms described by fuzzy sets. The question is how to properly construct fuzzy sets for each linguistic term and apply an adequate aggregation function. For construction of fuzzy sets, the lowest value, the highest value of attribute...... and the distribution of data inside its domain are used. The logarithmic transformation of domains appears to be suitable. This way leads to a balanced distribution of tuples over fuzzy sets. In addition, users’ opinions about linguistic terms as well as current content in database are merged. The second investigated...
Automatic histogram threshold using fuzzy measures.
Vieira Lopes, Nuno; Mogadouro do Couto, Pedro A; Bustince, Humberto; Melo-Pinto, Pedro
2010-01-01
In this paper, an automatic histogram threshold approach based on a fuzziness measure is presented. This work is an improvement of an existing method. Using fuzzy logic concepts, the problems involved in finding the minimum of a criterion function are avoided. Similarity between gray levels is the key to find an optimal threshold. Two initial regions of gray levels, located at the boundaries of the histogram, are defined. Then, using an index of fuzziness, a similarity process is started to find the threshold point. A significant contrast between objects and background is assumed. Previous histogram equalization is used in small contrast images. No prior knowledge of the image is required.
Fuzzy image processing and applications with Matlab
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,
Using fuzzy arithmetic in containment event trees
International Nuclear Information System (INIS)
Rivera, S.S.; Baron, Jorge H.
2000-01-01
The use of fuzzy arithmetic is proposed for the evaluation of containment event trees. Concepts such as improbable, very improbable, and so on, which are subjective by nature, are represented by fuzzy numbers. The quantitative evaluation of containment event trees is based on the extension principle, by which operations on real numbers are extended to operations on fuzzy numbers. Expert knowledge is considered as state of the base variable with a normal distribution, which is considered to represent the membership function. Finally, this paper presents results of an example calculation of a containment event tree for the CAREM-25 nuclear power plant, presently under detailed design stage at Argentina. (author)
Fuzzy clustering analysis of microarray data.
Han, Lixin; Zeng, Xiaoqin; Yan, Hong
2008-10-01
Fuzzy clustering is a useful tool for identifying relevant subsets of microarray data. This paper proposes a fuzzy clustering method for microarray data analysis. An advantage of the method is that it used a combination of the fuzzy c-means and the principal component analysis to identify the groups of genes that show similar expression patterns. It allows a gene to belong to more than a gene expression pattern with different membership grades. The method is suitable for the analysis of large amounts of noisy microarray data.
Fuzzy stability and synchronization of hyperchaos systems
International Nuclear Information System (INIS)
Wang Junwei; Xiong Xiaohua; Zhao Meichun; Zhang Yanbin
2008-01-01
This paper studies stability and synchronization of hyperchaos systems via a fuzzy-model-based control design methodology. First, we utilize a Takagi-Sugeno fuzzy model to represent a hyperchaos system. Second, we design fuzzy-model-based controllers for stability and synchronization of the system, based on so-called 'parallel distributed compensation (PDC)'. Third, we reduce a question of stabilizing and synchronizing hyperchaos systems to linear matrix inequalities (LMI) so that convex programming techniques can solve these LMIs efficiently. Finally, the generalized Lorenz hyperchaos system is employed to illustrate the effectiveness of our designing controller
Adaptive Fuzzy Systems in Computational Intelligence
Berenji, Hamid R.
1996-01-01
In recent years, the interest in computational intelligence techniques, which currently includes neural networks, fuzzy systems, and evolutionary programming, has grown significantly and a number of their applications have been developed in the government and industry. In future, an essential element in these systems will be fuzzy systems that can learn from experience by using neural network in refining their performances. The GARIC architecture, introduced earlier, is an example of a fuzzy reinforcement learning system which has been applied in several control domains such as cart-pole balancing, simulation of to Space Shuttle orbital operations, and tether control. A number of examples from GARIC's applications in these domains will be demonstrated.
Variable fuzzy control for heat pump operation
International Nuclear Information System (INIS)
Cho, Eun Jun; Hwang, Yoon Jei; Ha, Man Yeong; Chang, Se Dong
2011-01-01
The aim of this study is to determine the electronic expansion valve (EEV) opening using a fuzzy table when the superheating of a variable capacity air conditioning system is controlled via fuzzy control. Optimum opening of EEV is determined by applying superheat control method, where factors including superheat error and superheat gradient, as well as compressor capacity, indoor temperature, outdoor temperature, and indoor fan rpm, are considered. This control algorithm uses a fuzzy table wherein values are changed to optimal values according to operating conditions, enabling fast and stable control
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.
Data-Based Fuzzy TOPSIS for Alternative Ranking
Directory of Open Access Journals (Sweden)
Victor Utomo
2016-01-01
Full Text Available Technique for Order Preference by Similarity (TOPSIS solves multi-criteria decision making (MCDM by ranking the alternatives. When the attributes are not deterministic, a Fuzzy TOPSIS method is applied. The traditional fuzzy TOPSIS depends on decision makers to determine alternative’s value which considered subjective. A new method named data-based fuzzy TOPSIS proposed to diminish the dependency to decision maker. The proposed algorithm use data to determine alternative’s values objectively. Subtractive Clustering (SC and Fuzzy C-Mean (FCM selected to transform crisp value data to fuzzy value data. Some modification applied to SC and FCM to obtain fuzzy triangular value needed by fuzzy TOPSIS. Keyword : Index Terms—Decision support systems, fuzzy TOPSIS, fuzzy C-mean, subtractive clustering
Saravanan, Vijayakumar; Lakshmi, P T V
2014-09-01
The path to personalized medicine demands the use of new and customized biopharmaceutical products containing modified proteins. Hence, assessment of these products for allergenicity becomes mandatory before they are introduced as therapeutics. Despite the availability of different tools to predict the allergenicity of proteins, it remains challenging to predict the allergens and nonallergens, when they share significant sequence similarity with known nonallergens and allergens, respectively. Hence, we propose "FuzzyApp," a novel fuzzy rule based system to evaluate the quality of the query protein to be an allergen. It measures the allergenicity of the protein based on the fuzzy IF-THEN rules derived from five different modules. On various datasets, FuzzyApp outperformed other existing methods and retained balance between sensitivity and specificity, with positive Mathew's correlation coefficient. The high specificity of allergen-like putative nonallergens (APN) revealed the FuzzyApp's capability in distinguishing the APN from allergens. In addition, the error analysis and whole proteome dataset analysis suggest the efficiency and consistency of the proposed method. Further, FuzzyApp predicted the Tropomyosin from various allergenic and nonallergenic sources accurately. The web service created allows batch sequence submission, and outputs the result as readable sentences rather than values alone, which assists the user in understanding why and what features are responsible for the prediction. FuzzyApp is implemented using PERL CGI and is freely accessible at http://fuzzyapp.bicpu.edu.in/predict.php . We suggest the use of Fuzzy logic has much potential in biomarker and personalized medicine research to enhance predictive capabilities of post-genomics diagnostics.
Fuzzy C e-I(ec, eo) and Fuzzy Completely C e-I(rc, eo) Functions via Fuzzy e-Open Sets
Kamala, K.
2016-01-01
We introduced the notions of fuzzy C e-I(ec, eo) functions and fuzzy completely C e-I(rc, eo) functions via fuzzy e-open sets. Some properties and several characterization of these types of functions are investigated. PMID:27051858
Fuzzy Ce-I(ec,eo) and Fuzzy Completely Ce-I(rc,eo) Functions via Fuzzy e-Open Sets
Seenivasan, V.; Kamala, K.
2016-01-01
We introduced the notions of fuzzy C e -I(ec, eo) functions and fuzzy completely C e -I(rc, eo) functions via fuzzy e-open sets. Some properties and several characterization of these types of functions are investigated.
Fuzzy Ce-I(ec, eo) and Fuzzy Completely Ce-I(rc, eo) Functions via Fuzzy e-Open Sets.
Seenivasan, V; Kamala, K
2016-01-01
We introduced the notions of fuzzy C e-I(ec, eo) functions and fuzzy completely C e-I(rc, eo) functions via fuzzy e-open sets. Some properties and several characterization of these types of functions are investigated.
Luo, Yi; Zhang, Tao; Li, Xiao-song
2016-05-01
To explore the application of fuzzy time series model based on fuzzy c-means clustering in forecasting monthly incidence of Hepatitis E in mainland China. Apredictive model (fuzzy time series method based on fuzzy c-means clustering) was developed using Hepatitis E incidence data in mainland China between January 2004 and July 2014. The incidence datafrom August 2014 to November 2014 were used to test the fitness of the predictive model. The forecasting results were compared with those resulted from traditional fuzzy time series models. The fuzzy time series model based on fuzzy c-means clustering had 0.001 1 mean squared error (MSE) of fitting and 6.977 5 x 10⁻⁴ MSE of forecasting, compared with 0.0017 and 0.0014 from the traditional forecasting model. The results indicate that the fuzzy time series model based on fuzzy c-means clustering has a better performance in forecasting incidence of Hepatitis E.
Advanced Fuzzy Potential Field Method for Mobile Robot Obstacle Avoidance
Park, Jong-Wook; Kwak, Hwan-Joo; Kang, Young-Chang; Kim, Dong W.
2016-01-01
An advanced fuzzy potential field method for mobile robot obstacle avoidance is proposed. The potential field method primarily deals with the repulsive forces surrounding obstacles, while fuzzy control logic focuses on fuzzy rules that handle linguistic variables and describe the knowledge of experts. The design of a fuzzy controller—advanced fuzzy potential field method (AFPFM)—that models and enhances the conventional potential field method is proposed and discussed. This study also examines the rule-explosion problem of conventional fuzzy logic and assesses the performance of our proposed AFPFM through simulations carried out using a mobile robot. PMID:27123001
Advanced Fuzzy Potential Field Method for Mobile Robot Obstacle Avoidance.
Park, Jong-Wook; Kwak, Hwan-Joo; Kang, Young-Chang; Kim, Dong W
2016-01-01
An advanced fuzzy potential field method for mobile robot obstacle avoidance is proposed. The potential field method primarily deals with the repulsive forces surrounding obstacles, while fuzzy control logic focuses on fuzzy rules that handle linguistic variables and describe the knowledge of experts. The design of a fuzzy controller--advanced fuzzy potential field method (AFPFM)--that models and enhances the conventional potential field method is proposed and discussed. This study also examines the rule-explosion problem of conventional fuzzy logic and assesses the performance of our proposed AFPFM through simulations carried out using a mobile robot.
Fuzzy logic guided inverse treatment planning
International Nuclear Information System (INIS)
Yan Hui; Yin Fangfang; Guan Huaiqun; Kim, Jae Ho
2003-01-01
A fuzzy logic technique was applied to optimize the weighting factors in the objective function of an inverse treatment planning system for intensity-modulated radiation therapy (IMRT). Based on this technique, the optimization of weighting factors is guided by the fuzzy rules while the intensity spectrum is optimized by a fast-monotonic-descent method. The resultant fuzzy logic guided inverse planning system is capable of finding the optimal combination of weighting factors for different anatomical structures involved in treatment planning. This system was tested using one simulated (but clinically relevant) case and one clinical case. The results indicate that the optimal balance between the target dose and the critical organ dose is achieved by a refined combination of weighting factors. With the help of fuzzy inference, the efficiency and effectiveness of inverse planning for IMRT are substantially improved
Control Augmentation Using Adaptive Fuzzy Neural Networks
Kato, Akio; Wada, Yoshihisa
Control to improve control characteristics of aircraft, CA (Control Augmentation), is used to realize the desirable motion of aircraft corresponding to pilot's control action. When the control laws using fuzzy inference were designed, trial and error was repeated for optimization of the parameter. Here, in designing control laws using fuzzy neural networks, the systematic optimization of the parameter was possible using the learning algorithm usually used in neural networks, by expressing the fuzzy inference in the form of neural networks. Here, the control laws, which learned the characteristics of the aircraft for one flight condition only, were used in all flight conditions without changing any parameter. Evaluation of the designed control laws showed good performance in all flight conditions. This proves that fuzzy neural networks are an effective and flexible method when applied to control laws for control augmentation of aircraft.
