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Sample records for fuzzy na inspecao

  1. On the logos a naïve view on ordinary reasoning and fuzzy logic

    CERN Document Server

    Trillas, Enric

    2017-01-01

    This book offers an inspiring and naïve view on language and reasoning. It presents a new approach to ordinary reasoning that follows the author’s former work on fuzzy logic. Starting from a pragmatic scientific view on meaning as a quantity, and the common sense reasoning from a primitive notion of inference, which is shared by both laypeople and experts, the book shows how this can evolve, through the addition of more and more suppositions, into various formal and specialized modes of precise, imprecise, and approximate reasoning. The logos are intended here as a synonym for rationality, which is usually shown by the processes of questioning, guessing, telling, and computing. Written in a discursive style and without too many technicalities, the book presents a number of reflections on the study of reasoning, together with a new perspective on fuzzy logic and Zadeh’s “computing with words” grounded in both language and reasoning. It also highlights some mathematical developments supporting this vie...

  2. Fuzzy ABC: Modelando a Incerteza na Alocação dos Custos AmbientaisFuzzy ABC: Modeling the Uncertainty in Environmental Cost AllocationFuzzy ABC: Modelando la Incertidumbre en la Alocation de los Costos Ambientales

    Directory of Open Access Journals (Sweden)

    BORBA, José Alonso

    2007-05-01

    Full Text Available RESUMOEm muitos casos, prevenir a poluição e a destruição do meio ambiente é menos oneroso do que remediar esses danos. Nesse contexto, a alocação de custos ambientais aos produtos permite uma melhor visualização e análise da rentabilidade dos produtos. Entretanto, a alocação dos custos ambientais aos produtos envolve informações estimadas e assume uma linearidade entre o consumo das atividades e os produtos, que muitas vezes não existe. Para contemplar essa não linearidade, esta pesquisa apresenta uma metodologia baseada na utilização da lógica fuzzy para modelar a incerteza e a subjetividade, inerentes ao processo de alocação dos custos ambientais. Para isso, além de um estudo de caso desenvolvido por Hansen e Mowen (2001, p. 584, que foi utilizado como referência, outras variáveis foram incorporadas. Em seguida, uma proposta de solução, que utiliza fundamentos da teoria dos conjuntos fuzzy, ou nebulosos, foi desenvolvida com o objetivo de contemplar a subjetividade e a incerteza na alocação dos custos ambientais. Para simular esse modelo, foram estabelecidas 126 regras de inferência. A etapa final da elaboração do modelo nebuloso consistiu na fuzzificação e defuzzificação dos dados existentes e dos novos direcionadores gerados por intermédio da utilização do software FuzzyTECH®. Os resultados encontrados no modelo proposto - FuzzyABC (Fuzzy Activity Based Costing - evidenciam que a lógica fuzzy pode ser utilizada como uma importante ferramenta para tratar da ambigüidade e da incerteza, inerentes ao processo de alocação dos custos ambientais.ABSTRACTIn many cases, preventing pollution and environmental destruction is cheaper than remedying these damages. In this sense, environmental cost allocation enables a better visualization and analysis of a product’s profitability. However, the environmental allocation process involves estimated information and assumes linearity between activity consumption

  3. Lógica nebulosa para avaliar riscos na auditoria Fuzzy logic for risk assessment in auditing

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    Jerônimo Antunes

    2006-08-01

    Full Text Available A avaliação dos riscos de que os controles internos de uma entidade possam falhar constitui-se em significativo desafio para os auditores independentes de demonstrações contábeis. As metodologias de trabalho empregadas para tal finalidade, normalmente, utilizam a lógica clássica, ou também denominada binária, presumindo que os fatores de riscos estão presentes, ou não, em um determinado tipo de processo de controle. O objetivo deste trabalho foi conceber um modelo de avaliação de risco dos controles internos de uma entidade utilizando a lógica nebulosa (fuzzy logic, para contemplar os elementos difusos que compõem os fatores desse tipo de risco analisados na auditoria de demonstrações contábeis. A validação conceitual do modelo concebido foi realizada por meio de entrevistas e debates com especialistas em auditoria de demonstrações contábeis e com consultas a bibliografias relevantes pertinentes. Como conclusão do estudo, ficou patente que o modelo de avaliação de risco, com o uso da lógica nebulosa, elimina a restrição binária da lógica clássica e permite tratar, de forma quantitativa, conceitos ambíguos através da aplicação de uma escala psicométrica, para refl etir predicados tais como: "muito bom", "bom", "razoável", "de grande importância", "de pouca importância" etc., tendo potencial para produzir resultados mais amplos e próximos da realidade.The assessment of the risks that an entity's internal control system may fail represents a significant challenge to independent auditors. The methodologies used to audit financial statements are usually supported by classical logic, also called binary logic, departing from the relatively simplistic premise that risk factors are either present or not in a certain kind of control process. This study aimed to conceive a risk assessment model for an entity's internal control system, using the fuzzy logic approach, to take into account the diffuse elements that

  4. LÓGICA FUZZY NA ANÁLISE ESPACIAL DOS TEORES DE K E S NO TECIDO FOLIAR DO MAMOEIRO

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    Abel Souza da Fonseca

    2017-04-01

    Full Text Available Objetivou-se com este trabalho utilizar lógica fuzzy para mapear os graus de pertinência do K e do S considerando a variabilidade espacial de cada nutriente avaliado e o conjunto dos teores ideias. O estudo foi realizado em lavoura comercial de mamão, no norte do Espírito Santo, onde forma coletadas folhas recém-maduras em pontos georreferenciados. Foram determinados os teores foliares de K e S. Definida a dependência espacial foram confeccionados mapas temáticos por meio da krigagem ordinária. À partir dos mapas, determinou-se o universo de discurso de cada nutriente, seguido da construção dos conjuntos fuzzy de entrada, por meio da função trapezoidal. Com os mapas dos teores foliares realizou-se a classificação fuzzy. Os graus de pertinência para K representam os teores foliares abaixo do recomendado pela literatura. O S encontrado no tecido foliar apresentou se encontarm com mais pertinencia na faixa dos teores ideais.

  5. Fuzzy Boundary and Fuzzy Semiboundary

    OpenAIRE

    Athar, M.; Ahmad, B.

    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...

  6. Technical application of Fuzzy logic in the construction of an energy sustainability index; Aplicacao das tecnicas de logica fuzzi na construcao de um indice de sustentabilidade energetica

    Energy Technology Data Exchange (ETDEWEB)

    Santos, Francisco Carlos B. dos; Carneiro, Alvaro Luiz Guimaraes [Instituto de Pesquisas Energeticas e Nucleares (IPEN-CNEN/SP), Sao Paulo - SP (Brazil)], E-mails: fcarlos@usp.br, carneiro@ipen.br

    2010-11-15

    Aggregation tools database and subsequent interpretation are the most challenge in the area of sustainability This task becomes very complex due to correlation of topics that comprise the dimensions that form the basis of the concept of sustainable development. The technique known as Fuzzy Logic or Fuzzy Logic is a powerful tool to capture information on vacancies, which is often the only information available in the area of sustainability. (author)

  7. LÓGICA FUZZY NA ANÁLISE ESPACIAL DOS TEORES DE BORO E MANGANÊS NO TECIDO FOLIAR DO CAFEEIRO CONILON

    Directory of Open Access Journals (Sweden)

    Mariana Lima de Jesus

    2017-01-01

    Full Text Available Essa pesquisa objetivou utilizar lógica Fuzzy para mapear os teores foliares dos micronutrientes em café conilon, considerando sua variabilidade espacial. O estudo foi realizado na fazenda experimental do INCAPER, onde forma coletadas folhas recém-maduras para determinação dos teores de Mn e B. Fez-se a análise de estatística descritiva e geoestatística dos teores foliares; definida a dependência espacial, foram confeccionados mapas temáticos por meio da krigagem. A partir dos mapas, determinou-se o universo de discurso de cada nutriente, seguido da construção dos conjuntos fuzzy de entrada, por meio da função trapezoidal. Com os mapas dos teores foliares realizou-se a classificação fuzzy. A lógica fuzzy permitiu visualizar as mudanças gradativas das faixas tidas como ideais para B e Mn.

  8. Assessing sandy beach macrofaunal patterns along large-scale environmental gradients: A Fuzzy Naïve Bayes approach

    Science.gov (United States)

    Bozzeda, Fabio; Zangrilli, Maria Paola; Defeo, Omar

    2016-06-01

    A Fuzzy Naïve Bayes (FNB) classifier was developed to assess large-scale variations in abundance, species richness and diversity of the macrofauna inhabiting fifteen Uruguayan sandy beaches affected by the effects of beach morphodynamics and the estuarine gradient generated by Rio de la Plata. Information from six beaches was used to estimate FNB parameters, while abiotic data of the remaining nine beaches were used to forecast abundance, species richness and diversity. FNB simulations reproduced the general increasing trend of target variables from inner estuarine reflective beaches to marine dissipative ones. The FNB model also identified a threshold value of salinity range beyond which diversity markedly increased towards marine beaches. Salinity range is suggested as an ecological master factor governing distributional patterns in sandy beach macrofauna. However, the model: 1) underestimated abundance and species richness at the innermost estuarine beach, with the lowest salinity, and 2) overestimated species richness in marine beaches with a reflective morphodynamic state, which is strongly linked to low abundance, species richness and diversity. Therefore, future modeling efforts should be refined by giving a dissimilar weigh to the gradients defined by estuarine (estuarine beaches) and morphodynamic (marine beaches) variables, which could improve predictions of target variables. Our modeling approach could be applied to a wide spectrum of issues, ranging from basic ecology to social-ecological systems. This approach seems relevant, given the current challenge to develop predictive methodologies to assess the simultaneous and nonlinear effects of anthropogenic and natural impacts in coastal ecosystems.

  9. Fuzzy contractibility

    OpenAIRE

    GÜNER, Erdal

    2007-01-01

    Abstract. In this paper, .rstly some fundamental concepts are included re- lating to fuzzy topological spaces. Secondly, the fuzzy connected set is intro- duced. Finally, de.ning fuzzy contractible space, it is shown that X is a fuzzy contractible space if and only if X is fuzzy homotopic equivalent with a fuzzy single-point space.

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

    Energy Technology Data Exchange (ETDEWEB)

    Nascimento, Claudio Souza do

    2010-07-01

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

  11. Abordagem Fuzzy na Taxa de Sobrevivência de Trypoxylon (Trypargilum lactitarse (Hymenoptera: Crabronidae / Fuzzy Approach in the Survival Rate of Trypoxylon (Trypargilum lactitarse (Hymenoptera: Crabronidae

    Directory of Open Access Journals (Sweden)

    Lilian Berton

    2009-12-01

    Full Text Available ResumoEste trabalho apresenta um sistema baseado em regras fuzzy (SBRF abordando a interação entre fertilidade, tamanho do ninho e sobrevivência de machos e fêmeas de Trypoxylon lactitarse Saussure. A partir de informações sobre fertilidade e tamanho do ninho, o sistema retorna a taxa de sobrevivência de machos e fêmeas permitindo abordar as implicações de uma razão sexual enviesada a favor de machos, uma razão sexual enviesada a favor de fêmeas, ou uma razão sexual de 1:1.AbstractThis paper presents a fuzzy rule-based system (FRBS addressing the interaction among fertility, size of the nest and survival of Trypoxylon lactitarse Saussure males and females. From information on fertility and nest size, the system returns the survival rate of male and female allowing us to address the implications of a skewed sex ratio in favor of males, a skewed sex ratio in favor of females, or a sex ratio of 1:1.

  12. Fuzzy Set Field and Fuzzy Metric

    OpenAIRE

    Gebru Gebray; B. Krishna Reddy

    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.

  13. Fuzzy Deterrence

    Science.gov (United States)

    2010-05-01

    the world of logic than friction in mechanics. — Charles Sanders Peirce 1 Rational deterrence theory rests on the foundation that...4 Kosko, Fuzzy Thinking, 4-17. 5 Daniel McNeill and Paul Freiberger, Fuzzy Logic: The Revolutionary Computer Technology That Is Changing Our...1 McNeill and Freiberger, Fuzzy Logic, 174. 2 Yarger, Little Book on Big Strategy, 16. 3 Mukaidono, Fuzzy Logic for

  14. Fuzzy Cores and Fuzzy Balancedness

    NARCIS (Netherlands)

    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 a

  15. Fuzzy Cores and Fuzzy Balancedness

    NARCIS (Netherlands)

    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

  16. Fuzzy Ideals and Fuzzy Distributive Lattices%Fuzzy Ideals and Fuzzy Distributive Lattices*

    Institute of Scientific and Technical Information of China (English)

    S.H.Dhanani; Y. S. Pawar

    2011-01-01

    Our main objective is to study properties of a fuzzy ideals (fuzzy dual ideals). A study of special types of fuzzy ideals (fuzzy dual ideals) is also furnished. Some properties of a fuzzy ideals (fuzzy dual ideals) are furnished. Properties of a fuzzy lattice homomorphism are discussed. Fuzzy ideal lattice of a fuzzy lattice is defined and discussed. Some results in fuzzy distributive lattice are proved.