Single board system for fuzzy inference
Symon, James R.; Watanabe, Hiroyuki
1991-01-01
The very large scale integration (VLSI) implementation of a fuzzy logic inference mechanism allows the use of rule-based control and decision making in demanding real-time applications. Researchers designed a full custom VLSI inference engine. The chip was fabricated using CMOS technology. The chip consists of 688,000 transistors of which 476,000 are used for RAM memory. The fuzzy logic inference engine board system incorporates the custom designed integrated circuit into a standard VMEbus environment. The Fuzzy Logic system uses Transistor-Transistor Logic (TTL) parts to provide the interface between the Fuzzy chip and a standard, double height VMEbus backplane, allowing the chip to perform application process control through the VMEbus host. High level C language functions hide details of the hardware system interface from the applications level programmer. The first version of the board was installed on a robot at Oak Ridge National Laboratory in January of 1990.
Fuzzy logic applications in engineering science
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.
Fuzzy logic and neural network technologies
Villarreal, James A.; Lea, Robert N.; Savely, Robert T.
1992-01-01
Applications of fuzzy logic technologies in NASA projects are reviewed to examine their advantages in the development of neural networks for aerospace and commercial expert systems and control. Examples of fuzzy-logic applications include a 6-DOF spacecraft controller, collision-avoidance systems, and reinforcement-learning techniques. The commercial applications examined include a fuzzy autofocusing system, an air conditioning system, and an automobile transmission application. The practical use of fuzzy logic is set in the theoretical context of artificial neural systems (ANSs) to give the background for an overview of ANS research programs at NASA. The research and application programs include the Network Execution and Training Simulator and faster training algorithms such as the Difference Optimized Training Scheme. The networks are well suited for pattern-recognition applications such as predicting sunspots, controlling posture maintenance, and conducting adaptive diagnoses.
Optimum Fuzzy Design of Ecological Pressurised Containers
Directory of Open Access Journals (Sweden)
Heikki Martikka
2011-01-01
Full Text Available In this study, the basic engineering principles, goals, and constraints are all combined to fuzzy methodology and applied to design of optimally pressurised containers emphasising the ecological and durability merits of various materials. The present fuzzy heuristics approach is derivable from generalisation of conventional analytical optimisation method into fuzzy multitechnical tasks. In the present approach, first the goals and constraints of the end-user are identified. Then decision variables are expressed as functions of the design variables. Their desirable ranges and biases are defined using the same fuzzy satisfaction function form. The optimal result has highest total satisfaction. These are then checked and fine-tuned by finite element method FEM. The optimal solution is the ecoplastic vessel, and aluminium was close. The method reveals that optimum depends strongly on the preset goals and values of the producer, society, and end-user.
A COMPARISON OF TWO FUZZY CLUSTERING TECHNIQUES
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Samarjit Das
2013-10-01
Full Text Available - In fuzzy clustering, unlike hard clustering, depending on the membership value, a single object may belong exactly to one cluster or partially to more than one cluster. Out of a number of fuzzy clustering techniques Bezdek’s Fuzzy C-Means and GustafsonKessel clustering techniques are well known where Euclidian distance and Mahalanobis distance are used respectively as a measure of similarity. We have applied these two fuzzy clustering techniques on a dataset of individual differences consisting of fifty feature vectors of dimension (feature three. Based on some validity measures we have tried to see the performances of these two clustering techniques from three different aspects- first, by initializing the membership values of the feature vectors considering the values of the three features separately one at a time, secondly, by changing the number of the predefined clusters and thirdly, by changing the size of the dataset.
Reliability and safety analyses under fuzziness
International Nuclear Information System (INIS)
Onisawa, T.; Kacprzyk, J.
1995-01-01
Fuzzy theory, for example possibility theory, is compatible with probability theory. What is shown so far is that probability theory needs not be replaced by fuzzy theory, but rather that the former works much better in applications if it is combined with the latter. In fact, it is said that there are two essential uncertainties in the field of reliability and safety analyses: One is a probabilistic uncertainty which is more relevant for mechanical systems and the natural environment, and the other is fuzziness (imprecision) caused by the existence of human beings in systems. The classical probability theory alone is therefore not sufficient to deal with uncertainties in humanistic system. In such a context this collection of works will put a milestone in the arguments of probability theory and fuzzy theory. This volume covers fault analysis, life time analysis, reliability, quality control, safety analysis and risk analysis. (orig./DG). 106 figs
Fuzzy logic for structural system control
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Herbert Martins Gomes
Full Text Available This paper provides some information and numerical tests that aims to investigate the use of a Fuzzy Controller applied to control systems. Some advantages are reported regarding the use of this controller, such as the characteristic ease of implementation due to its semantic feature in the statement of the control rules. On the other hand, it is also hypothesized that these systems have a lower performance loss when the system to be controlled is nonlinear or has time varying parameters. Numerical tests are performed using modal LQR optimal control and Fuzzy control of non-collocated systems with full state feedback in a two-dimensional structure. The paper proposes a way of designing a controller that may be a supervisory Fuzzy controller for a traditional controller or even a fuzzy controller independent from the traditional control, consisting on individual mode controllers. Some comments are drawn regarding the performance of these proposals in a number of arrangements.
Managing Controversies in the Fuzzy Front End
DEFF Research Database (Denmark)
Christiansen, John K.; Gasparin, Marta
2016-01-01
This research investigates the controversies that emerge in the fuzzy front end (FFE) and how they are closed so the innovation process can move on. The fuzzy front has been characterized in the literature as a very critical phase, but controversies in the FFE have not been studied before....... 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...... 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...
Refining Linear Fuzzy Rules by Reinforcement Learning
Berenji, Hamid R.; Khedkar, Pratap S.; Malkani, Anil
1996-01-01
Linear fuzzy rules are increasingly being used in the development of fuzzy logic systems. Radial basis functions have also been used in the antecedents of the rules for clustering in product space which can automatically generate a set of linear fuzzy rules from an input/output data set. Manual methods are usually used in refining these rules. This paper presents a method for refining the parameters of these rules using reinforcement learning which can be applied in domains where supervised input-output data is not available and reinforcements are received only after a long sequence of actions. This is shown for a generalization of radial basis functions. The formation of fuzzy rules from data and their automatic refinement is an important step in closing the gap between the application of reinforcement learning methods in the domains where only some limited input-output data is available.
Fuzzy controllers and fuzzy expert systems: industrial applications of fuzzy technology
Bonissone, Piero P.
1995-06-01
We will provide a brief description of the field of approximate reasoning systems, with a particular emphasis on the development of fuzzy logic control (FLC). FLC technology has drastically reduced the development time and deployment cost for the synthesis of nonlinear controllers for dynamic systems. As a result we have experienced an increased number of FLC applications. In a recently published paper we have illustrated some of our efforts in FLC technology transfer, covering projects in turboshaft aircraft engine control, stream turbine startup, steam turbine cycling optimization, resonant converter power supply control, and data-induced modeling of the nonlinear relationship between process variable in a rolling mill stand. These applications will be illustrated in the oral presentation. In this paper, we will compare these applications in a cost/complexity framework, and examine the driving factors that led to the use of FLCs in each application. We will emphasize the role of fuzzy logic in developing supervisory controllers and in maintaining explicit the tradeoff criteria used to manage multiple control strategies. Finally, we will describe some of our FLC technology research efforts in automatic rule base tuning and generation, leading to a suite of programs for reinforcement learning, supervised learning, genetic algorithms, steepest descent algorithms, and rule clustering.
Artificial Hydrocarbon Networks Fuzzy Inference System
Ponce, Hiram; Ponce, Pedro; Molina, Arturo
2013-01-01
This paper presents a novel fuzzy inference model based on artificial hydrocarbon networks, a computational algorithm for modeling problems based on chemical hydrocarbon compounds. In particular, the proposed fuzzy-molecular inference model (FIM-model) uses molecular units of information to partition the output space in the defuzzification step. Moreover, these molecules are linguistic units that can be partially understandable due to the organized structure of the topology and metadata param...
On Fuzzy Solutions for Diffusion Equation
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Jefferson Leite
2015-01-01
Full Text Available Our main goal is to define a fuzzy solution for problems involving diffusion. To this end, the solution of fuzzy diffusion-reaction-advection equation will be defined as Zadeh’s extension of deterministic solution of the associated problem. Important aspects such as unity and stability of these solutions will also be studied. Graphical representations of these solutions will be presented.
On new solutions of fuzzy differential equations
International Nuclear Information System (INIS)
Chalco-Cano, Y.; Roman-Flores, H.
2008-01-01
We study fuzzy differential equations (FDE) using the concept of generalized H-differentiability. This concept is based in the enlargement of the class of differentiable fuzzy mappings and, for this, we consider the lateral Hukuhara derivatives. We will see that both derivatives are different and they lead us to different solutions from a FDE. Also, some illustrative examples are given and some comparisons with other methods for solving FDE are made
Redundant sensor validation by using fuzzy logic
International Nuclear Information System (INIS)
Holbert, K.E.; Heger, A.S.; Alang-Rashid, N.K.
1994-01-01
This research is motivated by the need to relax the strict boundary of numeric-based signal validation. To this end, the use of fuzzy logic for redundant sensor validation is introduced. Since signal validation employs both numbers and qualitative statements, fuzzy logic provides a pathway for transforming human abstractions into the numerical domain and thus coupling both sources of information. With this transformation, linguistically expressed analysis principles can be coded into a classification rule-base for signal failure detection and identification
Dimensional Reduction over Fuzzy Coset Spaces
Aschieri, P; Manousselis, P; Madore, J
2004-01-01
We examine gauge theories on Minkowski space-time times fuzzy coset spaces. This means that the extra space dimensions instead of being a continuous coset space S/R are a corresponding finite matrix approximation. The gauge theory defined on this non-commutative setup is reduced to four dimensions and the rules of the corresponding dimensional reduction are established. We investigate in particular the case of the fuzzy sphere including the dimensional reduction of fermion fields.
Dimensional Reduction over Fuzzy Coset Spaces
Aschieri, P.; Madore, J.; Manousselis, P.; Zoupanos, G.
2004-04-01
We examine gauge theories on Minkowski space-time times fuzzy coset spaces. This means that the extra space dimensions instead of being a continuous coset space S/R are a corresponding finite matrix approximation. The gauge theory defined on this non-commutative setup is reduced to four dimensions and the rules of the corresponding dimensional reduction are established. We investigate in particular the case of the fuzzy sphere including the dimensional reduction of fermion fields.
A Fuzzy Radon Transform for Track Recognition
De Laat, C T A M; CERN. Geneva; Lourens, W; Kamermans, R
1993-01-01
In this contribution a fuzzy Radon transform is shown for application in ALICE and ATLAS (typical track density of 8000 in one unit of rapidity). Resolution is introduced by the "broadening" of the matching tracks in the Radon transform, which is obtained by making a convolution of the matching tracks with Gaussian kernel. In a good approximation, an analytical expression for the fuzzy Radon transform is given. An example of two track separation with noisy input is added.
Hierarchical Fuzzy Sets To Query Possibilistic Databases
Thomopoulos, Rallou; Buche, Patrice; Haemmerlé, Ollivier
2008-01-01
Within the framework of flexible querying of possibilistic databases, based on the fuzzy set theory, this chapter focuses on the case where the vocabulary used both in the querying language and in the data is hierarchically organized, which occurs in systems that use ontologies. We give an overview of previous works concerning two issues: firstly, flexible querying of imprecise data in the relational model; secondly, the introduction of fuzziness in hierarchies. Concerning the latter point, w...
Relational Compositions in Fuzzy Class Theory
Czech Academy of Sciences Publication Activity Database
Běhounek, Libor; Daňková, M.
2009-01-01
Roč. 160, č. 8 (2009), s. 1005-1036 ISSN 0165-0114 R&D Projects: GA AV ČR KJB100300502 Institutional research plan: CEZ:AV0Z10300504 Keywords : fuzzy relation * sup-T-composition * inf-R-composition * BK-product * fuzzy class theory * formal truth value Subject RIV: BA - General Mathematics Impact factor: 2.138, year: 2009
Interval type–2 fuzzy decision making
Runkler, Thomas; Coupland, Simon; John, Robert
2017-01-01
Full text on Nottingham eprints - http://eprints.nottingham.ac.uk/36609/ This paper concerns itself with decision making under uncertainty and the consideration of risk. Type-1 fuzzy logic by its (essentially) crisp nature is limited in modelling decision making as there is no uncertainty in the membership function. We are interested in the role that interval type-2 fuzzy sets might play in enhancing decision making. Previous work by Bellman and Zadeh considered decision making to be based...
A FORMALISM FOR FUZZY BUSINESS RULES
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Vasile Mazilescu
2015-05-01
Full Text Available The aim of this paper is to provide a formalism for fuzzy rule bases, included in our prototype system FUZZY_ENTERPRISE. This framework can be used in Distributed Knowledge Management Systems (DKMSs, real-time interdisciplinary decision making systems, that often require increasing technical support to high quality decisions in a timely manner. The language of the first-degree predicates facilitates the formulation of complex knowledge in a rigorous way, imposing appropriate reasoning techniques.
Fault Diagnosis in Deaerator Using Fuzzy Logic
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S Srinivasan
2007-01-01
Full Text Available In this paper a fuzzy logic based fault diagnosis system for a deaerator in a power plant unit is presented. The system parameters are obtained using the linearised state space deaerator model. The fuzzy inference system is created and rule base are evaluated relating the parameters to the type and severity of the faults. These rules are fired for specific changes in system parameters and the faults are diagnosed.
A fuzzy approach to selecting roof supports in longwall mining
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Yetkin, M. E.
2016-05-01
Full Text Available As a decision-making problem, selecting proper machines and equipment plays a key role for mining sites and companies. Many factors affect this decision, and values belonging to these factors can be expressed numerically and/or non-numerically. In order to make the most appropriate decision, engineers must carry out an evaluation process that comprises all criteria that might affect decision-making. To achieve this, multi-criteria decision-making tools are used. As a result of technological developments, coal outputs in longwall mining have risen tremendously over the last decades, and longwall mechanisation has become unavoidable. The significance of powered roof supports in particular increases day- by-day, since the rate of roof support has to be in accordance with the rate of face advance in longwalls. In this study, an integrated fuzzy analytic hierarchy process and fuzzy goal programming model is used to select the most suitable powered roof supports. The procedure is applied to a real-life underground coal mine that is operated using the longwall method. Seven alternative powered roof supports are compared with each other, taking a total of 24 decision criteria under four main topics into account. In conclusion, the most suitable roof supports for the mine under study are determined and recommended to the decision-makers of the system.
Fuzzy Sliding Mode Control of Plate Vibrations
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Manu Sharma
2010-01-01
Full Text Available In this paper, fuzzy logic is meshed with sliding mode control, in order to control vibrations of a cantilevered plate. Test plate is instrumented with a piezoelectric sensor patch and a piezoelectric actuator patch. Finite element method is used to obtain mathematical model of the test plate. A design approach of a sliding mode controller for linear systems with mismatched time-varying uncertainties is used in this paper. It is found that chattering around the sliding surface in the sliding mode control can be checked by the proposed fuzzy sliding mode control approach. With presented fuzzy sliding mode approach the actuator voltage time response has a smooth decay. This is important because an abrupt decay can excite higher modes in the structure. Fuzzy rule base consisting of nine rules, is generated from the sliding mode inequality. Experimental implementation of the control approach verify the theoretical findings. For experimental implementation, size of the problem is reduced using modal truncation technique. Modal displacements as well as velocities of first two modes are observed using real-time kalman observer. Real time implementation of fuzzy logic based control has always been a challenge because a given set of rules has to be executed in every sampling interval. Results in this paper establish feasibility of experimental implementation of presented fuzzy logic based controller for active vibration control.
Adaptive fuzzy system for 3-D vision
Mitra, Sunanda
1993-01-01
An adaptive fuzzy system using the concept of the Adaptive Resonance Theory (ART) type neural network architecture and incorporating fuzzy c-means (FCM) system equations for reclassification of cluster centers was developed. The Adaptive Fuzzy Leader Clustering (AFLC) architecture is a hybrid neural-fuzzy system which learns on-line in a stable and efficient manner. The system uses a control structure similar to that found in the Adaptive Resonance Theory (ART-1) network to identify the cluster centers initially. The initial classification of an input takes place in a two stage process; a simple competitive stage and a distance metric comparison stage. The cluster prototypes are then incrementally updated by relocating the centroid positions from Fuzzy c-Means (FCM) system equations for the centroids and the membership values. The operational characteristics of AFLC and the critical parameters involved in its operation are discussed. The performance of the AFLC algorithm is presented through application of the algorithm to the Anderson Iris data, and laser-luminescent fingerprint image data. The AFLC algorithm successfully classifies features extracted from real data, discrete or continuous, indicating the potential strength of this new clustering algorithm in analyzing complex data sets. The hybrid neuro-fuzzy AFLC algorithm will enhance analysis of a number of difficult recognition and control problems involved with Tethered Satellite Systems and on-orbit space shuttle attitude controller.
Dalecký, Štěpán
2014-01-01
Diplomová práce se zabývá teorií umělých neuronových sítí, následně jsou popsány fuzzy množiny a vysvětlena fuzzy logika. Na základě neuronových sítí, fuzzy množin a fuzzy logiky je navržen hybridní neuro-fuzzy systém vycházející ze systému ANFIS. Funkčnost zmíněných systémů byla ověřena na úloze řízení inverzního kyvadla. Pro řízení byly navrženy tři regulátory - první na bázi neuronových sítí, druhý fuzzy regulátor a třetí založený na systému ANFIS. Cílem práce je popsané systémy, na základ...
Frontiers of higher order fuzzy sets
Tahayori, Hooman
2015-01-01
Frontiers of Higher Order Fuzzy Sets, strives to improve the theoretical aspects of general and Interval Type-2 fuzzy sets and provides a unified representation theorem for higher order fuzzy sets. Moreover, the book elaborates on the concept of gradual elements and their integration with the higher order fuzzy sets. This book also introduces new frameworks for information granulation based on general T2FSs, IT2FSs, Gradual elements, Shadowed sets and rough sets. In particular, the properties and characteristics of the new proposed frameworks are studied. Such new frameworks are shown to be more capable to be exploited in real applications. Higher order fuzzy sets that are the result of the integration of general T2FSs, IT2FSs, gradual elements, shadowed sets and rough sets will be shown to be suitable to be applied in the fields of bioinformatics, business, management, ambient intelligence, medicine, cloud computing and smart grids. Presents new variations of fuzzy set frameworks and new areas of applicabili...
Driver's Behavior Modeling Using Fuzzy Logic
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Sehraneh Ghaemi
2010-01-01
Full Text Available In this study, we propose a hierarchical fuzzy system for human in a driver-vehicle-environment system to model takeover by different drivers. The driver's behavior is affected by the environment. The climate, road and car conditions are included in fuzzy modeling. For obtaining fuzzy rules, experts' opinions are benefited by means of questionnaires on effects of parameters such as climate, road and car conditions on driving capabilities. Also the precision, age and driving individuality are used to model the driver's behavior. Three different positions are considered for driving and decision making. A fuzzy model called Model I is presented for modeling the change of steering angle and speed control by considering time distances with existing cars in these three positions, the information about the speed and direction of car, and the steering angle of car. Also we obtained two other models based on fuzzy rules called Model II and Model III by using Sugeno fuzzy inference. Model II and Model III have less linguistic terms than Model I for the steering angle and direction of car. The results of three models are compared for a driver who drives based on driving laws.
Simplified interval type-2 fuzzy neural networks.
Lin, Yang-Yin; Liao, Shih-Hui; Chang, Jyh-Yeong; Lin, Chin-Teng
2014-05-01
This paper describes a self-evolving interval type-2 fuzzy neural network (FNN) for various applications. As type-1 fuzzy systems cannot effectively handle uncertainties in information within the knowledge base, we propose a simple interval type-2 FNN, which uses interval type-2 fuzzy sets in the premise and the Takagi-Sugeno-Kang (TSK) type in the consequent of the fuzzy rule. The TSK-type consequent of fuzzy rule is a linear combination of exogenous input variables. Given an initially empty the rule-base, all rules are generated with on-line type-2 fuzzy clustering. Instead of the time-consuming K-M iterative procedure, the design factors ql and qr are learned to adaptively adjust the upper and lower positions on the left and right limit outputs, using the parameter update rule based on a gradient descent algorithm. Simulation results demonstrate that our approach yields fewer test errors and less computational complexity than other type-2 FNNs.
Wang, Lijie; Li, Hongyi; Zhou, Qi; Lu, Renquan
2017-09-01
This paper investigates the problem of observer-based adaptive fuzzy control for a category of nonstrict feedback systems subject to both unmodeled dynamics and fuzzy dead zone. Through constructing a fuzzy state observer and introducing a center of gravity method, unmeasurable states are estimated and the fuzzy dead zone is defuzzified, respectively. By employing fuzzy logic systems to identify the unknown functions. And combining small-gain approach with adaptive backstepping control technique, a novel adaptive fuzzy output feedback control strategy is developed, which ensures that all signals involved are semi-globally uniformly bounded. Simulation results are given to demonstrate the effectiveness of the presented method.
Fuzzy logic-based advanced on–off control for thermal comfort in residential buildings
International Nuclear Information System (INIS)
Kang, Chang-Soon; Hyun, Chang-Ho; Park, Mignon
2015-01-01
Highlights: • Fuzzy logic-based advanced on–off control is proposed. • An anticipative control mechanism is implemented by using fuzzy theory. • Novel thermal analysis program including solar irradiation as a factor is developed. • The proposed controller solves over-heating and under-heating thermal problems. • Solar energy compensation method is applied to compensate for the solar energy. - Abstract: In this paper, an advanced on–off control method based on fuzzy logic is proposed for maintaining thermal comfort in residential buildings. Due to the time-lag of the control systems and the late building thermal response, an anticipative control mechanism is required to reduce energy loss and thermal discomfort. The proposed controller is implemented based on an on–off controller combined with a fuzzy algorithm. On–off control was chosen over other conventional control methods because of its structural simplicity. However, because conventional on–off control has a fixed operating range and a limited ability for improvements in control performance, fuzzy theory can be applied to overcome these limitations. Furthermore, a fuzzy-based solar energy compensation algorithm can be applied to the proposed controller to compensate for the energy gained from solar radiation according to the time of day. Simulations were conducted to compare the proposed controller with a conventional on–off controller under identical external conditions such as outdoor temperature and solar energy; these simulations were carried out by using a previously reported thermal analysis program that was modified to consider such external conditions. In addition, experiments were conducted in a residential building called Green Home Plus, in which hydronic radiant floor heating is used; in these experiments, the proposed system performed better than a system employing conventional on–off control methods
Multicriteria Personnel Selection by the Modified Fuzzy VIKOR Method.
Alguliyev, Rasim M; Aliguliyev, Ramiz M; Mahmudova, Rasmiyya S
2015-01-01
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.
Multicriteria Personnel Selection by the Modified Fuzzy VIKOR Method
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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.
Multicriteria Personnel Selection by the Modified Fuzzy VIKOR Method
Alguliyev, Rasim M.; Aliguliyev, Ramiz M.; Mahmudova, Rasmiyya S.
2015-01-01
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. PMID:26516634
On fuzzy quasi continuity and an application of fuzzy set theory
International Nuclear Information System (INIS)
Mahmoud, R.A.
2003-01-01
Where as classical topology has been developed closely connected with classical analysis describing topological phenomena in analysis, fuzzy topology with its important application in quantum gravity indicated by Witten and Elnaschie, has only been introduced as an analogue of the classical topology. The development of fuzzy topology without close relations to analytical problems did not give the possibility of testing successfully the applicability of the new notions and results. Till now this situation did not change, essentially. Although, many types of fuzzy sets and fuzzy functions having the quasi-property in both of weak and strong than openness and continuity, respectively, have been studied in detail. Many properties on fuzzy topological spaces such as compactness are discussed via fuzzy notion. While others are far from being completely devoted in its foundation. So, this paper is devoted to present a new class of fuzzy quasi-continuous functions via fuzzy compactness has been defined. Some characterizations and several properties of this new concept were discussed. Possible application to high energy physics and quantum gravity are indicated
A neuro-fuzzy inference system through integration of fuzzy logic and extreme learning machines.