  17. Uso da lógica fuzzy na caracterização do ambiente produtivo para matrizes gestantes The use of fuzzy logic for the productive environment characterization for pregnant sows

    Directory of Open Access Journals (Sweden)

    Héliton Pandorfi

    2007-04-01

    Full Text Available O objetivo desta pesquisa consistiu na avaliação do ambiente de alojamento, estimando as condições favoráveis ao melhor desempenho de matrizes gestantes. O experimento foi realizado no período compreendido entre 4-1 e 11-3-2005, em propriedade de produção industrial de suínos, localizada no município de Elias Fausto - SP. A pesquisa foi desenvolvida no setor de gestação, com 24 matrizes primíparas, 12 fêmeas alojadas em baias individuais (T1 e 12 em baias coletivas (T2. O trabalho foi dividido em duas etapas, em função da forma de avaliação dos dados: análise bioclimática e da qualidade do ar, e estimativa dos padrões de conforto térmico ambiental. As variáveis bioclimáticas T (ºC, UR (%, Tgn (ºC e fisiológicas, taxa respiratória (mov min-1 e temperatura retal (ºC apontam o sistema de confinamento em baias coletivas como o que possibilitou melhor condicionamento térmico natural às matrizes em gestação. O uso da teoria dos conjuntos fuzzy permitiu que se fizesse inferência entre os dados resultantes do trabalho experimental com os estabelecidos pela literatura, por intermédio de base de regras, para a determinação do conforto ambiental aplicado a matrizes na fase de gestação.The objective of this research was to estimate the environment of housing systems for pregnant sows, as well as variables that have effect on production system. The trial was conducted out from January 4th to March 11th 2005 in a specialized farm in industrial production of pork, located in Elias Fausto City, São Paulo State. In gestation facility 24 gilts were allocated: 12 in individual stalls (T1 and 12 in group housing (T2. Basically, this study was divided in two steps in function of the way chosen for data analysis: bioclimatic and air quality analysis; and prediction for environmental thermal comfort patterns. The environmental variables (T, ºC; UR, %; Tgn, ºC and physiological (respiratory rate, mov min-1; rectal temperature

  18. On Fuzzy Simplex and Fuzzy Convex Hull

    Institute of Scientific and Technical Information of China (English)

    Dong QIU; Wei Quan ZHANG

    2011-01-01

    In this paper,we discuss fuzzy simplex and fuzzy convex hull,and give several representation theorems for fuzzy simplex and fuzzy convex hull.In addition,by giving a new characterization theorem of fuzzy convex hull,we improve some known results about fuzzy convex hull.

  19. The Fuzzy Set by Fuzzy Interval

    OpenAIRE

    Dr.Pranita Goswami

    2011-01-01

    Fuzzy set by Fuzzy interval is atriangular fuzzy number lying between the two specified limits. The limits to be not greater than 2 and less than -2 by fuzzy interval have been discussed in this paper. Through fuzzy interval we arrived at exactness which is a fuzzymeasure and fuzzy integral

  20. Fuzzy Riesz subspaces, fuzzy ideals, fuzzy bands and fuzzy band projections

    OpenAIRE

    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.

  1. On the Fuzzy Convergence

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    Abdul Hameed Q. A. Al-Tai

    2011-01-01

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

  2. Fuzzy logic

    Science.gov (United States)

    Zadeh, Lofti A.

    1988-01-01

    The author presents a condensed exposition of some basic ideas underlying fuzzy logic and describes some representative applications. The discussion covers basic principles; meaning representation and inference; basic rules of inference; and the linguistic variable and its application to fuzzy control.

  3. Fuzzy promises

    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...

  4. First course in fuzzy logic

    CERN Document Server

    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

  5. Fuzzy Set Approximations in Fuzzy Formal Contexts

    Institute of Scientific and Technical Information of China (English)

    Mingwen Shao; Shiqing Fan

    2006-01-01

    In this paper, a kind of multi-level formal concept is introduced. Based on the proposed multi-level formal concept, we present a pair of rough fuzzy set approximations within fuzzy formal contexts. By the proposed rough fuzzy set approximations, we can approximate a fuzzy set according to different precision level. We discuss the properties of the proposed approximation operators in detail.

  6. Fuzzy Clustering

    DEFF Research Database (Denmark)

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

    2000-01-01

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

  7. Fuzzy jets

    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.

  8. The Partial Fuzzy Set

    OpenAIRE

    Dr.Pranita Goswami

    2011-01-01

    The Partial Fuzzy Set is a portion of the Fuzzy Set which is again a Fuzzy Set. In the Partial Fuzzy Set the baseline is shifted from 0 to 1 to any of its α cuts . In this paper we have fuzzified a portion of the Fuzzy Set by transformation

  9. Properties of fuzzy hyperplanes

    Institute of Scientific and Technical Information of China (English)

    ZHANG Zhong; LI Chuandong; WU Deyin

    2004-01-01

    Some properties of closed fuzzy matroid and those of its hyperplanes are investigated. A fuzzy hyperplane property,which extends the analog of a crisp matroid from crisp set systems to fuzzy set systems, is proved.

  10. Intuitionistic Fuzzy Cycles and Intuitionistic Fuzzy Trees

    Science.gov (United States)

    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

  11. Gestão do pré-desenvolvimento de produto: estudo de casos na indústria de equipamentos médico-hospitalares Management of fuzzy front end: case studies in medical device industry

    Directory of Open Access Journals (Sweden)

    Glauco Henrique de Sousa Mendes

    2012-08-01

    Full Text Available O pré-desenvolvimento engloba as primeiras etapas do processo de desenvolvimento de novos produtos, nas quais as decisões são mais estratégicas e tomadas, geralmente, com alto grau de incerteza. O objetivo é analisar e discutir as práticas de gestão do pré-desenvolvimento em um conjunto de empresas de pequeno e médio portes da indústria de equipamentos médico-hospitalares. A análise é baseada num modelo conceitual, desenvolvido a partir da revisão bibliográfica, composto por cinco dimensões de gestão: orientação estratégica; processo; organização; avaliação; e ferramentas. A pesquisa de campo indica que as empresas estudadas apresentam deficiências na adoção e estruturação de boas práticas de gestão do pré-desenvolvimento. O modelo conceitual proposto serve de base para análise, estruturação e melhoria das atividades e do desempenho do pré-desenvolvimento.The fuzzy front end encompasses the first stages of new product development process. In that phase and period, the decisions are more strategic and are usually made with a high degree of uncertainty. This article aims to analyze and discuss the fuzzy front end management practices in small and medium medical device companies. The analysis is based on a conceptual model that was developed from the literature review and it consists of five dimensions of management: strategic orientation, process, organization, evaluation and tools. The results provide evidence that the studied companies have deficiencies in the adoption of best practices for managing the fuzzy front end, and the conceptual model suggested could serve as a basis for analysis, structuring and improving the fuzzy front end activities and performance.

  12. Some Additions to the Fuzzy Convergent and Fuzzy Bounded Sequence Spaces of Fuzzy Numbers

    OpenAIRE

    Şengönül, M.; Z. Zararsız

    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.

  13. Introduction to fuzzy systems

    CERN Document Server

    Chen, Guanrong

    2005-01-01

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

  14. Fuzziness in Chang's fuzzy topological spaces

    OpenAIRE

    1999-01-01

    It is known that fuzziness within the concept of openness of a fuzzy set in a Chang's fuzzy topological space (fts) is absent. In this paper we introduce a gradation of openness for the open sets of a Chang jts (X, $\\mathcal{T}$) by means of a map $\\sigma\\;:\\; I^{x}\\longrightarrow I\\left(I=\\left[0,1\\right]\\right)$, which is at the same time a fuzzy topology on X in Shostak 's sense. Then, we will be able to avoid the fuzzy point concept, and to introduce an adeguate theory f...

  15. Representation Theorems for Fuzzy Random Sets and Fuzzy Stochastic Processes

    Institute of Scientific and Technical Information of China (English)

    1999-01-01

    The fuzzy static and dynamic random phenomena in an abstract separable Banach space is discussed in this paper. The representation theorems for fuzzy set-valued random sets, fuzzy random elements and fuzzy set-valued stochastic processes are obtained.

  16. Fuzzy associative memories

    Science.gov (United States)

    Kosko, Bart

    1991-01-01

    Mappings between fuzzy cubes are discussed. This level of abstraction provides a surprising and fruitful alternative to the propositional and predicate-calculas reasoning techniques used in expert systems. It allows one to reason with sets instead of propositions. Discussed here are fuzzy and neural function estimators, neural vs. fuzzy representation of structured knowledge, fuzzy vector-matrix multiplication, and fuzzy associative memory (FAM) system architecture.

  17. Fuzzy Soft Topological Groups

    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.

  18. Intuitionistic supra fuzzy topological spaces

    Energy Technology Data Exchange (ETDEWEB)

    Abbas, S.E. E-mail: sabbas73@yahoo.com

    2004-09-01

    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.

  19. Fuzzy logic in management

    CERN Document Server

    Carlsson, Christer; Fullér, Robert

    2004-01-01

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

  20. Hesitant fuzzy sets theory

    CERN Document Server

    Xu, Zeshui

    2014-01-01

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

  1. The inspection of equipment in the Amazon region: from ACFM to electronic PIG in Urucu; A inspecao de equipamentos na Amazonia: do ACFM ao pig instrumentado em Urucu

    Energy Technology Data Exchange (ETDEWEB)

    Mac-Culloch, Joao Nazareth Lafayette de Mello [PETROBRAS S.A., Salvador, BA (Brazil). Exploracao e Producao. Unidade de Servicos de Sondagem Auto-Elevatoria; Beuren, Jair; Quadrado, Flavio Emir; Dunham, Paulo Cezar da Costa Lino [PETROBRAS S.A., Manaus, AM (Brazil). Exploracao e Producao. Unidade de Negocio da Bacia do Solimoes

    2003-07-01

    This paper presents the historical evolution of the activity of equipment inspection of the PETROBRAS/UN-BSOL, in which the developments of a motivation program of the personnel from the effort developed for the certification of inspectors since the techniques more known most modern for the examination of installations and equipment was of great importance. PETROBRAS was introduced in the ACFM by TSC-Technical Software Consultants, during NDT (Non Destructive Test) Congress in 1994. PETROBRAS/UN-BSOL was the first unit to acquire the last equipment, called Amigo. In 2002 has qualified three professionals to ACFM level I. Nowadays, five inspectors level I and one level II and the technique has been used through inspections in several equipment with very well satisfactory. The Duto de Coleta de oleo de LUC de 10in and the Duto de Coleta de gas de LUC de 14in had been inspected with the PIG using the technique of Magnetic flux leakage (MFL), being that in the first one it was used Quantitative Smart PIG (High Resolution) and in as it was used Qualitative Smart PIG (Low Resolution). The results show that, despite the raised cost of the High Resolution PIG, this still is indicated for in-line inspection of pipelines of the UN-BSOL. (author)

  2. 3 D localization system for inspection activities in metallic plates; Sistema de localizacao em tres dimensoes para auxilio na atividade de inspecao em chapas metalicas

    Energy Technology Data Exchange (ETDEWEB)

    Bonacin, Mario Vicente; Polli, Helton Luis; Czaikowski, Daniel Irineu; Arruda, Lucia Valeria Ramos de; Neves Junior, Flavio; Oliveira, Daniel Rossato de [Universidade Tecnologica Federal do Parana (UTFPR), Curitiba, Parana (Brazil)

    2008-07-01

    This work presents the development of a 3D localization system based on inertial sensors. The prototype aims for its application in the oil and gas industry, which presents deficiencies on automation of inspection procedures. Recent advances on the field of Nondestructive Testing (NDT) have contributed to automation of these inspections, but installation and removal of NDT equipment, as well as location measurements and data acquired processing, are still highly dependent on labour-human. However, only the double integration of data from the inertial sensors - position determination - does not reach the precision level required by inspection activity. It requires the use of techniques and methods to minimize errors. Different models and techniques can be applied to minimize these undesired effects in addition with filters as the Kalman filter, widely used on problems of estimation of trajectories and fusion of sensors. This paper presents the modeling and implementation of some of these techniques, obtaining interesting results. (author)

  3. Inspection of the brazilian nuclear regulatory body in the area of radiotherapy. A critical analysis; Inspecao do orgao regulador nuclear brasileiro na area de radioterapia. Uma analise critica

    Energy Technology Data Exchange (ETDEWEB)