Sun, Zhan-Li; Au, Kin-Fan; Choi, Tsan-Ming
2007-10-01
This paper investigates the feasibility of applying a relatively novel neural network technique, i.e., extreme learning machine (ELM), to realize a neuro-fuzzy Takagi-Sugeno-Kang (TSK) fuzzy inference system. The proposed method is an improved version of the regular neuro-fuzzy TSK fuzzy inference system. For the proposed method, first, the data that are processed are grouped by the k-means clustering method. The membership of arbitrary input for each fuzzy rule is then derived through an ELM, followed by a normalization method. At the same time, the consequent part of the fuzzy rules is obtained by multiple ELMs. At last, the approximate prediction value is determined by a weight computation scheme. For the ELM-based TSK fuzzy inference system, two extensions are also proposed to improve its accuracy. The proposed methods can avoid the curse of dimensionality that is encountered in backpropagation and hybrid adaptive neuro-fuzzy inference system (ANFIS) methods. Moreover, the proposed methods have a competitive performance in training time and accuracy compared to three ANFIS methods.
Fuzzy Context-Free Languages. Part 1: Generalized Fuzzy Context-Free Grammars
Asveld, P.R.J.
Motivated by aspects of robustness in parsing a context-free language, we study generalized fuzzy context-free grammars. These so-called fuzzy context-free $K$-grammars provide a very general framework to describe correctly as well as erroneously derived sentences by a single generating mechanism.
Fuzzy context-free languages - Part 1: Generalized fuzzy context-free grammars
Asveld, P.R.J.
2005-01-01
Motivated by aspects of robustness in parsing a context-free language, we study generalized fuzzy context-free grammars. These fuzzy context-free $K$-grammars provide a general framework to describe correctly as well as erroneously derived sentences by a single generating mechanism. They model the
On rarely generalized regular fuzzy continuous functions in fuzzy topological spaces
Directory of Open Access Journals (Sweden)
Appachi Vadivel
2016-11-01
Full Text Available In this paper, we introduce the concept of rarely generalized regular fuzzy continuous functions in the sense of A.P. Sostak's and Ramadan is introduced. Some interesting properties and characterizations of them are investigated. Also, some applications to fuzzy compact spaces are established.
Twenty-Five Years of the Fuzzy Factor: Fuzzy Logic, the Courts, and Student Press Law.
Plopper, Bruce L.; McCool, Lauralee
A study applied the structure of fuzzy logic, a fairly modern development in mathematical set theory, to judicial opinions concerning non-university, public school student publications, from 1975 to 1999. The study examined case outcomes (19 cases generated 27 opinions) as a function of fuzzy logic, and it evaluated interactions between fuzzy…
Fuzzy automata and pattern matching
Setzer, C. B.; Warsi, N. A.
1986-01-01
A wide-ranging search for articles and books concerned with fuzzy automata and syntactic pattern recognition is presented. A number of survey articles on image processing and feature detection were included. Hough's algorithm is presented to illustrate the way in which knowledge about an image can be used to interpret the details of the image. It was found that in hand generated pictures, the algorithm worked well on following the straight lines, but had great difficulty turning corners. An algorithm was developed which produces a minimal finite automaton recognizing a given finite set of strings. One difficulty of the construction is that, in some cases, this minimal automaton is not unique for a given set of strings and a given maximum length. This algorithm compares favorably with other inference algorithms. More importantly, the algorithm produces an automaton with a rigorously described relationship to the original set of strings that does not depend on the algorithm itself.
Comparison of fuzzy AHP and fuzzy TODIM methods for landfill location selection.
Hanine, Mohamed; Boutkhoum, Omar; Tikniouine, Abdessadek; Agouti, Tarik
2016-01-01
Landfill location selection is a multi-criteria decision problem and has a strategic importance for many regions. The conventional methods for landfill location selection are insufficient in dealing with the vague or imprecise nature of linguistic assessment. To resolve this problem, fuzzy multi-criteria decision-making methods are proposed. The aim of this paper is to use fuzzy TODIM (the acronym for Interactive and Multi-criteria Decision Making in Portuguese) and the fuzzy analytic hierarchy process (AHP) methods for the selection of landfill location. The proposed methods have been applied to a landfill location selection problem in the region of Casablanca, Morocco. After determining the criteria affecting the landfill location decisions, fuzzy TODIM and fuzzy AHP methods are applied to the problem and results are presented. The comparisons of these two methods are also discussed.
Research on Bounded Rationality of Fuzzy Choice Functions
Directory of Open Access Journals (Sweden)
Xinlin Wu
2014-01-01
Full Text Available The rationality of a fuzzy choice function is a hot research topic in the study of fuzzy choice functions. In this paper, two common fuzzy sets are studied and analyzed in the framework of the Banerjee choice function. The complete rationality and bounded rationality of fuzzy choice functions are defined based on the two fuzzy sets. An assumption is presented to study the fuzzy choice function, and especially the fuzzy choice function with bounded rationality is studied combined with some rationality conditions. Results show that the fuzzy choice function with bounded rationality also satisfies some important rationality conditions, but not vice versa. The research gives supplements to the investigation in the framework of the Banerjee choice function.
Bonissone CIDU Presentation: Design of Local Fuzzy Models
National Aeronautics and Space Administration — After reviewing key background concepts in fuzzy systems and evolutionary computing, we will focus on the use of local fuzzy models, which are related to both kernel...
Location Discovery Based on Fuzzy Geometry in Passive Sensor Networks
Directory of Open Access Journals (Sweden)
Rui Wang
2011-01-01
Full Text Available Location discovery with uncertainty using passive sensor networks in the nation's power grid is known to be challenging, due to the massive scale and inherent complexity. For bearings-only target localization in passive sensor networks, the approach of fuzzy geometry is introduced to investigate the fuzzy measurability for a moving target in R2 space. The fuzzy analytical bias expressions and the geometrical constraints are derived for bearings-only target localization. The interplay between fuzzy geometry of target localization and the fuzzy estimation bias for the case of fuzzy linear observer trajectory is analyzed in detail in sensor networks, which can realize the 3-dimensional localization including fuzzy estimate position and velocity of the target by measuring the fuzzy azimuth angles at intervals of fixed time. Simulation results show that the resulting estimate position outperforms the traditional least squares approach for localization with uncertainty.
A note on the L-fuzzy Banach's contraction principle
International Nuclear Information System (INIS)
Martinez-Moreno, J.; Roldan, A.; Roldan, C.
2009-01-01
Recently, Alaca et al. [Alaca C, Turkoglu D, Yildiz C. Fixed points in intuitionistic fuzzy metric spaces. Chaos, Solitons and Fractals 2006;29:10738] proved fuzzy Banach fixed point theorem in intuitionistic fuzzy metric spaces and Saadati [Saadati R. Notes to the paper 'fixed points in intuitionistic fuzzy metric spaces' and its generalization to L-fuzzy metric spaces. Chaos, Solitions and Fractals 2008;35:80-176] extended it in generalized fuzzy metric spaces. The purpose of this paper is to give a correct proof of the main result in Saadati [Saadati R. Notes to the paper 'fixed points in intuitionistic fuzzy metric spaces' and its generalization to L-fuzzy metric spaces. Chaos, Solitions and Fractals 2008;35:80-176].
Fuzzy randomness uncertainty in civil engineering and computational mechanics
Möller, Bernd
2004-01-01
This book, for the first time, provides a coherent, overall concept for taking account of uncertainty in the analysis, the safety assessment, and the design of structures. The reader is introduced to the problem of uncertainty modeling and familiarized with particular uncertainty models. For simultaneously considering stochastic and non-stochastic uncertainty the superordinated uncertainty model fuzzy randomness, which contains real valued random variables as well as fuzzy variables as special cases, is presented. For this purpose basic mathematical knowledge concerning the fuzzy set theory and the theory of fuzzy random variables is imparted. The body of the book comprises the appropriate quantification of uncertain structural parameters, the fuzzy and fuzzy probabilistic structural analysis, the fuzzy probabilistic safety assessment, and the fuzzy cluster structural design. The completely new algorithms are described in detail and illustrated by way of demonstrative examples.
Estimation of expiratory time constants via fuzzy clustering
M.S. Lourens (M.S.); L. Ali (Lejla); B.W. van den Berg (Bart); A.F.M. Verbraak (Anton); J.M. Bogaard (Jan); H.C. Hoogsteden (Henk); R. Babuška (R.)
2001-01-01
markdownabstractObjective. In mechanically ventilated patients the expiratorytime constant provides information about respiratory mechanics. In thepresent study a new method, fuzzy clustering, is proposed to determine expiratory time constants. Fuzzy clustering differs from other methods since it
Fuzzy Modelling and Simulation - The Evaluating Scales Problem
Czech Academy of Sciences Publication Activity Database
Vrba, Josef
2001-01-01
Roč. 41, - (2001), s. 257-288 ISSN 0232-9298 Institutional research plan: CEZ:AV0Z4072921 Keywords : fuzzy evaluating scale * membership asymmetry * fuzzy arithmetic Subject RIV: CI - Industrial Chemistry, Chemical Engineering
Application of Bipolar Fuzzy Sets in Graph Structures
Directory of Open Access Journals (Sweden)
Muhammad Akram
2016-01-01
Full Text Available A graph structure is a useful tool in solving the combinatorial problems in different areas of computer science and computational intelligence systems. In this paper, we apply the concept of bipolar fuzzy sets to graph structures. We introduce certain notions, including bipolar fuzzy graph structure (BFGS, strong bipolar fuzzy graph structure, bipolar fuzzy Ni-cycle, bipolar fuzzy Ni-tree, bipolar fuzzy Ni-cut vertex, and bipolar fuzzy Ni-bridge, and illustrate these notions by several examples. We study ϕ-complement, self-complement, strong self-complement, and totally strong self-complement in bipolar fuzzy graph structures, and we investigate some of their interesting properties.
Decision and game theory in management with intuitionistic fuzzy sets
Li, Deng-Feng
2014-01-01
The focus of this book is on establishing theories and methods of both decision and game analysis in management using intuitionistic fuzzy sets. It proposes a series of innovative theories, models and methods such as the representation theorem and extension principle of intuitionistic fuzzy sets, ranking methods of intuitionistic fuzzy numbers, non-linear and linear programming methods for intuitionistic fuzzy multi-attribute decision making and (interval-valued) intuitionistic fuzzy matrix games. These theories and methods form the theory system of intuitionistic fuzzy decision making and games, which is not only remarkably different from those of the traditional, Bayes and/or fuzzy decision theory but can also provide an effective and efficient tool for solving complex management problems. Since there is a certain degree of inherent hesitancy in real-life management, which cannot always be described by the traditional mathematical methods and/or fuzzy set theory, this book offers an effective approach to us...
Fuzzy model-based observers for fault detection in CSTR.
Ballesteros-Moncada, Hazael; Herrera-López, Enrique J; Anzurez-Marín, Juan
2015-11-01
Under the vast variety of fuzzy model-based observers reported in the literature, what would be the properone to be used for fault detection in a class of chemical reactor? In this study four fuzzy model-based observers for sensor fault detection of a Continuous Stirred Tank Reactor were designed and compared. The designs include (i) a Luenberger fuzzy observer, (ii) a Luenberger fuzzy observer with sliding modes, (iii) a Walcott-Zak fuzzy observer, and (iv) an Utkin fuzzy observer. A negative, an oscillating fault signal, and a bounded random noise signal with a maximum value of ±0.4 were used to evaluate and compare the performance of the fuzzy observers. The Utkin fuzzy observer showed the best performance under the tested conditions. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Two New Measures of Fuzzy Divergence and Their Properties
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Om Parkash
2006-06-01
Full Text Available Several measures of directed divergence and their corresponding measures of fuzzy divergence are available in the exiting literature. Two new measures of fuzzy divergence have been developed and their desirable properties have been discussed.
Human factors and fuzzy set theory for safety analysis
International Nuclear Information System (INIS)
Nishiwaki, Y.