    Brito, Ricardo Roberto de Azevedo

    2005-07-01

    The National Commission of Nuclear Energy (CNEN) is responsible in Brazil for the activities of licensing and control of radioactive installations in the radiotherapy medical area. The majority of these activities are developed by CNEN Co-ordination of Radioactive Installations (CORAD). One of the necessary stages for the development of licensing and control activities is the inspection of radiotherapy services (clinics and hospitals). Almost all of these inspections are carried out by CNEN Inst. of Radiation Protection and Dosimetry (IRD), through its Service of Medical Physics in Radiotherapy and Nuclear Medicine (SEFME). This work makes a survey of the main nonconformities found during ten years of inspections in radiotherapy services (1995 - 2004) and analyses the efficiency of these inspections in making the radiotherapy services develop their activities according to the norms in vigour in the country and adopt corrective actions against, at least, the nonconformities evidenced by CNEN inspectors. Additionally, it analyses the possibility of improvement and / or the optimisation of the process, through a procedure able to be unified and controlled, aiming a prompt communication to those involved in the licensing process (SEFME and CORAD) about the attendance by the radiotherapy services to the non-conformity items observed during the inspection. (author)

  4. Inspection of non-piggable pipelines at PETROBRAS-UN Bahia; Inspecao de dutos nao-pigaveis na PETROBRAS-UN Bahia

    Energy Technology Data Exchange (ETDEWEB)

    Alves, Luis F.C.; Lopes, Paulo R. [PETROBRAS, Salvador, BA (Brazil). Unidade de Negocios da Bahia

    2005-07-01

    PETROBRAS has made a huge effort to inspect and rehabilitate its pipeline net, mainly over the past 10 years. Currently, E and P inspection teams are being challenged to find feasible solutions for the inspection of non-piggable pipelines, so named because they have unsuitable geometry and/or operating conditions for usual in-line inspections. Inside this pipeline category, flow lines, injection and distribution lines and even non-metallic pipelines may be highlighted. This paper presents the results of tests and developments of new inspection tools for the inspection of non piggable pipelines, future tests to be performed in PETROBRAS/E and P Bahia (UN-BA) and some inspection cases in which the operating conditions hinder the run of smart pigs. (author)

  5. Transformation and entropy for fuzzy rough sets

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    A new method for translating a fuzzy rough set to a fuzzy set is introduced and the fuzzy approximation of a fuzzy rough set is given.The properties of the fuzzy approximation of a fuzzy rough set are studied and a fuzzy entropy measure for fuzzy rough sets is proposed.This measure is consistent with similar considerations for ordinary fuzzy sets and is the result of the fuzzy approximation of fuzzy rough sets.

  6. Boolean Operator Fuzzy Logic

    Institute of Scientific and Technical Information of China (English)

    刘叙华; 邓安生

    1994-01-01

    A new approach of operator fuzzy logic, Boolean operator fuzzy logic (BOFL) based on Boolean algebra, is presented. The resolution principle is also introduced into BOFL. BOFL is a natural generalization of classical logic and can be applied to the qualitative description of fuzzy knowledge.

  7. Paired fuzzy sets

    DEFF Research Database (Denmark)

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

    2015-01-01

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

  8. Fuzzy Linguistic Topological Spaces

    CERN Document Server

    Kandasamy, W B Vasantha; Amal, K

    2012-01-01

    This book has five chapters. Chapter one is introductory in nature. Fuzzy linguistic spaces are introduced in chapter two. Fuzzy linguistic vector spaces are introduced in chapter three. Chapter four introduces fuzzy linguistic models. The final chapter suggests over 100 problems and some of them are at research level.

  9. Fuzzy Logic Engine

    Science.gov (United States)

    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.

  10. Some weakly mappings on intuitionistic fuzzy topological spaces

    OpenAIRE

    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.

  11. Countable Fuzzy Topological Space and Countable Fuzzy Topological Vector Space

    Directory of Open Access Journals (Sweden)

    Apu Kumar Saha

    2015-06-01

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

  12. Mathematics of Fuzzy Sets and Fuzzy Logic

    CERN Document Server

    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...

  13. How we pass from fuzzy $po$-semigroups to fuzzy $po$-$\\Gamma$-semigroups

    OpenAIRE

    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.

  14. STATISTICS OF FUZZY DATA

    Directory of Open Access Journals (Sweden)

    Orlov A. I.

    2016-05-01

    Full Text Available Fuzzy sets are the special form of objects of nonnumeric nature. Therefore, in the processing of the sample, the elements of which are fuzzy sets, a variety of methods for the analysis of statistical data of any nature can be used - the calculation of the average, non-parametric density estimators, construction of diagnostic rules, etc. We have told about the development of our work on the theory of fuzziness (1975 - 2015. In the first of our work on fuzzy sets (1975, the theory of random sets is regarded as a generalization of the theory of fuzzy sets. In non-fiction series "Mathematics. Cybernetics" (publishing house "Knowledge" in 1980 the first book by a Soviet author fuzzy sets is published - our brochure "Optimization problems and fuzzy variables". This book is essentially a "squeeze" our research of 70-ies, ie, the research on the theory of stability and in particular on the statistics of objects of non-numeric nature, with a bias in the methodology. The book includes the main results of the fuzzy theory and its note to the random set theory, as well as new results (first publication! of statistics of fuzzy sets. On the basis of further experience, you can expect that the theory of fuzzy sets will be more actively applied in organizational and economic modeling of industry management processes. We discuss the concept of the average value of a fuzzy set. We have considered a number of statements of problems of testing statistical hypotheses on fuzzy sets. We have also proposed and justified some algorithms for restore relationships between fuzzy variables; we have given the representation of various variants of fuzzy cluster analysis of data and variables and described some methods of collection and description of fuzzy data

  15. On generalized fuzzy strongly semiclosed sets in fuzzy topological spaces

    Directory of Open Access Journals (Sweden)

    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.

  16. EXTENSION OF THE PROJECTION THEOREM ON HILBERT SPACE TO FUZZY HILBERT SPACE OVER FUZZY NUMBER SPACE

    OpenAIRE

    K. P. DEEPA; Dr.S.Chenthur Pandian

    2012-01-01

    In this paper, we extend the projection theorem on Hilbert space to its fuzzy version over fuzzy number space embedded with fuzzy number mapping. To prove this we discuss the concepts of fuzzy Hilbert space over fuzzy number space with fuzzy number mapping. The fuzzy orthogonality, fuzzy orthonormality, fuzzy complemented subset property etc. of fuzzy Hilbert space over fuzzy number space using fuzzy number mapping also been discussed.

  17. On fuzzy weakly-closed sets

    OpenAIRE

    Mahanta, J.; P. K. Das

    2012-01-01

    A new class of fuzzy closed sets, namely fuzzy weakly closed set in a fuzzy topological space is introduced and it is established that this class of fuzzy closed sets lies between fuzzy closed sets and fuzzy generalized closed sets. Alongwith the study of fundamental results of such closed sets, we define and characterize fuzzy weakly compact space and fuzzy weakly closed space.

  18. Compactness in intuitionistic fuzzy topological spaces

    Directory of Open Access Journals (Sweden)

    S. E. Abbas

    2005-02-01

    Full Text Available We introduce fuzzy almost continuous mapping, fuzzy weakly continuous mapping, fuzzy compactness, fuzzy almost compactness, and fuzzy near compactness in intuitionistic fuzzy topological space in view of the definition of Å ostak, and study some of their properties. Also, we investigate the behavior of fuzzy compactness under several types of fuzzy continuous mappings.

  19. Fuzzy social choice theory

    CERN Document Server

    B Gibilisco, Michael; E Albert, Karen; N Mordeson, John; J Wierman, Mark; D Clark, Terry

    2014-01-01

    This book offers a comprehensive analysis of the social choice literature and shows, by applying fuzzy sets, how the use of fuzzy preferences, rather than that of strict ones, may affect the social choice theorems. To do this, the book explores the presupposition of rationality within the fuzzy framework and shows that the two conditions for rationality, completeness and transitivity, do exist with fuzzy preferences. Specifically, this book examines: the conditions under which a maximal set exists; the Arrow’s theorem;  the Gibbard-Satterthwaite theorem; and the median voter theorem.  After showing that a non-empty maximal set does exists for fuzzy preference relations, this book goes on to demonstrating the existence of a fuzzy aggregation rule satisfying all five Arrowian conditions, including non-dictatorship. While the Gibbard-Satterthwaite theorem only considers individual fuzzy preferences, this work shows that both individuals and groups can choose alternatives to various degrees, resulting in a so...

  20. 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.

  1. Vector-valued fuzzy multifunctions

    Directory of Open Access Journals (Sweden)

    Ismat Beg

    2001-01-01

    Full Text Available Some of the properties of vector-valued fuzzy multifunctions are studied. The notion of sum fuzzy multifunction, convex hull fuzzy multifunction, close convex hull fuzzy multifunction, and upper demicontinuous are given, and some of the properties of these fuzzy multifunctions are investigated.

  2. Approximate Reasoning with Fuzzy Booleans

    NARCIS (Netherlands)

    Broek, van den P.M.; Noppen, J.A.R.

    2004-01-01

    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 ante

  3. Fuzzy Sets and Mathematical Education.

    Science.gov (United States)

    Alsina, C.; Trillas, E.

    1991-01-01

    Presents the concept of "Fuzzy Sets" and gives some ideas for its potential interest in mathematics education. Defines what a Fuzzy Set is, describes why we need to teach fuzziness, gives some examples of fuzzy questions, and offers some examples of activities related to fuzzy sets. (MDH)

  4. Uma abordagem heurística para a programação da produção na indústria de fundição com utilização da lógica fuzzy A heuristic approach for production scheduling in the foundry industry using fuzzy logic

    Directory of Open Access Journals (Sweden)

    Raul Landmann

    2011-01-01

    Full Text Available Este artigo descreve a concepção, desenvolvimento e aplicação de uma metodologia para a programação da produção na indústria de fundição. Há dois momentos importantes e interligados, que são a programação do forno e a programação das máquinas de moldagem. O problema consiste em determinar um sequenciamento adequado de ordens de produção nas linhas de moldagem, combinando peças leves com peças de peso médio e com peças pesadas, de modo a obter uma demanda constante de metal líquido, em equilíbrio com a oferta de metal proveniente do forno. Foi adotada a abordagem heurística para a solução, com utilização da lógica fuzzy, que oferece mecanismos para a representação e manipulação do conhecimento de especialistas, identificado em uma pesquisa qualitativa. Os resultados da aplicação demonstraram, além dos benefícios da sistematização do conhecimento e da capacidade de realizar simulações com muita rapidez, um desempenho mais eficiente que o obtido pelos profissionais da fundição.This article describes the conception, development, and application of a methodology for the production scheduling in the foundry industry. There are two important and related situations involved, which are the furnace scheduling and the molding machine scheduling. The problem consists in determining an adequate sequencing of production orders in the molding line combining light weight parts with medium and heavy parts in order to obtain a constant demand of molten metal balanced with the offer of furnace derived metal. The heuristic approach was chosen to find a solution to the problem, and using fuzzy logic technique, which allows modeling complex systems using a higher level of abstraction originating from knowledge and experience identified in a qualitative research. The results demonstrated, besides the benefits of the knowledge systematization and the capacity to run quick simulations in order to find the best alternatives

  5. On fuzzy almost continuous convergence in fuzzy function spaces

    Directory of Open Access Journals (Sweden)

    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.

  6. A New Type Fuzzy Module over Fuzzy Rings

    Directory of Open Access Journals (Sweden)

    Ece Yetkin

    2014-01-01

    Full Text Available A new kind of fuzzy module over a fuzzy ring is introduced by generalizing Yuan and Lee’s definition of the fuzzy group and Aktaş and Çağman’s definition of fuzzy ring. The concepts of fuzzy submodule, and fuzzy module homomorphism are studied and some of their basic properties are presented analogous of ordinary module theory.

  7. Decision making with fuzzy probability assessments and fuzzy payoff

    Institute of Scientific and Technical Information of China (English)

    Song Yexin; Yin Di; Chen Mianyun

    2005-01-01

    A novel method for decision making with fuzzy probability assessments and fuzzy payoff is presented. The consistency of the fuzzy probability assessment is considered. A fuzzy aggregate algorithm is used to indicate the fuzzy expected payoff of alternatives. The level sets of each fuzzy expected payoff are then obtained by solving linear programming models. Based on a defuzzification function associated with the level sets of fuzzy number and a numerical integration formula (Newton-Cotes formula), an effective approach to rank the fuzzy expected payoff of alternatives is also developed to determine the best alternative. Finally, a numerical example is provided to illustrate the proposed method.

  8. Generation of fuzzy mathematical morphologies

    OpenAIRE

    2001-01-01

    Fuzzy Mathematical Morphology aims to extend the binary morphological operators to grey-level images. In order to define the basic morphological operations fuzzy erosion, dilation, opening and closing, we introduce a general method based upon fuzzy implication and inclusion grade operators, including as particular case, other ones existing in related literature In the definition of fuzzy erosion and dilation we use several fuzzy implications (Annexe A, Table of fuzzy implic...

  9. Introduction to Fuzzy Set Theory

    Science.gov (United States)

    Kosko, Bart

    1990-01-01

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

  10. Application of data representation by fuzzy conditional propositions in the modeling of measurement uncertainty; Aplicacao da representacao de dados por proposicoes condicionais difusas na modelagem da incerteza de medicao

    Energy Technology Data Exchange (ETDEWEB)

    Magalhaes, A.N. de; Lambert-Torres, G.; Rissino, S.; Silva, M.F. da; Silva, L.E. Borges da; Carvalho, L.M.R. de

    2009-07-01

    It is not an easy task to frame uncertainty measurement problems by means of differential equations quickly and satisfactorily. Therefore, it is necessary to adapt the method for data representation by conditional fuzzy propositions for modeling uncertainties measurement and their effect on the propagation. This method provides a parametric adjustment for fuzzy sets of assumptions, and the functions of consequence of each rule in the manner of a parable. The paper introduces concepts of sources of errors in measures, fundamentals of fuzzy logic, description of the algorithm method, application to error detection and representation of global uncertainty.

  11. The fuzzy space construction kit

    CERN Document Server

    Sykora, Andreas

    2016-01-01

    Fuzzy spaces like the fuzzy sphere or the fuzzy torus have received remarkable attention, since they appeared as objects in string theory. Although there are higher dimensional examples, the most known and most studied fuzzy spaces are realized as matrix algebras defined by three Hermitian matrices, which may be seen as fuzzy membrane or fuzzy surface. We give a mapping between directed graphs and matrix algebras defined by three Hermitian matrices and show that the matrix algebras of known two-dimensional fuzzy spaces are associated with unbranched graphs. By including branchings into the graphs we find matrix algebras that represent fuzzy spaces associated with surfaces having genus 2 and higher.

  12. Fuzzy Model for Trust Evaluation

    Institute of Scientific and Technical Information of China (English)

    Zhang Shibin; He Dake

    2006-01-01

    Based on fuzzy set theory, a fuzzy trust model is established by using membership function to describe the fuzziness of trust. The trust vectors of subjective trust are obtained based on a mathematical model of fuzzy synthetic evaluation. Considering the complicated and changeable relationships between various subjects, the multi-level mathematical model of fuzzy synthetic evaluation is introduced. An example of a two-level fuzzy synthetic evaluation model confirms the feasibility of the multi-level fuzzy synthesis evaluation model. The proposed fuzzy model for trust evaluation may provide a promising method for research of trust model in open networks.

  13. Intuitionistic fuzzy calculus

    CERN Document Server

    Lei, Qian

    2017-01-01

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

  14. Foundations Of Fuzzy Control

    DEFF Research Database (Denmark)

    Jantzen, Jan

    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......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...

  15. Foundations Of Fuzzy Control

    DEFF Research Database (Denmark)

    Jantzen, Jan

    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......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...... 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...

  16. Ciclo de vida organizacional pautado no modelo de Lester, Parnell e Carraher (2003 e na lógica fuzzy: classificação de empresas de um segmento industrial de Santa Catarina

    Directory of Open Access Journals (Sweden)

    Ilse Maria Beuren

    2012-06-01

    Full Text Available Neste estudo, objetiva-se identificar os estágios do ciclo de vida organizacional pautados no modelo de Lester, Parnell e Carraher (2003 das empresas do segmento industrial de máquinas, aparelhos e materiais elétricos do estado de Santa Catarina. Pesquisa descritiva, com abordagem quantitativa, foi realizada por meio de levantamento com aplicação de questionário aos gestores das empresas. A população constituiu-se das 264 empresas desse segmento econômico, listadas na Secretaria da Fazenda do Estado de Santa Catarina, e a amostra não aleatória das 40 empresas que responderam a pesquisa. As variáveis de identificação dos estágios de ciclo de vida utilizadas no questionário foram extraídas de Lester, Parnell e Carraher (2003. Os dados da pesquisa foram submetidos à técnica estatística denominada lógica fuzzy. Os resultados da pesquisa demonstraram que 57,5% das empresas foram classificadas no estágio do nascimento, 15% do, 7,5% da Maturidade, 10% do rejuvenescimento e 10% do declínio. Concluiu-se que determinados estágios do ciclo de vida organizacional estão próximos uns dos outros e que não se pode perceber claramente uma progressão determinista nas fases do ciclo de vida, como uma sequência única, definitiva e irreversível, no sentido tradicional biológico.

  17. Metamathematics of fuzzy logic

    CERN Document Server

    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.

  18. Fuzzy Control Tutorial

    DEFF Research Database (Denmark)

    Dotoli, M.; Jantzen, Jan

    1999-01-01

    The tutorial concerns automatic control of an inverted pendulum, especially rule based control by means of fuzzy logic. A ball balancer, implemented in a software simulator in Matlab, is used as a practical case study. The objectives of the tutorial are to teach the basics of fuzzy control......, and to show how to apply fuzzy logic in automatic control. The tutorial is distance learning, where students interact one-to-one with the teacher using e-mail....

  19. Fuzzy Control Tutorial

    DEFF Research Database (Denmark)

    Dotoli, M.; Jantzen, Jan

    1999-01-01

    The tutorial concerns automatic control of an inverted pendulum, especially rule based control by means of fuzzy logic. A ball balancer, implemented in a software simulator in Matlab, is used as a practical case study. The objectives of the tutorial are to teach the basics of fuzzy control, and t......, 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....

  20. Design of Fuzzy Controllers

    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 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....

  1. Intuitionistic fuzzy logics

    CERN Document Server

    T Atanassov, Krassimir

    2017-01-01

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

  2. AUV fuzzy neural BDI

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    The typical BDI (belief desire intention) model of agent is not efficiently computable and the strict logic expression is not easily applicable to the AUV (autonomous underwater vehicle) domain with uncertainties. In this paper, an AUV fuzzy neural BDI model is proposed. The model is a fuzzy neural network composed of five layers: input ( beliefs and desires) , fuzzification, commitment, fuzzy intention, and defuzzification layer. In the model, the fuzzy commitment rules and neural network are combined to form intentions from beliefs and desires. The model is demonstrated by solving PEG (pursuit-evasion game), and the simulation result is satisfactory.

  3. RANDOM VARIABLE WITH FUZZY PROBABILITY

    Institute of Scientific and Technical Information of China (English)

    吕恩琳; 钟佑明

    2003-01-01

    Mathematic description about the second kind fuzzy random variable namely the random variable with crisp event-fuzzy probability was studied. Based on the interval probability and using the fuzzy resolution theorem, the feasible condition about a probability fuzzy number set was given, go a step further the definition arid characters of random variable with fuzzy probability ( RVFP ) and the fuzzy distribution function and fuzzy probability distribution sequence of the RVFP were put forward. The fuzzy probability resolution theorem with the closing operation of fuzzy probability was given and proved. The definition and characters of mathematical expectation and variance of the RVFP were studied also. All mathematic description about the RVFP has the closing operation for fuzzy probability, as a result, the foundation of perfecting fuzzy probability operation method is laid.

  4. Relations Among Some Fuzzy Entropy Formulae

    Institute of Scientific and Technical Information of China (English)

    卿铭

    2004-01-01

    Fuzzy entropy has been widely used to analyze and design fuzzy systems, and many fuzzy entropy formulae have been proposed. For further in-deepth analysis of fuzzy entropy, the axioms and some important formulae of fuzzy entropy are introduced. Some equivalence results among these fuzzy entropy formulae are proved, and it is shown that fuzzy entropy is a special distance measurement.

  5. Results on fuzzy soft topological spaces

    CERN Document Server

    Mahanta, J

    2012-01-01

    B. Tanay et. al. introduced and studied fuzzy soft topological spaces. Here we introduce fuzzy soft point and study the concept of neighborhood of a fuzzy soft point in a fuzzy soft topological space. We also study fuzzy soft closure and fuzzy soft interior. Separation axioms and connectedness are introduced and investigated for fuzzy soft topological spaces.

  6. Some properties of fuzzy soft proximity spaces.

    Science.gov (United States)

    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.

  7. Some Properties of Fuzzy Soft Proximity Spaces

    Science.gov (United States)

    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

  8. 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.

  9. Properties of Bipolar Fuzzy Hypergraphs

    OpenAIRE

    M. Akram; 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.

  10. Fuzzy Markov chains: uncertain probabilities

    OpenAIRE

    2002-01-01

    We consider finite Markov chains where there are uncertainties in some of the transition probabilities. These uncertainties are modeled by fuzzy numbers. Using a restricted fuzzy matrix multiplication we investigate the properties of regular, and absorbing, fuzzy Markov chains and show that the basic properties of these classical Markov chains generalize to fuzzy Markov chains.

  11. Achieving of Fuzzy Automata for Processing Fuzzy Logic

    Institute of Scientific and Technical Information of China (English)

    SHU Lan; WU Qing-e

    2005-01-01

    At present, there has been an increasing interest in neuron-fuzzy systems, the combinations of artificial neural networks with fuzzy logic. In this paper, a definition of fuzzy finite state automata (FFA) is introduced and fuzzy knowledge equivalence representations between neural networks, fuzzy systems and models of automata are discussed. Once the network has been trained, we develop a method to extract a representation of the FFA encoded in the recurrent neural network that recognizes the training rules.

  12. Entropy of Fuzzy Partitions and Entropy of Fuzzy Dynamical Systems

    Directory of Open Access Journals (Sweden)

    Dagmar Markechová

    2016-01-01

    Full Text Available In the paper we define three kinds of entropy of a fuzzy dynamical system using different entropies of fuzzy partitions. It is shown that different definitions of the entropy of fuzzy partitions lead to different notions of entropies of fuzzy dynamical systems. The relationships between these entropies are studied and connections with the classical case are mentioned as well. Finally, an analogy of the Kolmogorov–Sinai Theorem on generators is proved for fuzzy dynamical systems.

  13. Tutorial On Fuzzy Logic

    DEFF Research Database (Denmark)

    Jantzen, Jan

    1998-01-01

    A logic based on the two truth values True and False is sometimes inadequate when describing human reasoning. Fuzzy logic uses the whole interval between 0 (False) and 1 (True) to describe human reasoning. As a result, fuzzy logic is being applied in rule based automatic controllers, and this paper...

  14. Extended Fuzzy Clustering Algorithms

    NARCIS (Netherlands)

    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 fuz

  15. Statistical Methods for Fuzzy Data

    CERN Document Server

    Viertl, Reinhard

    2011-01-01

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

  16. Axiomatic of Fuzzy Complex Numbers

    OpenAIRE

    Angel Garrido

    2012-01-01

    Fuzzy numbers are fuzzy subsets of the set of real numbers satisfying some additional conditions. Fuzzy numbers allow us to model very difficult uncertainties in a very easy way. Arithmetic operations on fuzzy numbers have also been developed, and are based mainly on the crucial Extension Principle. When operating with fuzzy numbers, the results of our calculations strongly depend on the shape of the membership functions of these numbers. Logically, less regular membership functions may lead ...

  17. MODELING FUZZY GEOGRAPHIC OBJECTS WITHIN FUZZY FIELDS

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    To improve the current GIS functions in describing geographic objects w ith fuzziness,this paper begins with a discussion on the distance measure of sp atial objects based on the theory of sets and an introduction of dilation and er osion operators.Under the assumption that changes of attributes in a geographic region are gradual,the analytic expressions for the fuzzy objects of points,l ines and areas,and the description of their formal structures are presented.Th e analytic model of geographic objects by means of fuzzy fields is developed.We have shown that the 9-intersection model proposed by Egenhofer and Franzosa (19 91) is a special case of the model presented in the paper.

  18. Super Fuzzy Matrices and Super Fuzzy Models for Social Scientists

    CERN Document Server

    Kandasamy, W B Vasantha; Amal, K

    2008-01-01

    This book introduces the concept of fuzzy super matrices and operations on them. This book will be highly useful to social scientists who wish to work with multi-expert models. Super fuzzy models using Fuzzy Cognitive Maps, Fuzzy Relational Maps, Bidirectional Associative Memories and Fuzzy Associative Memories are defined here. The authors introduce 13 multi-expert models using the notion of fuzzy supermatrices. These models are described with illustrative examples. This book has three chapters. In the first chaper, the basic concepts about super matrices and fuzzy super matrices are recalled. Chapter two introduces the notion of fuzzy super matrices adn their properties. The final chapter introduces many super fuzzy multi expert models.

  19. Fuzzy Dot Structure of BG-algebras

    Directory of Open Access Journals (Sweden)

    Tapan Senapati

    2014-09-01

    Full Text Available In this paper, the notions of fuzzy dot subalgebras is introduced together with fuzzy normal dot subalgebras and fuzzy dot ideals of BG-algebras. The homomorphic image and inverse image are investigated in fuzzy dot subalgebras and fuzzy dot ideals of BG-algebras. Also, the notion of fuzzy relations on the family of fuzzy dot subalgebras and fuzzy dot ideals of BG-algebras are introduced with some related properties.