1987-01-01
Human reliability and performance is affected by many factors: medical, physiological and psychological, etc. The uncertainty involved in human factors may not necessarily be probabilistic, but fuzzy. Therefore, it is important to develop a theory by which both the non-probabilistic uncertainties, or fuzziness, of human factors and the probabilistic properties of machines can be treated consistently. In reality, randomness and fuzziness are sometimes mixed. From the mathematical point of view, probabilistic measures may be considered a special case of fuzzy measures. Therefore, fuzzy set theory seems to be an effective tool for analysing man-machine systems. The concept 'failure possibility' based on fuzzy sets is suggested as an approach to safety analysis and fault diagnosis of a large complex system. Fuzzy measures and fuzzy integrals are introduced and their possible applications are also discussed. (author)
Z Number Based Fuzzy Inference System for Dynamic Plant Control
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Rahib H. Abiyev
2016-01-01
Full Text Available Frequently the reliabilities of the linguistic values of the variables in the rule base are becoming important in the modeling of fuzzy systems. Taking into consideration the reliability degree of the fuzzy values of variables of the rules the design of inference mechanism acquires importance. For this purpose, Z number based fuzzy rules that include constraint and reliability degrees of information are constructed. Fuzzy rule interpolation is presented for designing of an inference engine of fuzzy rule-based system. The mathematical background of the fuzzy inference system based on interpolative mechanism is developed. Based on interpolative inference process Z number based fuzzy controller for control of dynamic plant has been designed. The transient response characteristic of designed controller is compared with the transient response characteristic of the conventional fuzzy controller. The obtained comparative results demonstrate the suitability of designed system in control of dynamic plants.
A fuzzy MCDM framework based on fuzzy measure and fuzzy integral for agile supplier evaluation
Dursun, Mehtap
2017-06-01
Supply chains need to be agile in order to response quickly to the changes in today's competitive environment. The success of an agile supply chain depends on the firm's ability to select the most appropriate suppliers. This study proposes a multi-criteria decision making technique for conducting an analysis based on multi-level hierarchical structure and fuzzy logic for the evaluation of agile suppliers. The ideal and anti-ideal solutions are taken into consideration simultaneously in the developed approach. The proposed decision approach enables the decision-makers to use linguistic terms, and thus, reduce their cognitive burden in the evaluation process. Furthermore, a hierarchy of evaluation criteria and their related sub-criteria is employed in the presented approach in order to conduct a more effective analysis.
Gain ratio based fuzzy weighted association rule mining classifier for ...
Indian Academy of Sciences (India)
2: 271–277. Chen C-H, Tseng V S and Hong T-P 2008 Cluster-based evaluation in fuzzy-genetic data mining. IEEE. Trans. Fuzzy Syst. 16(1): 249 del Jesus M J, González P, Herrera F and Mesonero M 2007 Evolutionary fuzzy rule induction process for subgroup discovery: A case study in marketing. IEEE Trans. Fuzzy Syst.
Fuzzy model-based control of a nuclear reactor
International Nuclear Information System (INIS)
Van Den Durpel, L.; Ruan, D.
1994-01-01
The fuzzy model-based control of a nuclear power reactor is an emerging research topic world-wide. SCK-CEN is dealing with this research in a preliminary stage, including two aspects, namely fuzzy control and fuzzy modelling. The aim is to combine both methodologies in contrast to conventional model-based PID control techniques, and to state advantages of including fuzzy parameters as safety and operator feedback. This paper summarizes the general scheme of this new research project
8th International Conference on Fuzzy Information and Engineering
Wang, Pei-Zhuang; Liu, Zeng-Liang; Zhong, Yu-Bin
2016-01-01
This proceedings book presents edited results of the eighth International Conference on Fuzzy Information and Engineering (ICFIE'2015) and on Oriental Thinking and Fuzzy Logic, in August 17-20, 2015, in Dalian, China. The book contains 65 high-quality papers and is divided into six main parts: "Fuzzy Information Processing", "Fuzzy Engineering", "Internet and Big Data Applications", "Factor Space and Factorial Neural Networks", "Information Granulation and Granular Computing" as well as "Extenics and Innovation Methods".
VLSI design of universal approximator neuro-fuzzy systems
Baturone, I.; Sánchez-Solano, Santiago; Barriga, Angel; Jiménez Fernández, Carlos Jesús; Senhadji, Raouf; López, D. R.
2001-01-01
Neuro-fuzzy systems can theoretically solve any problem since they are universal approximators. Besides, they combine the advantages of the neuro and fuzzy paradigms. This paper describes and compares the different strategies that can be adopted to implement the learning and inference mechanisms involved in a neuro-fuzzy system. CAD tools, most of them integrated into the fuzzy system development environment Xfuzzy 2.0, have been developed to assist the designer in the implementation of neuro...
On the Difference between Traditional and Deductive Fuzzy Logic
Czech Academy of Sciences Publication Activity Database
Běhounek, Libor
2008-01-01
Roč. 159, č. 10 (2008), s. 1153-1164 ISSN 0165-0114 R&D Projects: GA AV ČR KJB100300502 Institutional research plan: CEZ:AV0Z10300504 Keywords : deductive fuzzy logic * fuzzy elements * gradual sets * entropy of fuzzy sets * aggregation * membership degrees * methodology of fuzzy mathematics Subject RIV: BA - General Mathematics Impact factor: 1.833, year: 2008
Fuzzy One-Class Classification Model Using Contamination Neighborhoods
Directory of Open Access Journals (Sweden)
Lev V. Utkin
2012-01-01
Full Text Available A fuzzy classification model is studied in the paper. It is based on the contaminated (robust model which produces fuzzy expected risk measures characterizing classification errors. Optimal classification parameters of the models are derived by minimizing the fuzzy expected risk. It is shown that an algorithm for computing the classification parameters is reduced to a set of standard support vector machine tasks with weighted data points. Experimental results with synthetic data illustrate the proposed fuzzy model.
Optimization of Inventories for Multiple Companies by Fuzzy Control Method
Kawase, Koichi; Konishi, Masami; Imai, Jun
2008-01-01
In this research, Fuzzy control theory is applied to the inventory control of the supply chain between multiple companies. The proposed control method deals with the amountof inventories expressing supply chain between multiple companies. Referring past demand and tardiness, inventory amounts of raw materials are determined by Fuzzy inference. The method that an appropriate inventory control becomes possible optimizing fuzzy control gain by using SA method for Fuzzy control. The variation of ...
A RIDING FUZZY CONTROL SYSTEM FOR A MOUNTAIN AGRICULTURAL ROBOT
Wang, Yuanjie; Yang, Fuzeng; Zhou, Yu; Pan, Guanting; He, Jinyi; Lan, Yubin
2013-01-01
A fuzzy control system was designed to command driving directions for a mountain agriculture robot. First, a fuzzy control system program was developed based on the scheme of the robot driving control system. Then, the core part of the system--the fuzzy controller--was designed. Finally, a system model was created and a simulation test was conducted through the application of the Fuzzy Toolbox in MATLAB and SIMULINK. The results showed that the system is effective.
Type-2 fuzzy sets: geometric defuzzification and type-reduction
Coupland, Simon
2007-01-01
This paper presents the geometric defuzzifier for general type-2 fuzzy sets. This novel method has the potential to transform the fuzzy control paradigm. General type-2 fuzzy logic is better able to model noise and uncertainty but suffers from the massive computational cost of defuzzification. This paper uses geometry to eliminate this problem, paving the way for general type-2 fuzzy control. This paper was shortlisted for the best paper award at this prestigious international conference.
Evolving fuzzy rules in a learning classifier system
Valenzuela-Rendon, Manuel
1993-01-01
The fuzzy classifier system (FCS) combines the ideas of fuzzy logic controllers (FLC's) and learning classifier systems (LCS's). It brings together the expressive powers of fuzzy logic as it has been applied in fuzzy controllers to express relations between continuous variables, and the ability of LCS's to evolve co-adapted sets of rules. The goal of the FCS is to develop a rule-based system capable of learning in a reinforcement regime, and that can potentially be used for process control.
Solution of the Traffic Jam Problem through Fuzzy Applications
Fernandez, Shery
2010-11-01
The major hurdle of a city planning council is to handle the traffic jam problem. The number of vehicles on roads increases day by day. Also the number of vehicles is directly proportional to the width of the road (including that of parallel roads). But it is not always possible to make roads or to increase width of the road corresponding to the increase in the number of vehicles. Also we cannot tell a person not to buy a vehicle. So trying to minimise the traffic jam is the only possible way to overcome this hurdle. Here we try to develop a method to avoid traffic jam through a mathematical approach (through fuzzy applications). This method helps to find a suitable route from an origin to a destination with lesser time than other routes.
Fuzzy Versions of Epistemic and Deontic Logic
Gounder, Ramasamy S.; Esterline, Albert C.
1998-01-01
Epistemic and deontic logics are modal logics, respectively, of knowledge and of the normative concepts of obligation, permission, and prohibition. Epistemic logic is useful in formalizing systems of communicating processes and knowledge and belief in AI (Artificial Intelligence). Deontic logic is useful in computer science wherever we must distinguish between actual and ideal behavior, as in fault tolerance and database integrity constraints. We here discuss fuzzy versions of these logics. In the crisp versions, various axioms correspond to various properties of the structures used in defining the semantics of the logics. Thus, any axiomatic theory will be characterized not only by its axioms but also by the set of properties holding of the corresponding semantic structures. Fuzzy logic does not proceed with axiomatic systems, but fuzzy versions of the semantic properties exist and can be shown to correspond to some of the axioms for the crisp systems in special ways that support dependency networks among assertions in a modal domain. This in turn allows one to implement truth maintenance systems. For the technical development of epistemic logic, and for that of deontic logic. To our knowledge, we are the first to address fuzzy epistemic and fuzzy deontic logic explicitly and to consider the different systems and semantic properties available. We give the syntax and semantics of epistemic logic and discuss the correspondence between axioms of epistemic logic and properties of semantic structures. The same topics are covered for deontic logic. Fuzzy epistemic and fuzzy deontic logic discusses the relationship between axioms and semantic properties for these logics. Our results can be exploited in truth maintenance systems.
A Brief History of Fuzzy Logic
Directory of Open Access Journals (Sweden)
Angel Garrido
2012-04-01
Full Text Available
The problems of uncertainty, imprecision and vagueness have been discussed for many years. These problems have been major topics in philosophical circles with much debate, in particular, about the nature of vagueness and the ability of traditional Boolean logic to cope with concepts and perceptions that are imprecise or vague. The Fuzzy Logic (which is usually translated into Castilian by “Lógica Borrosa”, or “Lógica Difusa”, but also by “Lógica Heurística” can be considered a bypass-valued logics (Multi-valued Logic, MVL, its acronym in English. It is founded on, and is closely related to-Fuzzy Sets Theory, and successfully applied on Fuzzy Systems. You might think that fuzzy logic is quite recent and what has worked for a short time, but its origins date back at least to the Greek philosophers and especially Plato (428-347 B.C.. It even seems plausible
to trace their origins in China and India. Because it seems that they were the first to consider that all things need not be of a certain type or quit, but there are a stopover between. That is, be the pioneers in considering that there may be varying degrees of truth and falsehood. In case of colors, for example, between white and black there is a whole infinite scale: the shades of gray. Some recent theorems show that in principle fuzzy logic can be used to model any continuous system, be it based
in AI, or physics, or biology, or economics, etc. Investigators in many fields may find that fuzzy, commonsense models are more useful, and many more accurate than are standard mathematical ones. We analyze here the history and development of this problem: Fuzziness, or “Borrosidad” (in Castilian, essential to work with Uncertainty.
Directory of Open Access Journals (Sweden)
Anahid Kamali
2015-12-01
Full Text Available In this paper, a new class of fuzzy sets called fuzzy strongly ${{g}^{*}}$-closed sets is introduced and its properties are investigated. Moreover, we study some more properties of this type of closed spaces.
Anahid Kamali; Hamid Moradi; Balwinder Singh
2015-01-01
In this paper, a new class of fuzzy sets called fuzzy strongly ${{g}^{*}}$-closed sets is introduced and its properties are investigated. Moreover, we study some more properties of this type of closed spaces.
Zhao, Tao; Dian, Songyi
2017-09-01
This paper addresses a fuzzy dynamic output feedback H ∞ control design problem for continuous-time nonlinear systems via T-S fuzzy model. The stability of the fuzzy closed-loop system which is formed by a T-S fuzzy model and a fuzzy dynamic output feedback H ∞ controller connected in a closed loop is investigated with Lyapunov stability theory. The proposed fuzzy controller does not share the same membership functions and number of rules with T-S fuzzy systems, which can enhance design flexibility. A line-integral fuzzy Lyapunov function is utilized to derive the stability conditions in the form of linear matrix inequalities (LMIs). The boundary information of membership functions is considered in the stability analysis to reduce the conservativeness of the imperfect premise matching design technique. Two simulation examples are provided to demonstrate the effectiveness of the proposed approach. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
A Fuzzy Student Modeling with Two Intelligent Agents.