  20. Structural Holes in Directed Fuzzy Social Networks

    OpenAIRE

    Renjie Hu; Guangyu Zhang

    2014-01-01

    The structural holes have been a key issue in fuzzy social network analysis. For undirected fuzzy social networks where edges are just present or absent undirected fuzzy relation and have no more information attached, many structural holes measures have been presented, such as key fuzzy structural holes, general fuzzy structural holes, strong fuzzy structural holes, and weak fuzzy structural holes. There has been a growing need to design structural holes measures for directed fuzzy social net...

  1. The Fuzzy Supersphere

    CERN Document Server

    Grosse, Harald; Grosse, Harald; Reiter, Gert

    1998-01-01

    We introduce the fuzzy supersphere as sequence of finite-dimensional, noncommutative $Z_{2}$-graded algebras tending in a suitable limit to a dense subalgebra of the $Z_{2}$-graded algebra of ${\\cal H}^{\\infty}$-functions on the $(2| 2)$-dimensional supersphere. Noncommutative analogues of the body map (to the (fuzzy) sphere) and the super-deRham complex are introduced. In particular we reproduce the equality of the super-deRham cohomology of the supersphere and the ordinary deRham cohomology of its body on the "fuzzy level".

  2. A fuzzy disaggregation technique

    Directory of Open Access Journals (Sweden)

    Alessandro Polli

    2013-05-01

    Full Text Available The aim of this paper is to analyze a problem of time series disaggregation in presence of broad information lack. In this framework it is not possible to follow standard methodologies, like those stemming from the Chow and Lin algorithm and based on probabilistic assumptions. In general terms, when information sets are limited, instead of referring to probabilistic measures it could be more appropriate to adopt an uncertainty measure satisfying only some general properties, like the fuzzy one. After a synthetic survey about fuzzy aggregation operators, we introduce a fuzzy disaggregation technique, based on Choquet capacity theory and characterized by De Finetti coherence.

  3. A Novel Weak Fuzzy Solution for Fuzzy Linear System

    Directory of Open Access Journals (Sweden)

    Soheil Salahshour

    2016-03-01

    Full Text Available This article proposes a novel weak fuzzy solution for the fuzzy linear system. As a matter of fact, we define the right-hand side column of the fuzzy linear system as a piecewise fuzzy function to overcome the related shortcoming, which exists in the previous findings. The strong point of this proposal is that the weak fuzzy solution is always a fuzzy number vector. Two complex and non-complex linear systems under uncertainty are tested to validate the effectiveness and correctness of the presented method.

  4. Fuzzy Modeling for Uncertainty Nonlinear Systems with Fuzzy Equations

    Directory of Open Access Journals (Sweden)

    Raheleh Jafari

    2017-01-01

    Full Text Available The uncertain nonlinear systems can be modeled with fuzzy equations by incorporating the fuzzy set theory. In this paper, the fuzzy equations are applied as the models for the uncertain nonlinear systems. The nonlinear modeling process is to find the coefficients of the fuzzy equations. We use the neural networks to approximate the coefficients of the fuzzy equations. The approximation theory for crisp models is extended into the fuzzy equation model. The upper bounds of the modeling errors are estimated. Numerical experiments along with comparisons demonstrate the excellent behavior of the proposed method.

  5. Axiomatic of Fuzzy Complex Numbers

    Directory of Open Access Journals (Sweden)

    Angel Garrido

    2012-04-01

    Full Text Available Fuzzy numbers are fuzzy subsets of the set of real numbers satisfying some additional conditions. Fuzzy numbers allow us to model very difficult uncertainties in a very easy way. Arithmetic operations on fuzzy numbers have also been developed, and are based mainly on the crucial Extension Principle. When operating with fuzzy numbers, the results of our calculations strongly depend on the shape of the membership functions of these numbers. Logically, less regular membership functions may lead to very complicated calculi. Moreover, fuzzy numbers with a simpler shape of membership functions often have more intuitive and more natural interpretations. But not only must we apply the concept and the use of fuzzy sets, and its particular case of fuzzy number, but also the new and interesting mathematical construct designed by Fuzzy Complex Numbers, which is much more than a correlate of Complex Numbers in Mathematical Analysis. The selected perspective attempts here that of advancing through axiomatic descriptions.

  6. Homomorphic Properties of Fuzzy Rough Groups

    Institute of Scientific and Technical Information of China (English)

    QIN Ke-yun; ZHANG Xiao-hua

    2012-01-01

    This paper is devoted to the discussion of homomorphic properties of fuzzy rough groups.The fuzzy approximation space was generated by fuzzy normal subgroups and the fuzzy rough approximation operators were discussed in the frame of fuzzy rough set model.The basic properties of fuzzy rough approximation operators were obtained.

  7. Some Results on Fuzzy Soft Topological Spaces

    Directory of Open Access Journals (Sweden)

    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.

  8. Fuzzy Rough Ring and Its Prop erties

    Institute of Scientific and Technical Information of China (English)

    REN Bi-jun; FU Yan-ling

    2013-01-01

    This paper is devoted to the theories of fuzzy rough ring and its properties. The fuzzy approximation space generated by fuzzy ideals and the fuzzy rough approximation operators were proposed in the frame of fuzzy rough set model. The basic properties of fuzzy rough approximation operators were analyzed and the consistency between approximation operators and the binary operation of ring was discussed.

  9. Some Weaker Forms of Fuzzy Faintly Open Mappings

    OpenAIRE

    Hakeem A. Othman

    2015-01-01

    This paper is devoted to introduce and investigate some weak forms of fuzzy open mappings, namely fuzzy faintly semi open (fuzzy faintly semi closed), fuzzy faintly preopen (fuzzy faintly preclosed), fuzzy faintly $\\alpha$-open (fuzzy faintly $\\alpha$-closed), fuzzy faintly semi preopen (fuzzy faintly semi preclosed) and fuzzy faintly $sp$- open (fuzzy faintly $sp$- closed) mappings and their fundamental properties are obtained. Moreover, their relationship with other types of fuzzy open (clo...

  10. Fuzzy Sets, Fuzzy S-Open and S-Closed Mappings

    OpenAIRE

    Ahmad, B; Athar Kharal

    2009-01-01

    Several properties of fuzzy semiclosure and fuzzy semi-interior of fuzzy sets defined by Yalvac (1988), have been established and supported by counterexamples. We also study the characterizations and properties of fuzzy semi-open and fuzzy semi-closed sets. Moreover, we define fuzzy s-open and fuzzy s-closed mappings and give some interesting characterizations.

  11. Extended Fuzzy Logic Programs with Fuzzy Answer Set Semantics

    Science.gov (United States)

    Saad, Emad

    This paper extends fuzzy logic programs [12, 24] to allow the explicit representation of classical negation as well as non-monotonic negation, by introducing the notion of extended fuzzy logic programs. We present the fuzzy answer set semantics for the extended fuzzy logic programs, which is based on the classical answer set semantics of classical extended logic programs [7]. We show that the proposed semantics is a natural extension to the classical answer set semantics of classical extended logic programs [7]. Furthermore, we define fixpoint semantics for extended fuzzy logic programs with and without non-monotonic negation, and study their relationship to the fuzzy answer set semantics. In addition, we show that the fuzzy answer set semantics is reduced to the stable fuzzy model semantics for normal fuzzy logic programs introduced in [42]. The importance of that is computational methods developed for normal fuzzy logic programs can be applied to the extended fuzzy logic programs. Moreover, we show that extended fuzzy logic programs can be intuitively used for representing and reasoning about actions in fuzzy environment.

  12. Risk Assessment of Ammonia Tanks Using Fuzzy Layer of Protection Analysis (FLOPA

    Directory of Open Access Journals (Sweden)

    Mohsen Omidvar

    2016-03-01

    Full Text Available Introduction: Risk assessment of hazardous processes is the priority of risk management. Layer of protection analysis (LOPA is one of the most popular methods used for risk assessment. Due to the insufficient information or uncertainty in failure rates (PFD of protective layers, risk assessment based on the conventional LOPA can result in error in calculations. In this study, we tried to use the fuzzy set theory to evaluate the ammonia receiving tank safety, using the LOPA method. Methods: Initially, the fuzzy failure rate of protective layers were calculated using the subjective opinions of professionals. Then, by applying the fuzzy operators, fuzzy possibilities transformed to fuzzy probabilities and subsequently they were deffuzified to crisp failure rate. Afterwards, using the severity fuzzy logic, severity of the outcome event was calculated in the fuzzy form, and subsequently, fuzzy risk index was calculated using the fuzzy matrix. Results: In the ammonia release scenario, calculated severity, probability and risk levels were determined as P: Low, S: High, and R: TNA, and PF = -2.66, SF = 3.99, RF = 3.79 (0.2 TNA, 0.8 NA for classic and fuzzy LOPA methods, respectively. In addition, after inserting additional layers of protection, the fuzzy risk index reduced from 3.79 (0.2 TNA, 0.8 NA to 1.92 (0.1 A, 0.8 TA, 0.1 TNA. Conclusions: In the condition of uncertainty and lack of information relating to probability and severity of risk scenarios, the experts’ opinions can be used in forms of linguistic variables and fuzzy relations to reduce calculation errors in risk assessment as much as possible

  13. Fuzziness and Relevance Theory

    Institute of Scientific and Technical Information of China (English)

    Grace Qiao Zhang

    2005-01-01

    This paper investigates how the phenomenon of fuzzy language, such as `many' in `Mary has many friends', can be explained by Relevance Theory. It is concluded that fuzzy language use conforms with optimal relevance in that it can achieve the greatest positive effect with the least processing effort. It is the communicators themselves who decide whether or not optimal relevance is achieved, rather than the language form (fuzzy or non-fuzzy) used. People can skillfully adjust the deployment of different language forms or choose appropriate interpretations to suit different situations and communication needs. However, there are two challenges to RT: a. to extend its theory from individual relevance to group relevance; b. to embrace cultural considerations (because when relevance principles and cultural protocols are in conflict, the latter tends to prevail).

  14. Sobre multifunciones Fuzzy

    Directory of Open Access Journals (Sweden)

    Renato César Scarparo

    2002-01-01

    Full Text Available En este trabajo se presentan y demuestran algunos resultados de D.T. Luc y C, Vargas referentes a multifunciones con dominio y blanco en espacios vectoriales topológicos de Hausdorff sobre R, como así mismo se explícita el concepto de multifunción fuzzy de acuerdo a Papageogiou, y se demuestran dos teorema de S. S. Chag, con respecto a las multifunciones fuzzy, proposiciones todas estas, que integran una línea de resultados necesarios para la demostración de desigualdades variacionales para multifunciones fuzzy, a su vez necesarias, para la extensión fuzzy de conocido teorema de Walras.

  15. Fuzzy data analysis

    CERN Document Server

    Bandemer, Hans

    1992-01-01

    Fuzzy data such as marks, scores, verbal evaluations, imprecise observations, experts' opinions and grey tone pictures, are quite common. In Fuzzy Data Analysis the authors collect their recent results providing the reader with ideas, approaches and methods for processing such data when looking for sub-structures in knowledge bases for an evaluation of functional relationship, e.g. in order to specify diagnostic or control systems. The modelling presented uses ideas from fuzzy set theory and the suggested methods solve problems usually tackled by data analysis if the data are real numbers. Fuzzy Data Analysis is self-contained and is addressed to mathematicians oriented towards applications and to practitioners in any field of application who have some background in mathematics and statistics.

  16. Fuzzy stochastic multiobjective programming

    CERN Document Server

    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.

  17. Fuzziness in abacus logic

    Science.gov (United States)

    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.

  18. Dialectic operator fuzzy logic

    Institute of Scientific and Technical Information of China (English)

    程晓春; 姜云飞; 刘叙华

    1996-01-01

    Dialectic operator fuzzy logic (DOFL) is presented which is relevant,paraconsistent and nonmonotonic.DOFL can vividly describe the belief revision in the cognitive process and can infer reasonably well while the knowledge is inconsistent,imprecise or incomplete.

  19. On Fuzzy Regular-I-Closed Sets, Fuzzy Semi-I-Regular Sets, Fuzzy ABI-Sets and Decompositions of Fuzzy Regular-I-Continuity, Fuzzy AI - Continuity

    OpenAIRE

    Yildiz, Cemil; ABBAS, Fadhil

    2011-01-01

     The concepts of fuzzy regular-I-closed set and fuzzy semi-I-regular set in fuzzy ideal topological spaces are investigated and some of their properties are obtained. Key words: Topological, Spaces, Fuzzy, Regular, Sets

  20. Development of a controller based on Fuzzy theory to better use the energy of a hybrid system power generation solar-photovoltaic and wind; Desenvolvimento de um controlador baseado na teoria Fuzzy para melhor aproveitamento da energia de um sistema hibrido de geracao de energia solar-fotovoltaico e eolico

    Energy Technology Data Exchange (ETDEWEB)

    Caneppele, Fernando de Lima [Universidade Estadual Paulista (UNESP), Itapeva, SP (Brazil). Campus Experimental], E-mail: fernando@itapeva.unesp.br; Seraphim, Odivaldo Jose [Universidade Estadual Paulista (FCA/UNESP), Botucatu, SP (Brazil). Fac. de Ciencias Agronomicas. Dept. de Engenharia Rural; Gabriel Filho, Luis Roberto de Almeida [Universidade Estadual Paulista (UNESP), Tupa, SP (Brazil). Campus Experimental

    2010-07-01

    The work developed a methodology fuzzy and simulated its use in control of a hybrid system of electric power generation, using solar-photovoltaic and wind energy. Using this control system, we get the point of maximum energy generation and transfer all the energy generated from alternative sources, solar-photovoltaic and wind energy to charge and / or batteries. The model uses three input variables, which are: wind (wind speed), sun (solar radiation) and batteries (charge the battery bank). With these variables, the fuzzy system will play, according to the rules to be described, what is the source of power supply system, which will have priority and how the batteries are loaded. For the simulations regarding the use of fuzzy theory to control, we used the scientific computing environment MATLAB. In this environment have been analyzed and simulated all mathematical modeling, rules and other variables described in the fuzzy system. This model can be applied to implement a control system of hybrid power generation, providing the best use of renewable energy, solar and wind, so that we can extract the maximum possible energy of these alternative sources without compromising the environment. (author)

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

    Science.gov (United States)

    Chen, Shyi-Ming; Wang, Nai-Yi

    2010-10-01

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

  2. Fuzzy variable linear programming with fuzzy technical coefficients

    Directory of Open Access Journals (Sweden)

    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.

  3. Intuitionistic fuzzy alpha-continuity and intuitionistic fuzzy precontinuity

    Directory of Open Access Journals (Sweden)

    Joung Kon Jeon

    2005-01-01

    Full Text Available A characterization of intuitionistic fuzzy α-open set is given, and conditions for an IFS to be an intuitionistic fuzzy α-open set are provided. Characterizations of intuitionistic fuzzy precontinuous (resp., α-continuous mappings are given.

  4. On fuzzy points in semigroups

    Directory of Open Access Journals (Sweden)

    Kyung Ho Kim

    2001-01-01

    Full Text Available We consider the semigroup S¯ of the fuzzy points of a semigroup S, and discuss the relation between the fuzzy interior ideals and the subsets of S¯ in an (intra-regular semigroup S.

  5. 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.

  6. Compactness theorems of fuzzy semantics

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    The relationship among diverse fuzzy semantics vs. the corresponding logic consequence operators has been analyzed systematically. The results that compactness and logical compactness of fuzzy semantics are equivalent to compactness and continuity of the logic consequence operator induced by the semantics respectively have been proved under certain conditions. A general compactness theorem of fuzzy semantics have been established which says that every fuzzy semantics defined on a free algebra with members corresponding to continuous functions is compact.

  7. Fuzzy Group Ideals and Rings

    Directory of Open Access Journals (Sweden)

    Kharatti Lal

    2015-12-01

    Full Text Available This section define a level subring or level ideals obtain a set of necessary and sufficient condition for the equality of two ideals and characterizes field in terms of its fuzzy ideals. It also presents a procedure to construct a fuzzy subrings (fuzzy ideals from any given ascending chain of subring ideal. We prove that the lattice of fuzzy congruence of group G (respectively ring R is isomorphic to the lattice of fuzzy normal subgroup of G (respectively fuzzy ideals of R.In Yuan Boond Wu wangrning investigated the relationship between the fuzzy ideals and the fuzzy congruences on a distributive lattice and obtained that the lattice of fuzzy ideals is isomorphic to the lattice of fuzzy congruences on a generalized Boolean algebra. Fuzzy group theory can be used to describe, symmetries and permutation in nature and mathematics. The fuzzy group is one of the oldest branches of abstract algebra. For example group can be used is classify to all of the forms chemical crystal can take. Group can be used to count the number of non-equivalent objects and permutation or symmetries. For example, the number of different is switching functions of n, variable when permutation of the input are allowed. Beside crystallography and combinatory group have application of quantum mechanics.

  8. Possibility Intuitionistic Fuzzy Soft Set

    Directory of Open Access Journals (Sweden)

    Maruah Bashir

    2012-01-01

    Full Text Available Possibility intuitionistic fuzzy soft set and its operations are introduced, and a few of their properties are studied. An application of possibility intuitionistic fuzzy soft sets in decision making is investigated. A similarity measure of two possibility intuitionistic fuzzy soft sets has been discussed. An application of this similarity measure in medical diagnosis has been shown.

  9. Fuzzy Soft Compact Topological Spaces

    Directory of Open Access Journals (Sweden)

    Seema Mishra

    2016-01-01

    Full Text Available In this paper, we have studied compactness in fuzzy soft topological spaces which is a generalization of the corresponding concept by R. Lowen in the case of fuzzy topological spaces. Several basic desirable results have been established. In particular, we have proved the counterparts of Alexander’s subbase lemma and Tychonoff theorem for fuzzy soft topological spaces.

  10. Two-Point Fuzzy Ostrowski Type Inequalities

    Directory of Open Access Journals (Sweden)

    Muhammad Amer Latif

    2013-08-01

    Full Text Available Two-point fuzzy Ostrowski type inequalities are proved for fuzzy Hölder and fuzzy differentiable functions. The two-point fuzzy Ostrowski type inequality for M-lipshitzian mappings is also obtained. It is proved that only the two-point fuzzy Ostrowski type inequality for M-lipshitzian mappings is sharp and as a consequence generalize the two-point fuzzy Ostrowski type inequalities obtained for fuzzy differentiable functions.

  11. Bifundamental Fuzzy 2-Sphere and Fuzzy Killing Spinors

    Directory of Open Access Journals (Sweden)

    Horatiu Nastase

    2010-07-01

    Full Text Available We review our construction of a bifundamental version of the fuzzy 2-sphere and its relation to fuzzy Killing spinors, first obtained in the context of the ABJM membrane model. This is shown to be completely equivalent to the usual (adjoint fuzzy sphere. We discuss the mathematical details of the bifundamental fuzzy sphere and its field theory expansion in a model-independent way. We also examine how this new formulation affects the twisting of the fields, when comparing the field theory on the fuzzy sphere background with the compactification of the 'deconstructed' (higher dimensional field theory.

  12. Multiple Fuzzy Classification Systems

    CERN Document Server

    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...

  13. Possibilistic Exponential Fuzzy Clustering

    Institute of Scientific and Technical Information of China (English)

    Kiatichai Treerattanapitak; Chuleerat Jaruskulchai

    2013-01-01

    Generally,abnormal points (noise and outliers) cause cluster analysis to produce low accuracy especially in fuzzy clustering.These data not only stay in clusters but also deviate the centroids from their true positions.Traditional fuzzy clustering like Fuzzy C-Means (FCM) always assigns data to all clusters which is not reasonable in some circumstances.By reformulating objective function in exponential equation,the algorithm aggressively selects data into the clusters.However noisy data and outliers cannot be properly handled by clustering process therefore they are forced to be included in a cluster because of a general probabilistic constraint that the sum of the membership degrees across all clusters is one.In order to improve this weakness,possibilistic approach relaxes this condition to improve membership assignment.Nevertheless,possibilistic clustering algorithms generally suffer from coincident clusters because their membership equations ignore the distance to other clusters.Although there are some possibilistic clustering approaches that do not generate coincident clusters,most of them require the right combination of multiple parameters for the algorithms to work.In this paper,we theoretically study Possibilistic Exponential Fuzzy Clustering (PXFCM) that integrates possibilistic approach with exponential fuzzy clustering.PXFCM has only one parameter and not only partitions the data but also filters noisy data or detects them as outliers.The comprehensive experiments show that PXFCM produces high accuracy in both clustering results and outlier detection without generating coincident problems.

  14. Lógica fuzzy e regressão logística na decisão para prática de cintilografia das paratiróides Fuzzy logic and logistic regression in the decision making for parathyroid scintigraphy study

    Directory of Open Access Journals (Sweden)

    Clóvis Arlindo de Sousa

    2006-10-01

    Full Text Available OBJETIVO: Desenvolver e comparar dois modelos matemáticos, um deles baseado em regressão logística e o outro em teoria de conjuntos fuzzy, para definir a indicação para a realização do exame cintilográfico a partir de resultados dos exames laboratoriais. MÉTODOS: Foram identificados 194 pacientes que tiveram cálcio e paratormônio séricos medidos a partir da base de registros de cintilografia de paratiróides realizadas em laboratório de diagnóstico de São Paulo, no período de janeiro de 2000 a dezembro de 2004. O modelo de regressão logística foi desenvolvido utilizando-se o software SPSS e o modelo fuzzy, o Matlab. A performance dos modelos foi comparada utilizando-se curvas ROC. RESULTADOS: Os modelos apresentaram diferenças estatisticamente significantes (p=0,026 nos seus desempenhos. A área sob a curva ROC do modelo de regressão logística foi de 0,862 (IC 95%: 0,811-0,913 e do modelo de lógica fuzzy foi 0,887 (IC 95%: 0,840-0,933. Este último destacou-se como particularmente útil porque, ao contrário do modelo logístico, mostrou capacidade de utilizar informações de paratormônio em intervalo em que os valores de cálcio mostraram-se pouco discriminantes. CONCLUSÕES: O modelo matemático baseado em teoria de conjuntos fuzzy pareceu ser mais adequado do que o baseado em regressão logística como método para decisão da realização de cintilografia das paratiróides. Todavia, sendo resultado de um exercício metodológico, inferências sobre o comportamento do objeto podem ser impróprias, dada a não representatividade populacional dos dados.OBJECTIVE: To develop and compare two mathematical models, the first one based on logistic regression and the second one on fuzzy sets theory, aiming at defining a laboratory testing-based measure of indication for submitting patients to parathyroid scintigraphy. METHODS: One-hundred and ninety-four patients with serum calcium and parathyroid hormone available were

  15. A comparative analysis between fuzzy topsis and simplified fuzzy topsis

    Science.gov (United States)

    Ahmad, Sharifah Aniza Sayed; Mohamad, Daud

    2017-08-01

    Fuzzy Multiple Criteria Decision Making plays an important role in solving problems in decision making under fuzzy environment. Among the popular methods used is the fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) where the solution is based on the shortest distance from its positive ideal solution and the farthest distance from its negative ideal solution. The fuzzy TOPSIS method was first introduced by Chen (2000). At present, there are several variants of fuzzy TOPSIS methods and each of them claimed to have its own advantages. In this paper, a comparative analysis is made between the classical fuzzy TOPSIS method proposed by Chen in 2000 and the simplified fuzzy TOPSIS proposed by Sodhi in 2012. The purpose of this study is to show the similarities and the differences between these two methods and also elaborate on their strengths and limitations as well. A comparison is also made by providing numerical examples of both methods.

  16. A neural fuzzy controller learning by fuzzy error propagation

    Science.gov (United States)

    Nauck, Detlef; Kruse, Rudolf

    1992-01-01

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

  17. -Fuzzy Ideals in Ordered Semigroups

    Directory of Open Access Journals (Sweden)

    Asghar Khan

    2009-01-01

    Full Text Available We introduce the concept of 𝒩-fuzzy left (right ideals in ordered semigroups and characterize ordered semigroups in terms of 𝒩-fuzzy left (right ideals. We characterize left regular (right regular and left simple (right simple ordered semigroups in terms of 𝒩-fuzzy left (𝒩-fuzzy right ideals. The semilattice of left (right simple semigroups in terms of 𝒩-fuzzy left (right ideals is discussed.

  18. Tuning of Fuzzy PID Controllers

    DEFF Research Database (Denmark)

    Jantzen, Jan

    1998-01-01

    Since fuzzy controllers are nonlinear, it is more difficult to set the controller gains compared to proportional-integral-derivative (PID) controllers. This research paper proposes a design procedure and a tuning procedure that carries tuning rules from the PID domain over to fuzzy single......-loop controllers. The idea is to start with a tuned, conventional PID controller, replace it with an equivalent linear fuzzy controller, make the fuzzy controller nonlinear, and eventually fine-tune the nonlinear fuzzy controller. This is relevant whenever a PID controller is possible or already implemented....

  19. The foundations of fuzzy control

    CERN Document Server

    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.