Huang, Mu-Jung
1999-01-01
A new fuzzy student modeling method with two intelligent agents, a diagnosis agent and a learning agent, are suggested by this article for several aspects of student modeling in Intelligent Tutoring Systems. Also integrated are fuzzy theories and Fuzzy-Hasse diagrams for student modeling. (Author/AEF)
control of a dc motor using fuzzy logic control algorithm
African Journals Online (AJOL)
user
This study sought to establish the impact of a fuzzy logic controller (FLC) and a Proportional-Integral-Derivative (PID) controller in the control performance of an industrial type DC motor using MATLAB. The fuzzy logic controller was developed on the basis of Mamdani type fuzzy inference system (FIS). The centroid method ...
Land cover classification using reformed fuzzy C-means
Indian Academy of Sciences (India)
Areas of application of fuzzy cluster analysis include data analysis, pattern recognition, and image segmentation. The detection of special geometrical shapes like circles and ellipses can be achieved by so-called shell clustering algorithms. 3.1 Fuzzy C means. The most prominent algorithm is the FCM or fuzzy C means ...
Exact Membership Functions for the Fuzzy Weighted Average
van den Broek, P.M.; Noppen, J.A.R.
2011-01-01
The problem of computing the fuzzy weighted average, where both attributes and weights are fuzzy numbers, is well studied in the literature. Generally, the approach is to apply Zadeh’s extension principle to compute α-cuts of the fuzzy weighted average from the α-cuts of the attributes and weights
On Convergence of Fixed Points in Fuzzy Metric Spaces
Directory of Open Access Journals (Sweden)
Yonghong Shen
2013-01-01
Full Text Available We mainly focus on the convergence of the sequence of fixed points for some different sequences of contraction mappings or fuzzy metrics in fuzzy metric spaces. Our results provide a novel research direction for fixed point theory in fuzzy metric spaces as well as a substantial extension of several important results from classical metric spaces.
Interpolation of fuzzy data | Khodaparast | Journal of Fundamental ...
African Journals Online (AJOL)
In the current world and in the field of science and technology, interpolation issues are also of a fuzzy type, it has many scientific applications in developmental work, medical issues, imaging, engineering software and graphics. Therefore, in this article we intend to investigate Interpolation of fuzzy data in order to apply fuzzy ...
Modified intuitionistic fuzzy metric spaces and some fixed point theorems
International Nuclear Information System (INIS)
Saadati, R.; Sedghi, S.; Shobe, N.
2008-01-01
Since the intuitionistic fuzzy metric space has extra conditions (see [Gregori V, Romaguera S, Veereamani P. A note on intuitionistic fuzzy metric spaces. Chaos, Solitons and Fractals 2006;28:902-5]). In this paper, we consider modified intuitionistic fuzzy metric spaces and prove some fixed point theorems in these spaces. All the results presented in this paper are new
A Comparative Analysis of Fuzzy Inference Engines in Context of ...
African Journals Online (AJOL)
PROF. O. E. OSUAGWU
profitability quantification in plastic recycling. [14] designs a neuro-fuzzy linguistic approach in optimizing the flow rate of a plastic extruder process. [15] presents fuzzy rule-base frame work for the management of tropical diseases. [16] proposes a fuzzy-neural network model for effective control of profitability in a paper.
Intuitionistic fuzzy 2-metric space and its completion
International Nuclear Information System (INIS)
Mursaleen, M.; Lohani, Q.M. Danish; Mohiuddine, S.A.
2009-01-01
Recently, Mursaleen and Lohani [Mursaleen M, Lohani Danish. Intuitionistic fuzzy 2-normed space and some related concepts. Chaos, Solitons and Fractals (2008), doi:10.1016/j.chaos.2008.11.006] have introduced the concept of intuitionistic fuzzy 2-normed space. In this paper, we introduce the concept of intuitionistic fuzzy 2-metric space and study its completion.
Minimal solution of linear formed fuzzy matrix equations
Directory of Open Access Journals (Sweden)
Maryam Mosleh
2012-10-01
Full Text Available In this paper according to the structured element method, the $mimes n$ inconsistent fuzzy matrix equation $Ailde{X}=ilde{B},$ which are linear formed by fuzzy structured element, is investigated. The necessary and sufficient condition for the existence of a fuzzy solution is also discussed. some examples are presented to illustrate the proposed method.
Postmodern Fuzzy System Theory: A Deconstruction Approach Based on Kabbalah
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Gabriel Burstein
2014-11-01
Full Text Available Modern general system theory proposed a holistic integrative approach based on input-state-output dynamics as opposed to the traditional reductionist detail based approach. Information complexity and uncertainty required a fuzzy system theory, based on fuzzy sets and fuzzy logic. While successful in dealing with analysis, synthesis and control of technical engineering systems, general system theory and fuzzy system theory could not fully deal with humanistic and human-like intelligent systems which combine technical engineering components with human or human-like components characterized by their cognitive, emotional/motivational and behavioral/action levels of operation. Such humanistic systems are essential in artificial intelligence, cognitive and behavioral science applications, organization management and social systems, man-machine systems or human factor systems, behavioral knowledge based economics and finance applications. We are introducing here a “postmodern fuzzy system theory” for controlled state dynamics and output fuzzy systems and fuzzy rule based systems using our earlier postmodern fuzzy set theory and a Kabbalah possible worlds model of modal logic and semantics type. In order to create a postmodern fuzzy system theory, we “deconstruct” a fuzzy system in order to incorporate in it the cognitive, emotional and behavioral actions and expressions levels characteristic for humanistic systems. Kabbalah offers a structural, fractal and hierarchic model for integrating cognition, emotions and behavior. We obtain a canonic deconstruction for a fuzzy system into its cognitive, emotional and behavioral fuzzy subsystems.
Evaluation of Soil Quality: Application of Fuzzy Indicators
The problem of assessing soil quality is considered as the fuzzy modeling task. Fuzzy indicator concept (FIC) is used as a general platform for the assessment of soil quality as a "degree or grade of perfection”. The FIC can be realized through the utilization of fuzzy soil quality indicators (FSQI)...
Type-2 fuzzy elliptic membership functions for modeling uncertainty
DEFF Research Database (Denmark)
Kayacan, Erdal; Sarabakha, Andriy; Coupland, Simon
2018-01-01
Whereas type-1 and type-2 membership functions (MFs) are the core of any fuzzy logic system, there are no performance criteria available to evaluate the goodness or correctness of the fuzzy MFs. In this paper, we make extensive analysis in terms of the capability of type-2 elliptic fuzzy MFs in m...
Fuzzy logic control of vehicle suspensions with dry friction nonlinearity
Indian Academy of Sciences (India)
of methods could be used to perform defuzzification, two of the most common of which are: i) The Mamdani method that returns the centroid of the output fuzzy region as the crisp output of the fuzzy interface system. ii) The TVFI (truth value flow inference) method that returns a weighted average as the crisp output of the fuzzy ...
Fuzzy Reasoning Based on First-Order Modal Logic,
Zhang, Xiaoru; Zhang, Z.; Sui, Y.; Huang, Z.
2008-01-01
As an extension of traditional modal logics, this paper proposes a fuzzy first-order modal logic based on believable degree, and gives out a description of the fuzzy first-order modal logic based on constant domain semantics. In order to make the reasoning procedure between the fuzzy assertions
Implementation of fuzzy logic control algorithm in embedded ...
African Journals Online (AJOL)
Fuzzy logic control algorithm solves problems that are difficult to address with traditional control techniques. This paper describes an implementation of fuzzy logic control algorithm using inexpensive hardware as well as how to use fuzzy logic to tackle a specific control problem without any special software tools. As a case ...
On Intuitionistic Fuzzy β-Almost Compactness and β-Nearly Compactness.
Renuka, R; Seenivasan, V
2015-01-01
The concept of intuitionistic fuzzy β-almost compactness and intuitionistic fuzzy β-nearly compactness in intuitionistic fuzzy topological spaces is introduced and studied. Besides giving characterizations of these spaces, we study some of their properties. Also, we investigate the behavior of intuitionistic fuzzy β-compactness, intuitionistic fuzzy β-almost compactness, and intuitionistic fuzzy β-nearly compactness under several types of intuitionistic fuzzy continuous mappings.
Soft ideal topological space and mixed fuzzy soft ideal topological space
Directory of Open Access Journals (Sweden)
Manash Borah
2019-01-01
Full Text Available In this paper we introduce fuzzy soft ideal and mixed fuzzy soft ideal topological spaces and some properties of this space. Also we introduce fuzzy soft $I$-open set, fuzzy soft $\\alpha$-$I$-open set, fuzzy soft pre-$I$-open set, fuzzy soft semi-$I$-open set and fuzzy soft $\\beta$-$I$-open set and discuss some of their properties.
FPGA Based Modified Fuzzy PID Controller for Pitch Angle of Bench-top Helicopter
A.A. Aldair
2012-01-01
Fuzzy PID controller design is still a complex task due to the involvement of a large number of parameters in defining the fuzzy rule base. To reduce the huge number of fuzzy rules required in the normal design for fuzzy PID controller, the fuzzy PID controller is represented as Proportional-Derivative Fuzzy (PDF) controller and Proportional-Integral Fuzzy (PIF) controller connected in parallel through a summer. The PIF controller design has been simplified by replacing the PIF controller by ...
An Integrated Risk Index Model Based on Hierarchical Fuzzy Logic for Underground Risk Assessment
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Muhammad Fayaz
2017-10-01
Full Text Available Available space in congested cities is getting scarce due to growing urbanization in the recent past. The utilization of underground space is considered as a solution to the limited space in smart cities. The numbers of underground facilities are growing day by day in the developing world. Typical underground facilities include the transit subway, parking lots, electric lines, water supply and sewer lines. The likelihood of the occurrence of accidents due to underground facilities is a random phenomenon. To avoid any accidental loss, a risk assessment method is required to conduct the continuous risk assessment and report any abnormality before it happens. In this paper, we have proposed a hierarchical fuzzy inference based model for under-ground risk assessment. The proposed hierarchical fuzzy inference architecture reduces the total number of rules from the rule base. Rule reduction is important because the curse of dimensionality damages the transparency and interpretation as it is very tough to understand and justify hundreds or thousands of fuzzy rules. The computation time also increases as rules increase. The proposed model takes 175 rules having eight input parameters to compute the risk index, and the conventional fuzzy logic requires 390,625 rules, having the same number of input parameters to compute risk index. Hence, the proposed model significantly reduces the curse of dimensionality. Rule design for fuzzy logic is also a tedious task. In this paper, we have also introduced new rule schemes, namely maximum rule-based and average rule-based; both schemes can be used interchangeably according to the logic needed for rule design. The experimental results show that the proposed method is a virtuous choice for risk index calculation where the numbers of variables are greater.
Nguyen, Huu-Tho; Md Dawal, Siti Zawiah; Nukman, Yusoff; Aoyama, Hideki; Case, Keith
2015-01-01
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.
Fuzzy logic, neural networks, and soft computing
Zadeh, Lofti A.
1994-01-01
The past few years have witnessed a rapid growth of interest in a cluster of modes of modeling and computation which may be described collectively as soft computing. The distinguishing characteristic of soft computing is that its primary aims are to achieve tractability, robustness, low cost, and high MIQ (machine intelligence quotient) through an exploitation of the tolerance for imprecision and uncertainty. Thus, in soft computing what is usually sought is an approximate solution to a precisely formulated problem or, more typically, an approximate solution to an imprecisely formulated problem. A simple case in point is the problem of parking a car. Generally, humans can park a car rather easily because the final position of the car is not specified exactly. If it were specified to within, say, a few millimeters and a fraction of a degree, it would take hours or days of maneuvering and precise measurements of distance and angular position to solve the problem. What this simple example points to is the fact that, in general, high precision carries a high cost. The challenge, then, is to exploit the tolerance for imprecision by devising methods of computation which lead to an acceptable solution at low cost. By its nature, soft computing is much closer to human reasoning than the traditional modes of computation. At this juncture, the major components of soft computing are fuzzy logic (FL), neural network theory (NN), and probabilistic reasoning techniques (PR), including genetic algorithms, chaos theory, and part of learning theory. Increasingly, these techniques are used in combination to achieve significant improvement in performance and adaptability. Among the important application areas for soft computing are control systems, expert systems, data compression techniques, image processing, and decision support systems. It may be argued that it is soft computing, rather than the traditional hard computing, that should be viewed as the foundation for artificial
A Novel Pixon-Based Image Segmentation Process Using Fuzzy Filtering and Fuzzy C-mean Algorithm
DEFF Research Database (Denmark)
Nadernejad, Ehsan; Barari, Amin
2011-01-01
for image segmentation. The key idea is to create a pixon model by combining fuzzy filtering as a kernel function and a fuzzy c-means clustering algorithm for image segmentation. Use of fuzzy filters reduces noise and slightly smoothes the image. Use of the proposed pixon model prevented image over...