  20. Fuzzy Multiresolution Neural Networks

    Science.gov (United States)

    Ying, Li; Qigang, Shang; Na, Lei

    A fuzzy multi-resolution neural network (FMRANN) based on particle swarm algorithm is proposed to approximate arbitrary nonlinear function. The active function of the FMRANN consists of not only the wavelet functions, but also the scaling functions, whose translation parameters and dilation parameters are adjustable. A set of fuzzy rules are involved in the FMRANN. Each rule either corresponding to a subset consists of scaling functions, or corresponding to a sub-wavelet neural network consists of wavelets with same dilation parameters. Incorporating the time-frequency localization and multi-resolution properties of wavelets with the ability of self-learning of fuzzy neural network, the approximation ability of FMRANN can be remarkable improved. A particle swarm algorithm is adopted to learn the translation and dilation parameters of the wavelets and adjusting the shape of membership functions. Simulation examples are presented to validate the effectiveness of FMRANN.

  1. WHY FUZZY QUALITY?

    Directory of Open Access Journals (Sweden)

    Abbas Parchami

    2016-09-01

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

  2. (L,M-Fuzzy σ-Algebras

    Directory of Open Access Journals (Sweden)

    Fu-Gui Shi

    2010-01-01

    Full Text Available The notion of (L,M-fuzzy σ-algebras is introduced in the lattice value fuzzy set theory. It is a generalization of Klement's fuzzy σ-algebras. In our definition of (L,M-fuzzy σ-algebras, each L-fuzzy subset can be regarded as an L-measurable set to some degree.

  3. Fuzzy Supervisory Control

    DEFF Research Database (Denmark)

    Jantzen, Jan

    1998-01-01

    Control problems in the process industry are dominated by non-linear and time-varying behaviour, many inner loops, and much interaction between the control loops. Fuzzy controllers have in some cases nevertheless mimicked the control actions of a human operator. For high level control and supervi......Control problems in the process industry are dominated by non-linear and time-varying behaviour, many inner loops, and much interaction between the control loops. Fuzzy controllers have in some cases nevertheless mimicked the control actions of a human operator. For high level control...

  4. Fuzzy OPF incorporating UPFC

    Energy Technology Data Exchange (ETDEWEB)

    Venkatesh, B.; George, M.K. [Multimedia University (Malaysia). Faculty of Engineering and Technology; Gooi, H.B. [Nanyang Technological University (Singapore). School of Electrical and Electronics Engineering

    2004-09-01

    A new optimal reactive power flow (ORPF) method is proposed which considers the inclusion of unified powerflow controllers (UPFC). The modelling and inclusion of UPFC in the solution of power flow equations is presented. The ORPF problem is formulated as a fuzzy optimisation problem considering the objectives of minimising system transmission loss and obtaining the best voltage profile. The fuzzy formulation of the ORPF problem is solved using an EP algorithm. The proposed method is applied on the 6-bus and 57-bus IEEE test systems and on a 191-bus Indian electric power system. The results demonstrate the applicability of the method. (author)

  5. Fuzzy CP2

    CERN Document Server

    Alexanian, G G; Immirzi, G; Ydri, B

    2001-01-01

    Regularization of quantum field theories (QFT's) can be achieved by quantizing the underlying manifold (spacetime or spatial slice) thereby replacing it by a non-commutative matrix model or a ``fuzzy manifold''. Such discretization by quantization is remarkably successful in preserving symmetries and topological features, and altogether overcoming the fermion-doubling problem. In this paper, we report on our work on the ``fuzzification'' of the four-dimensional CP2 and its QFT's. CP2 is not spin, but spin${}_c$. Its Dirac operator has many unique features. They are explained and their fuzzy versions are described.

  6. Fuzzy Topological Systems

    CERN Document Server

    Syropoulos, Apostolos

    2011-01-01

    Dialectica categories are a very versatile categorical model of linear logic. These have been used to model many seemingly different things (e.g., Petri nets and Lambek's calculus). In this note, we expand our previous work on fuzzy petri nets to deal with fuzzy topological systems. One basic idea is to use as the dualizing object in the Dialectica categories construction, the unit real interval [0,1], which has all the properties of a {\\em lineale}. The second basic idea is to generalize Vickers's notion of a topological system.

  7. A Fuzzy Commitment Scheme

    CERN Document Server

    Al-saggaf, Alawi A

    2008-01-01

    This paper attempt has been made to explain a fuzzy commitment scheme. In the conventional Commitment schemes, both committed string m and valid opening key are required to enable the sender to prove the commitment. However there could be many instances where the transmission involves noise or minor errors arising purely because of the factors over which neither the sender nor the receiver have any control. The fuzzy commitment scheme presented in this paper is to accept the opening key that is close to the original one in suitable distance metric, but not necessarily identical. The concept itself is illustrated with the help of simple situation.

  8. The fuzzy WOD model

    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...

  9. FUZZY PREFERENCES IN CONFLICTS

    Institute of Scientific and Technical Information of China (English)

    Mubarak S. AL-MUTAIRI; Keith W. HIPEL; Mohamed S. KAMEL

    2008-01-01

    A systematic fuzzy approach is developed to model fuzziness and uncertainties in the preferences of decision makers involved in a conflict. This unique fuzzy preference formulation is used within the paradigm of the Graph Model for Conflict Resolution in which a given dispute is modeled in terms of decision makers, each decision maker's courses of actions or options, and each decision maker's preferences concerning the states or outcomes which could take place. In order to be able to determine the stability of each state for each decision maker and the possible equilibria or resolutions, a range of solution concepts describing potential human behavior under conflict are defined for use with fuzzy preferences. More specifically, strong and weak definitions of stability are provided for the solution concepts called Nash, general metarational, symmetric metarational, and sequential stability. To illustrate how these solution concepts can be conveniently used in practice, they are applied to a dispute over the contamination of an aquifer by a chemical company located in Elmira, Ontario, Canada.

  10. Fuzzy efficiency without convexity

    DEFF Research Database (Denmark)

    Hougaard, Jens Leth; Balezentis, Tomas

    2014-01-01

    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...

  11. Fuzziness at the horizon

    Energy Technology Data Exchange (ETDEWEB)

    Batic, Davide, E-mail: dbatic@uniandes.edu.c [Departamento de Matematica, Universidad de los Andes, Cra 1E, No. 18A-10, Bogota, Colombia Department of Mathematics, University of West Indies, Kingston (Jamaica); Nicolini, Piero, E-mail: nicolini@th.physik.uni-frankfurt.d [Frankfurt Institute for Advanced Studies (FIAS), Institut fuer Theoretische Physik, Johann Wolfgang Goethe-Universitaet, Ruth-Moufang-Strasse 1, 60438 Frankfurt am Main (Germany)

    2010-08-16

    We study the stability of the noncommutative Schwarzschild black hole interior by analysing the propagation of a massless scalar field between the two horizons. We show that the spacetime fuzziness triggered by the field higher momenta can cure the classical exponential blue-shift divergence, suppressing the emergence of infinite energy density in a region nearby the Cauchy horizon.

  12. Fuzzy knowledge management for the semantic web

    CERN Document Server

    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.

  13. Intuitionistic Fuzzy Graphs with Categorical Properties

    Directory of Open Access Journals (Sweden)

    Hossein Rashmanlou

    2015-09-01

    Full Text Available The main purpose of this paper is to show the rationality of some operations, defined or to be defined, on intuitionistic fuzzy graphs. Firstly, three kinds of new product operations (called direct product, lexicographic product, and strong product are defined in intuitionistic fuzzy graphs, and some important notions on intuitionistic fuzzy graphs are demonstrated by characterizing these notions and their level counterparts graphs such as intuitionistic fuzzy complete graph, cartesian product of intuitionistic fuzzy graphs, composition of intuitionistic fuzzy graphs, union of intuitionistic fuzzy graphs, and join of intuitionistic fuzzy graphs. As a result, a kind of representations of intuitionistic fuzzy graphs and intuitionistic fuzzy complete graphs are given. Next, categorical goodness of intuitionistic fuzzy graphs is illustrated by proving that the category of intuitionistic fuzzy graphs and homomorphisms between them is isomorphic-closed, complete, and co-complete.

  14. Probability representations of fuzzy systems

    Institute of Scientific and Technical Information of China (English)

    LI Hongxing

    2006-01-01

    In this paper, the probability significance of fuzzy systems is revealed. It is pointed out that COG method, a defuzzification technique used commonly in fuzzy systems, is reasonable and is the optimal method in the sense of mean square. Based on different fuzzy implication operators, several typical probability distributions such as Zadeh distribution, Mamdani distribution, Lukasiewicz distribution, etc. are given. Those distributions act as "inner kernels" of fuzzy systems. Furthermore, by some properties of probability distributions of fuzzy systems, it is also demonstrated that CRI method, proposed by Zadeh, for constructing fuzzy systems is basically reasonable and effective. Besides, the special action of uniform probability distributions in fuzzy systems is characterized. Finally, the relationship between CRI method and triple I method is discussed. In the sense of construction of fuzzy systems, when restricting three fuzzy implication operators in triple I method to the same operator, CRI method and triple I method may be related in the following three basic ways: 1) Two methods are equivalent; 2) the latter is a degeneration of the former; 3) the latter is trivial whereas the former is not. When three fuzzy implication operators in triple I method are not restricted to the same operator, CRI method is a special case of triple I method; that is, triple I method is a more comprehensive algorithm. Since triple I method has a good logical foundation and comprises an idea of optimization of reasoning, triple I method will possess a beautiful vista of application.

  15. Hierarchical type-2 fuzzy aggregation of fuzzy controllers

    CERN Document Server

    Cervantes, Leticia

    2016-01-01

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

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

    Institute of Scientific and Technical Information of China (English)

    Yuangang TANG; Fuchun SUN; Zengqi SUN

    2005-01-01

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

  17. Generalised Interval-Valued Fuzzy Soft Set

    OpenAIRE

    Shawkat Alkhazaleh; Abdul Razak Salleh

    2012-01-01

    We introduce the concept of generalised interval-valued fuzzy soft set and its operations and study some of their properties. We give applications of this theory in solving a decision making problem. We also introduce a similarity measure of two generalised interval-valued fuzzy soft sets and discuss its application in a medical diagnosis problem: fuzzy set; soft set; fuzzy soft set; generalised fuzzy soft set; generalised interval-valued fuzzy soft set; interval-valued fuzz...

  18. On Intuitionistic Fuzzy Magnified Translation in Semigroups

    OpenAIRE

    Sardar, Sujit Kumar; Mandal, Manasi; Majumder, Samit Kumar

    2011-01-01

    The notion of intuitionistic fuzzy sets was introduced by Atanassov as a generalization of the notion of fuzzy sets. S.K Sardar and S.K. Majumder unified the idea of fuzzy translation and fuzzy multiplication of Vasantha Kandasamy to introduce the concept of fuzzy magnified translation in groups and semigroups. The purpose of this paper is to intuitionistically fuzzify(by using Atanassov's idea) the concept of fuzzy magnified translation in semigroups. Here among other results we obtain some ...

  19. Lower and Upper Fuzzy Topological Subhypergroups

    Institute of Scientific and Technical Information of China (English)

    Irina CRISTEA; Jian Ming ZHAN

    2013-01-01

    This paper provides a new connection between algebraic hyperstructures and fuzzy sets.More specifically,using both properties of fuzzy topological spaces and those of fuzzy subhypergroups,we define the notions of lower (upper) fuzzy topological subhypergroups of a hypergroup endowed with a fuzzy topology.Some results concerning the image and the inverse image of a lower (upper) topological subhypergroup under a very good homomorphism of hypergroups (endowed with fuzzy topologies) are pointed out.

  20. The squashed fuzzy sphere, fuzzy strings and the Landau problem

    CERN Document Server

    Andronache, Stefan

    2015-01-01

    We discuss the squashed fuzzy sphere, which is a projection of the fuzzy sphere onto the equatorial plane, and use it to illustrate the stringy aspects of noncommutative field theory. We elaborate explicitly how strings linking its two coincident sheets arise in terms of fuzzy spherical harmonics. In the large N limit, the matrix-model Laplacian is shown to correctly reproduce the semi-classical dynamics of these charged strings, as given by the Landau problem.

  1. The squashed fuzzy sphere, fuzzy strings and the Landau problem

    Science.gov (United States)

    Andronache, Stefan; Steinacker, Harold C.

    2015-07-01

    We discuss the squashed fuzzy sphere, which is a projection of the fuzzy sphere onto the equatorial plane, and use it to illustrate the stringy aspects of noncommutative field theory. We elaborate explicitly how strings linking its two coincident sheets arise in terms of fuzzy spherical harmonics. In the large N limit, the matrix-model Laplacian is shown to correctly reproduce the semi-classical dynamics of these charged strings, as given by the Landau problem.