Collaborative fuzzy clustering from multiple weighted views.
Jiang, Yizhang; Chung, Fu-Lai; Wang, Shitong; Deng, Zhaohong; Wang, Jun; Qian, Pengjiang
2015-04-01
Clustering with multiview data is becoming a hot topic in data mining, pattern recognition, and machine learning. In order to realize an effective multiview clustering, two issues must be addressed, namely, how to combine the clustering result from each view and how to identify the importance of each view. In this paper, based on a newly proposed objective function which explicitly incorporates two penalty terms, a basic multiview fuzzy clustering algorithm, called collaborative fuzzy c-means (Co-FCM), is firstly proposed. It is then extended into its weighted view version, called weighted view collaborative fuzzy c-means (WV-Co-FCM), by identifying the importance of each view. The WV-Co-FCM algorithm indeed tackles the above two issues simultaneously. Its relationship with the latest multiview fuzzy clustering algorithm Collaborative Fuzzy K-Means (Co-FKM) is also revealed. Extensive experimental results on various multiview datasets indicate that the proposed WV-Co-FCM algorithm outperforms or is at least comparable to the existing state-of-the-art multitask and multiview clustering algorithms and the importance of different views of the datasets can be effectively identified.
Decentralized fuzzy control of multiple nonholonomic vehicles
Energy Technology Data Exchange (ETDEWEB)
Driessen, B.J.; Feddema, J.T.; Kwok, K.S.
1997-09-01
This work considers the problem of controlling multiple nonholonomic vehicles so that they converge to a scent source without colliding with each other. Since the control is to be implemented on simple 8-bit microcontrollers, fuzzy control rules are used to simplify a linear quadratic regulator control design. The inputs to the fuzzy controllers for each vehicle are the (noisy) direction to the source, the distance to the closest neighbor vehicle, and the direction to the closest vehicle. These directions are discretized into four values: Forward, Behind, Left, and Right, and the distance into three values: Near, Far, Gone. The values of the control at these discrete values are obtained based on the collision-avoidance repulsive forces and the change of variables that reduces the motion control problem of each nonholonomic vehicle to a nonsingular one with two degrees of freedom, instead of three. A fuzzy inference system is used to obtain control values for inputs between the small number of discrete input values. Simulation results are provided which demonstrate that the fuzzy control law performs well compared to the exact controller. In fact, the fuzzy controller demonstrates improved robustness to noise.
Fuzzy Multi-objective Linear Programming Approach
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Amna Rehmat
2007-07-01
Full Text Available Traveling salesman problem (TSP is one of the challenging real-life problems, attracting researchers of many fields including Artificial Intelligence, Operations Research, and Algorithm Design and Analysis. The problem has been well studied till now under different headings and has been solved with different approaches including genetic algorithms and linear programming. Conventional linear programming is designed to deal with crisp parameters, but information about real life systems is often available in the form of vague descriptions. Fuzzy methods are designed to handle vague terms, and are most suited to finding optimal solutions to problems with vague parameters. Fuzzy multi-objective linear programming, an amalgamation of fuzzy logic and multi-objective linear programming, deals with flexible aspiration levels or goals and fuzzy constraints with acceptable deviations. In this paper, a methodology, for solving a TSP with imprecise parameters, is deployed using fuzzy multi-objective linear programming. An example of TSP with multiple objectives and vague parameters is discussed.
Similarity Measures of Sequence of Fuzzy Numbers and Fuzzy Risk Analysis
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Zarife Zararsız
2015-01-01
Full Text Available We present the methods to evaluate the similarity measures between sequence of triangular fuzzy numbers for making contributions to fuzzy risk analysis. Firstly, we calculate the COG (center of gravity points of sequence of triangular fuzzy numbers. After, we present the methods to measure the degree of similarity between sequence of triangular fuzzy numbers. In addition, we give an example to compare the methods mentioned in the text. Furthermore, in this paper, we deal with the (t1,t2 type fuzzy number. By defining the algebraic operations on the (t1,t2 type fuzzy numbers we can solve the equations in the form x+u(t1,t2=v(t1,t2, where u(t1,t2 and v(t1,t2 are fuzzy number. By this way, we can build an algebraic structure on fuzzy numbers. Additionally, the generalized difference sequence spaces of triangular fuzzy numbers [l∞(Ft]B(r^,s^, [c(Ft]B(r^,s^, and [c0(Ft]B(r^,s^, consisting of all sequences u∗=(u(t1,t2k such that Br^,s^u∗ is in the spaces l∞(Ft, c(Ft, and c0(Ft, have been constructed, respectively. Furthermore, some classes of matrix transformations from the space cFtB(r^,s^ and μ(Ft to μ(Ft and cFtB(r^,s^ are characterized, respectively, where μ(Ft is any sequence space.
A version of Stone-Weierstrass theorem in Fuzzy Analysis
Energy Technology Data Exchange (ETDEWEB)
Font, J.J.; Sanchis, D.; Sanchis, M.
2017-07-01
Fuzzy numbers provide formalized tools to deal with non-precise quantities. They are indeed fuzzy sets in the real line and were introduced in 1978 by Dubois and Prade , who also defined their basic operations. Since then, Fuzzy Analysis has developed based on the notion of fuzzy number just as much as classical Real Analysis did based on the concept of real number. Such development was eased by a characterization of fuzzy numbers provided in 1986 by Goetschel and Voxman leaning on their level sets. As in the classical setting, continuous fuzzy-valued functions (fuzzy functions) are the central core of the theory. The principal difference with regard to real-valued continuous functions is the fact that the fuzzy numbers do not form a vectorial space, which determines all the results, and, especially, the proofs. The study of fuzzy functions has developed, principally, about two lines of investigation: - Differential fuzzy equations, which have turned out to be the natural way of modelling physical and engineering problems in contexts where the parameters are vague or incomplete. - The problem of approximation of fuzzy functions, basically using the approximation capability of fuzzy neural networks. We will focus on this second line of investigation, though our approach will be more general and based on an adaptation of the famous Stone-Weierstrass Theorem to the fuzzy context. This way so, we introduce the concept of “multiplier” of a set of fuzzy functions and use it to give a constructive proof of a Stone-Weiestrass type theorem for fuzzy functions. (Author)
Classification of protein profiles using fuzzy clustering techniques
DEFF Research Database (Denmark)
Karemore, Gopal; Mullick, Jhinuk B.; Sujatha, R.
2010-01-01
Present study has brought out a comparison of PCA and fuzzy clustering techniques in classifying protein profiles (chromatogram) of homogenates of different tissue origins: Ovarian, Cervix, Oral cancers, which were acquired using HPLC–LIF (High Performance Liquid......-to-day variation, artifacts due to experimental strategies, inherent uncertainty in pumping procedure which are very common activities during HPLC-LIF experiment. Under these circumstances we demonstrate how fuzzy clustering algorithm like Gath Geva followed by sammon mapping outperform...
Sistem Pendukung Keputusan Fuzzy Mamdani pada Alat Penyiraman Tanaman Otomatis
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Munjiat Setiani Asih
2018-04-01
Full Text Available In the gardening activities that cannot be separated from the activities of watering plants. Almost everyone is still doing the activity of watering the plants manually, by watering the plants one by one is time-consuming enough and wasting energy. Watering plants is an activity that is always done every day by almost everyone that has plants at home, office and elsewhere. The activity of watering the plants manually can not know how much water is needed by the plant so that many plants die of excess water. With the development of technology provides ease of watering plants. Technological advances include automatic plant watering, automatic plant watering equipment utilizing micro controller as a circuit brain that processes the entire series to be used for watering plants. Knowledge of fuzzy mamdani can be used as a reference when the plants watered or not to take the value of soil moisture and air temperature, so the need for water plants can be met.Keywords: automatic, air temperature, soil moisture, fuzzy mamdani
International Nuclear Information System (INIS)
Zhang, Xu; Huang, Hong Zhong; Yu, Lanfeng
2006-01-01
Interactive Fuzzy Physical Programming (IFPP) developed in this paper is a new efficient multi-objective optimization method, which retains the advantages of physical programming while considering the fuzziness of the designer's preferences. The fuzzy preference function is introduced based on the model of linear physical programming, which is used to guide the search for improved solutions by interactive decision analysis. The example of multi-objective optimization design of the spindle of internal grinder demonstrates that the improved preference conforms to the subjective desires of the designer
Influence of fuzzy norms and other heuristics on “Mixed fuzzy rule formation”
Gabriel, Thomas R.; Berthold, Michael R.
2004-01-01
In Mixed Fuzzy Rule Formation [Int. J. Approx. Reason. 32 (2003) 67] a method to extract mixed fuzzy rules from data was introduced. The underlying algorithm s performance is influenced by the choice of fuzzy t-norm and t-conorm, and a heuristic to avoid conflicts between patterns and rules of different classes throughout training. In the following addendum to [Int. J. Approx. Reason. 32 (2003) 67], we discuss in more depth how these parameters affect the generalization performance of the res...
Directory of Open Access Journals (Sweden)
Sukhpreet Kaur Sidhu
2014-01-01
Full Text Available The drawbacks of the existing methods to obtain the fuzzy optimal solution of such linear programming problems, in which coefficients of the constraints are represented by real numbers and all the other parameters as well as variables are represented by symmetric trapezoidal fuzzy numbers, are pointed out, and to resolve these drawbacks, a new method (named as Mehar method is proposed for the same linear programming problems. Also, with the help of proposed Mehar method, a new method, much easy as compared to the existing methods, is proposed to deal with the sensitivity analysis of the same type of linear programming problems.
A fuzzy logic model to forecast stock market momentum in Indonesia's property and real estate sector
Penawar, H. K.; Rustam, Z.
2017-07-01
The Capital market has the important role in Indonesia's economy. The capital market does not only support the economy of Indonesia but also being an indicator Indonesia's economy improvement. Something that has been traded in the capital market is stock (stock market). Nowadays, the stock market is full of uncertainty. That uncertainty values make predicting stock market is all that we have to do before we make a decision in the stock market. One that can be predicted in the stock market is momentum. To forecast stock market momentum, it can use fuzzy logic model. In the process of modeling, it will be used 14 days historical data that consisting the value of open, high, low, and close, to predict the next 5 days momentum categories. There are three momentum categories namely Bullish, Neutral, and Bearish. To illustrate the fuzzy logic model, we will use stocks data from several companies that listed on Indonesia Stock Exchange (IDX) in property and real estate sector.
Probabilistic Quadratic Programming Problems with Some Fuzzy Parameters
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S. K. Barik
2012-01-01
making problem by using some specified random variables and fuzzy numbers. In the present paper, randomness is characterized by Weibull random variables and fuzziness is characterized by triangular and trapezoidal fuzzy number. A defuzzification method has been introduced for finding the crisp values of the fuzzy numbers using the proportional probability density function associated with the membership functions of these fuzzy numbers. An equivalent deterministic crisp model has been established in order to solve the proposed model. Finally, a numerical example is presented to illustrate the solution procedure.
Fuzzy logic and neural networks basic concepts & application
Alavala, Chennakesava R
2008-01-01
About the Book: The primary purpose of this book is to provide the student with a comprehensive knowledge of basic concepts of fuzzy logic and neural networks. The hybridization of fuzzy logic and neural networks is also included. No previous knowledge of fuzzy logic and neural networks is required. Fuzzy logic and neural networks have been discussed in detail through illustrative examples, methods and generic applications. Extensive and carefully selected references is an invaluable resource for further study of fuzzy logic and neural networks. Each chapter is followed by a question bank
Application of ANNs approach for solving fully fuzzy polynomials system
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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.
FUZZY ACCEPTANCE SAMPLING AND CHARACTERISTIC CURVES
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Ebru Turano?lu
2012-02-01
Full Text Available Acceptance sampling is primarily used for the inspection of incoming or outgoing lots. Acceptance sampling refers to the application of specific sampling plans to a designated lot or sequence of lots. The parameters of acceptance sampling plans are sample sizes and acceptance numbers. In some cases, it may not be possible to define acceptance sampling parameters as crisp values. These parameters can be expressed by linguistic variables. The fuzzy set theory can be successfully used to cope with the vagueness in these linguistic expressions for acceptance sampling. In this paper, the main distributions of acceptance sampling plans are handled with fuzzy parameters and their acceptance probability functions are derived. Then the characteristic curves of acceptance sampling are examined under fuzziness. Illustrative examples are given.
On fuzzy control of water desalination plants
Energy Technology Data Exchange (ETDEWEB)
Titli, A. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Jamshidi, M. [New Mexico Univ., Albuquerque, NM (United States); Olafsson, F. [Institute of Technology, Norway (Norway)
1995-12-31
In this report we have chosen a sub-system of an MSF water desalination plant, the brine heater, for analysis, synthesis, and simulation. This system has been modelled and implemented on computer. A fuzzy logic controller (FLC) for the top brine temperature control loop has been designed and implemented on the computer. The performance of the proposed FLC is compared with three other conventional control strategies: PID, cascade and disturbance rejection control. One major concern on FLC`s has been the lack of stability criteria. An up to-date survey of stability of fuzzy control systems is given. We have shown stability of the proposed FLC using the Sinusoidal Input Describing Functions (SIDF) method. The potential applications of fuzzy controllers for complex and large-scale systems through hierarchy of rule sets and hybridization with conventional approaches are also investigated. (authors)
Neurocontrol and fuzzy logic: Connections and designs
Werbos, Paul J.
1991-01-01
Artificial neural networks (ANNs) and fuzzy logic are complementary technologies. ANNs extract information from systems to be learned or controlled, while fuzzy techniques mainly use verbal information from experts. Ideally, both sources of information should be combined. For example, one can learn rules in a hybrid fashion, and then calibrate them for better whole-system performance. ANNs offer universal approximation theorems, pedagogical advantages, very high-throughput hardware, and links to neurophysiology. Neurocontrol - the use of ANNs to directly control motors or actuators, etc. - uses five generalized designs, related to control theory, which can work on fuzzy logic systems as well as ANNs. These designs can copy what experts do instead of what they say, learn to track trajectories, generalize adaptive control, and maximize performance or minimize cost over time, even in noisy environments. Design tradeoffs and future directions are discussed throughout.
Fuzzy logic in autonomous orbital operations
Lea, Robert N.; Jani, Yashvant
1991-01-01
Fuzzy logic can be used advantageously in autonomous orbital operations that require the capability of handling imprecise measurements from sensors. Several applications are underway to investigate fuzzy logic approaches and develop guidance and control algorithms for autonomous orbital operations. Translational as well as rotational control of a spacecraft have been demonstrated using space shuttle simulations. An approach to a camera tracking system has been developed to support proximity operations and traffic management around the Space Station Freedom. Pattern recognition and object identification algorithms currently under development will become part of this camera system at an appropriate level in the future. A concept to control environment and life support systems for large Lunar based crew quarters is also under development. Investigations in the area of reinforcement learning, utilizing neural networks, combined with a fuzzy logic controller, are planned as a joint project with the Ames Research Center.
Genetic algorithms and fuzzy multiobjective optimization
Sakawa, Masatoshi
2002-01-01
Since the introduction of genetic algorithms in the 1970s, an enormous number of articles together with several significant monographs and books have been published on this methodology. As a result, genetic algorithms have made a major contribution to optimization, adaptation, and learning in a wide variety of unexpected fields. Over the years, many excellent books in genetic algorithm optimization have been published; however, they focus mainly on single-objective discrete or other hard optimization problems under certainty. There appears to be no book that is designed to present genetic algorithms for solving not only single-objective but also fuzzy and multiobjective optimization problems in a unified way. Genetic Algorithms And Fuzzy Multiobjective Optimization introduces the latest advances in the field of genetic algorithm optimization for 0-1 programming, integer programming, nonconvex programming, and job-shop scheduling problems under multiobjectiveness and fuzziness. In addition, the book treats a w...
Fuzzy efficiency optimization of AC induction motors
Jani, Yashvant; Sousa, Gilberto; Turner, Wayne; Spiegel, Ron; Chappell, Jeff
1993-01-01
This paper describes the early states of work to implement a fuzzy logic controller to optimize the efficiency of AC induction motor/adjustable speed drive (ASD) systems running at less than optimal speed and torque conditions. In this paper, the process by which the membership functions of the controller were tuned is discussed and a controller which operates on frequency as well as voltage is proposed. The membership functions for this dual-variable controller are sketched. Additional topics include an approach for fuzzy logic to motor current control which can be used with vector-controlled drives. Incorporation of a fuzzy controller as an application-specific integrated circuit (ASIC) microchip is planned.
Unified Theories from Fuzzy Extra Dimensions
Aschieri, P.; Manousselis, P.; Zoupanos, G.
2004-01-01
We combine and exploit ideas from Coset Space Dimensional Reduction (CSDR) methods and Non-commutative Geometry. We consider the dimensional reduction of gauge theories defined in high dimensions where the compact directions are a fuzzy space (matrix manifold). In the CSDR one assumes that the form of space-time is M^D=M^4 x S/R with S/R a homogeneous space. Then a gauge theory with gauge group G defined on M^D can be dimensionally reduced to M^4 in an elegant way using the symmetries of S/R, in particular the resulting four dimensional gauge is a subgroup of G. In the present work we show that one can apply the CSDR ideas in the case where the compact part of the space-time is a finite approximation of the homogeneous space S/R, i.e. a fuzzy coset. In particular we study the fuzzy sphere case.
Fuzzy technology present applications and future challenges
Fedrizzi, Mario; Kacprzyk, Janusz
2016-01-01
This book provides readers with a timely and comprehensive yet concise view on the field of fuzzy logic and its real-world applications. The chapters, written by authoritative scholars in the field, report on promising new models for data analysis, decision making, and systems modeling, with a special emphasis on their applications in management science. The book is a token of appreciation from the fuzzy research community to Professor Christer Carlsson for his long time research and organizational commitment, which have among other things resulted in the foundation and success of the Institute for Advanced Management Systems Research (IAMSR) at Åbo Akademi University, in Åbo (Turku), Finland. The book serves as timely guide for the fuzzy logic and operations research communities alike. .
Resource integrated planning through fuzzy techniques
Energy Technology Data Exchange (ETDEWEB)
Haddad, J.; Torres, G. Lambert [Escola Federal de Engenharia de Itajuba, MG (Brazil); Jannuzzi, G. de M. [Universidade Estadual de Campinas, SP (Brazil). Faculdade de Engenharia Mecanica
1994-12-31
A methodology for decision-making in studies involving energy saving by using the Fuzzy Sets Theory is presented. The Fuzzy Sets Theory permits to handle and to operate exact and non-exact propositions, that is, to incorporate both numerical data (exact) and the knowledge of either the expert or the analyst (inexact). The basic concepts of this theory are presented with its main operations and properties. Following, some criteria and technical-economical parameters used in the planning of the generation expansion are shown and, finally, the Theory of the Fuzzy Sets is applied aiming to establish electrical power generation and conservation strategies considering the power demand. (author) 6 refs., 8 tabs.
Evaluating software architecture using fuzzy formal models
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Payman Behbahaninejad
2012-04-01
Full Text Available Unified Modeling Language (UML has been recognized as one of the most popular techniques to describe static and dynamic aspects of software systems. One of the primary issues in designing software packages is the existence of uncertainty associated with such models. Fuzzy-UML to describe software architecture has both static and dynamic perspective, simultaneously. The evaluation of software architecture design phase initiates always help us find some additional requirements, which helps reduce cost of design. In this paper, we use a fuzzy data model to describe the static aspects of software architecture and the fuzzy sequence diagram to illustrate the dynamic aspects of software architecture. We also transform these diagrams into Petri Nets and evaluate reliability of the architecture. The web-based hotel reservation system for further explanation has been studied.
Fuzzy spheres from inequivalent coherent states quantizations
International Nuclear Information System (INIS)
Gazeau, Jean Pierre; Huguet, Eric; Lachieze-Rey, Marc; Renaud, Jacques
2007-01-01
The existence of a family of coherent states (CS) solving the identity in a Hilbert space allows, under certain conditions, to quantize functions defined on the measure space of CS parameters. The application of this procedure to the 2-sphere provides a family of inequivalent CS quantizations based on the spin spherical harmonics (the CS quantization from usual spherical harmonics appears to give a trivial issue for the Cartesian coordinates). We compare these CS quantizations to the usual (Madore) construction of the fuzzy sphere. Due to these differences, our procedure yields new types of fuzzy spheres. Moreover, the general applicability of CS quantization suggests similar constructions of fuzzy versions of a large variety of sets
Fuzzy Logic Controller Design for Intelligent Robots
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Ching-Han Chen
2017-01-01
Full Text Available This paper presents a fuzzy logic controller by which a robot can imitate biological behaviors such as avoiding obstacles or following walls. The proposed structure is implemented by integrating multiple ultrasonic sensors into a robot to collect data from a real-world environment. The decisions that govern the robot’s behavior and autopilot navigation are driven by a field programmable gate array- (FPGA- based fuzzy logic controller. The validity of the proposed controller was demonstrated by simulating three real-world scenarios to test the bionic behavior of a custom-built robot. The results revealed satisfactorily intelligent performance of the proposed fuzzy logic controller. The controller enabled the robot to demonstrate intelligent behaviors in complex environments. Furthermore, the robot’s bionic functions satisfied its design objectives.
Robust fuzzy logic stabilization with disturbance elimination.
Danapalasingam, Kumeresan A
2014-01-01
A robust fuzzy logic controller is proposed for stabilization and disturbance rejection in nonlinear control systems of a particular type. The dynamic feedback controller is designed as a combination of a control law that compensates for nonlinear terms in a control system and a dynamic fuzzy logic controller that addresses unknown model uncertainties and an unmeasured disturbance. Since it is challenging to derive a highly accurate mathematical model, the proposed controller requires only nominal functions of a control system. In this paper, a mathematical derivation is carried out to prove that the controller is able to achieve asymptotic stability by processing state measurements. Robustness here refers to the ability of the controller to asymptotically steer the state vector towards the origin in the presence of model uncertainties and a disturbance input. Simulation results of the robust fuzzy logic controller application in a magnetic levitation system demonstrate the feasibility of the control design.
Variable-order fuzzy fractional PID controller.
Liu, Lu; Pan, Feng; Xue, Dingyu
2015-03-01
In this paper, a new tuning method of variable-order fractional fuzzy PID controller (VOFFLC) is proposed for a class of fractional-order and integer-order control plants. Fuzzy logic control (FLC) could easily deal with parameter variations of control system, but the fractional-order parameters are unable to change through this way and it has confined the effectiveness of FLC. Therefore, an attempt is made in this paper to allow all the five parameters of fractional-order PID controller vary along with the transformation of system structure as the outputs of FLC, and the influence of fractional orders λ and μ on control systems has been investigated to make the fuzzy rules for VOFFLC. Four simulation results of different plants are shown to verify the availability of the proposed control strategy. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Fuzzy Logic Based Autonomous Traffic Control System
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Muhammad ABBAS
2012-01-01
Full Text Available The aim of this paper is to design and implement fuzzy logic based traffic light Control system to solve the traffic congestion issues. In this system four input parameters: Arrival, Queue, Pedestrian and Emergency Vehicle and two output parameters: Extension in Green and Pedestrian Signals are used. Using Fuzzy Rule Base, the system extends or terminates the Green Signal according to the Traffic situation at the junction. On the presence of emergency vehicle, the system decides which signal(s should be red and how much an extension should be given to Green Signal for Emergency Vehicle. The system also monitors the density of people and makes decisions accordingly. In order to verify the proposed design algorithm MATLAB simulation is adopted and results obtained show concurrency to the calculated values according to the Mamdani Model of the Fuzzy Control System.