  2. Genetic Algorithm Optimization for Determining Fuzzy Measures from Fuzzy Data

    Directory of Open Access Journals (Sweden)

    Chen Li

    2013-01-01

    Full Text Available Fuzzy measures and fuzzy integrals have been successfully used in many real applications. How to determine fuzzy measures is a very difficult problem in these applications. Though there have existed some methodologies for solving this problem, such as genetic algorithms, gradient descent algorithms, neural networks, and particle swarm algorithm, it is hard to say which one is more appropriate and more feasible. Each method has its advantages. Most of the existed works can only deal with the data consisting of classic numbers which may arise limitations in practical applications. It is not reasonable to assume that all data are real data before we elicit them from practical data. Sometimes, fuzzy data may exist, such as in pharmacological, financial and sociological applications. Thus, we make an attempt to determine a more generalized type of general fuzzy measures from fuzzy data by means of genetic algorithms and Choquet integrals. In this paper, we make the first effort to define the σ-λ rules. Furthermore we define and characterize the Choquet integrals of interval-valued functions and fuzzy-number-valued functions based on σ-λ rules. In addition, we design a special genetic algorithm to determine a type of general fuzzy measures from fuzzy data.

  3. GENERALIZED FUZZY FILTERS OF BL-ALGEBRAS

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The concept of quasi-coincidence of a fuzzy interval value with an interval valued fuzzy set is considered. In fact, this is a generalization of quasi-coincidence of a fuzzy point with a fuzzy set. By using this new idea, the notion of interval valued (∈, ∈∨q)-fuzzy filters in BL-algebras which is a generalization of fuzzy filters of BL-algebras, is defined, and related properties are investigated. In particular, the concept of a fuzzy subgroup with thresholds is extended to the concept of an interval valued fuzzy filter with thresholds in BL-algebras.

  4. On the intuitionistic fuzzy topological spaces

    Energy Technology Data Exchange (ETDEWEB)

    Saadati, Reza [Department of Mathematics, Azad University, Amol, P.O. Box 678 (Iran, Islamic Republic of)] e-mail: rsaadati@eml.cc; Park, Jin Han [Division of Mathematical Sciences, Pukyong National University, 599-1 Daeyeon, 3-Dong Nam-Gu, Pusan 608 737 (Korea, Republic of)] e-mail: jihpark@pknu.ac.kr

    2006-01-01

    In this paper, we define precompact set in intuitionistic fuzzy metric spaces and prove that any subset of an intuitionistic fuzzy metric space is compact if and only if it is precompact and complete. Also we define topologically complete intuitionistic fuzzy metrizable spaces and prove that any G{sub {delta}} set in a complete intuitionistic fuzzy metric spaces is a topologically complete intuitionistic fuzzy metrizable space and vice versa. Finally, we define intuitionistic fuzzy normed spaces and fuzzy boundedness for linear operators and so we prove that every finite dimensional intuitionistic fuzzy normed space is complete.

  5. On the intuitionistic fuzzy topological spaces

    Science.gov (United States)

    Saadati, Reza; Park, Jin Han

    2006-01-01

    In this paper, we define precompact set in intuitionistic fuzzy metric spaces and prove that any subset of an intuitionistic fuzzy metric space is compact if and only if it is precompact and complete. Also we define topologically complete intuitionistic fuzzy metrizable spaces and prove that any $G_{\\delta }$ set in a complete intuitionistic fuzzy metric spaces is a topologically complete intuitionistic fuzzy metrizable space and vice versa. Finally, we define intuitionistic fuzzy normed spaces and fuzzy boundedness for linear operators and so we prove that every finite dimensional intuitionistic fuzzy normed space is complete.

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

    Institute of Scientific and Technical Information of China (English)

    FENG Yu-hu

    2005-01-01

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

  7. Fuzzy logic particle tracking velocimetry

    Science.gov (United States)

    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.

  8. Fuzzy pharmacology: theory and applications.

    Science.gov (United States)

    Sproule, Beth A; Naranjo, Claudio A; Türksen, I Burhan

    2002-09-01

    Fuzzy pharmacology is a term coined to represent the application of fuzzy logic and fuzzy set theory to pharmacological problems. Fuzzy logic is the science of reasoning, thinking and inference that recognizes and uses the real world phenomenon that everything is a matter of degree. It is an extension of binary logic that is able to deal with complex systems because it does not require crisp definitions and distinctions for the system components. In pharmacology, fuzzy modeling has been used for the mechanical control of drug delivery in surgical settings, and work has begun evaluating its use in other pharmacokinetic and pharmacodynamic applications. Fuzzy pharmacology is an emerging field that, based on these initial explorations, warrants further investigation.

  9. Planning projects for generation of electrical energy in the state of Sao Paulo, according to the degree of interference on air quality: an atmospheric qualification index using fuzzy sets; Ordenamento de projetos de geracao de energia eletrica no estado de Sao Paulo, segundo o grau de interferencia na qualidade do ar: um indice de qualificacao atmosferica (IQA) utilizando fuzzy sets

    Energy Technology Data Exchange (ETDEWEB)

    Dzedzej, Maira; Maciel, Jonas Fernandes; Santos, Afonso Henrique Moreira [IX Consultoria e Representacoes Ltda, Itajuba, MG (Brazil); Duarte, Pamella Santos [MS Consultoria Ltda, Itajuba, MG (Brazil); Universidade Federal de Itajuba (UNIFEI), MG (Brazil)

    2010-07-01

    Environmental issues are of great importance when assessing the feasibility and priority installation of new developments in electric power generation. In this sense, fuzzy logic can help define the regions that have favorable characteristics for receiving certain forms of generation. This study sought to order for the State of Sao Paulo, four kinds of generation projects: those using municipal solid waste gasification, those which make use of landfill gas with a change in firing (to reduce emissions), thermoelectric plants (TEPs) to bagasse (with 15% straw) and Small Hydropower (SHP). Such an ordering considered not only the type of generation but also the allocation of projects in the four regions, defined by regional vocations as defined by the State Water Resources Plan (Annex III of the State Law No. 9.034/94): Agriculture, Conservation, In Industrialization and Industrial. As a result, the use of fuzzy sets allowed the creation of a ranking of the alternatives (which totaled 14 possibilities), based exclusively on the degree of interference in air quality resulting from the installation of every form of generation. Such information may help the decision-making governing bodies to establish priorities in order, thereby accelerating the process of installation and operation of projects for generating electricity. (author)

  10. Intuitionistic fuzzy aggregation and clustering

    CERN Document Server

    Xu, Zeshui

    2012-01-01

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

  11. Phase structures in fuzzy geometries

    CERN Document Server

    Govindarajan, T R; Gupta, K S; Martin, X

    2012-01-01

    We study phase structures of quantum field theories in fuzzy geometries. Several examples of fuzzy geometries as well as QFT's on such geometries are considered. They are fuzzy spheres and beyond as well as noncommutative deformations of BTZ blackholes. Analysis is done analytically and through simulations. Several features like novel stripe phases as well as spontaneous symmetry breaking avoiding Colemen, Mermin, Wagner theorem are brought out. Also we establish that these phases are stable due to topological obstructions.

  12. COMPATIBLE EXTENSIONS OF FUZZY RELATIONS

    Institute of Scientific and Technical Information of China (English)

    Irina GEORGESCU

    2003-01-01

    In 1930 Szpilrajn proved that any strict partial order can be embedded in a strict linear order.This theorem was later refined by Dushnik and Miller (1941), Hansson (1968), Suzumura (1976),Donaldson and Weymark (1998), Bossert (1999). Particularly Suzumura introduced the important concept of compatible extension of a (crisp) relation. These extension theorems have an important role in welfare economics. In particular Szpilrajn theorem is the main tool for proving a known theorem of Richter that establishes the equivalence between rational and congruous consumers. In 1999 Duggan proved a general extension theorem that contains all these results. In this paper we introduce the notion of compatible extension of a fuzzy relation and we prove an extension theorem for fuzzy relations. Our result generalizes to fuzzy set theory the main part of Duggan's theorem. As applications we obtain fuzzy versions of the theorems of Szpilrajn, Hansson and Suzumura. We also prove that an asymmetric and transitive fuzzy relation has a compatible extension that is total, asymmetric and transitive.Our results can be useful in the theory of fuzzy consumers. We can prove that any rational fuzzyconsumer is congruous, extending to a fuzzy context a part of Richter's theorem. To prove that acongruous fuzzy consumer is rational remains an open problem. A proof of this result can somehowuse a fuzzy version of Szpilrajn theorem.

  13. Fuzzy-Contextual Contrast Enhancement.

    Science.gov (United States)

    Parihar, Anil; Verma, Om; Khanna, Chintan

    2017-02-08

    This paper presents contrast enhancement algorithms based on fuzzy contextual information of the images. We introduce fuzzy similarity index and fuzzy contrast factor to capture the neighborhood characteristics of a pixel. A new histogram, using fuzzy contrast factor of each pixel is developed, and termed as the fuzzy dissimilarity histogram (FDH). A cumulative distribution function (CDF) is formed with normalized values of FDH and used as a transfer function to obtain the contrast enhanced image. The algorithm gives good contrast enhancement and preserves the natural characteristic of the image. In order to develop a contextual intensity transfer function, we introduce a fuzzy membership function based on fuzzy similarity index and coefficient of variation of the image. The contextual intensity transfer function is designed using the fuzzy membership function to achieve final contrast enhanced image. The overall algorithm is referred as the fuzzy contextual contrast-enhancement (FCCE) algorithm. The proposed algorithms are compared with conventional and state-of-art contrast enhancement algorithms. The quantitative and visual assessment of the results is performed. The results of quantitative measures are statistically analyzed using t-test. The exhaustive experimentation and analysis show the proposed algorithm efficiently enhances contrast and yields in natural visual quality images.

  14. A New View on Fuzzy Hypermodules

    Institute of Scientific and Technical Information of China (English)

    Jian Ming ZHAN; Bijan DAVVAZ; K. P. SHUM

    2007-01-01

    We describe the relationship between the fuzzy sets and the algebraic hyperstructures.In fact,this paper is a continuation of the ideas presented by Davvaz in (Fuzzy Sets Syst.,117: 477-484,2001) and Bhakat and Das in (Fuzzy Sets Syst.,80: 359-368,1996).The concept of the quasi-coincidence of a fuzzy interval value with an interval-valued fuzzy set is introduced and this is a naturalgeneralization of the quasi-coincidence of a fuzzy point in fuzzy sets.By using this new idea,the conceptof interval-valued (α,β)-fuzzy sub-hypermodules of a hypermodule is defined.This newly definedinterval-valued (α,β)-fuzzy sub-hypermodule is a generalization of the usual fuzzy sub-hypermodule.We shall study such fuzzy sub-hypermodules and consider the implication-based interval-valued fuzzysub-hypermodules of a hypermodule.

  15. New Closeness Coefficients for Fuzzy Similarity Based Fuzzy TOPSIS: An Approach Combining Fuzzy Entropy and Multidistance

    Directory of Open Access Journals (Sweden)

    Mikael Collan

    2015-01-01

    Full Text Available This paper introduces new closeness coefficients for fuzzy similarity based TOPSIS. The new closeness coefficients are based on multidistance or fuzzy entropy, are able to take into consideration the level of similarity between analysed criteria, and can be used to account for the consistency or homogeneity of, for example, performance measuring criteria. The commonly known OWA operator is used in the aggregation process over the fuzzy similarity values. A range of orness values is considered in creating a fuzzy overall ranking for each object, after which the fuzzy rankings are ordered to find a final linear ranking. The presented method is numerically applied to a research and development project selection problem and the effect of using two new closeness coefficients based on multidistance and fuzzy entropy is numerically illustrated.

  16. Fuzzy dot ideals and fuzzy dot H-ideals of BCH-algebras

    Institute of Scientific and Technical Information of China (English)

    PENG Jia-yin

    2008-01-01

    The notions of fuzzy dot ideals and fuzzy dot H-ideals in BCH-algebras are intro duced,several appropriate examples are provided,and their some properties are investigated.The relations among fuzzy ideal,fuzzy H-ideal,fuzzy dot ideal and fuzzy dot H-ideals in BCH algebras are discussed,several equivalent depictions of fuzzy dot ideal are obtained. How to deal with the homomorphic image and inverse image of fuzzy dot ideals (fuzzy dot H-ideals) are studied. The relations between a fuzzy dot ideal (fuzzy dot H-ideal) in BCH-algebras and a fuzzy dot ideal (fuzzy dot H-ideal) in the product algebra of BCH-algebras are given.

  17. Fuzzy Perfect Mappings and Q-Compactness in Smooth Fuzzy Topological Spaces

    Directory of Open Access Journals (Sweden)

    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.

  18. Spinning the fuzzy sphere

    Energy Technology Data Exchange (ETDEWEB)

    Berenstein, David [Department of Applied Mathematics and Theoretical Physics,University of Cambridge, Wilberforce Road, Cambridge CB3 0WA (United Kingdom); Department of Physics, University of California Santa Barbara,Santa Barbara, California 93106 (United States); Dzienkowski, Eric; Lashof-Regas, Robin [Department of Physics, University of California Santa Barbara,Santa Barbara, California 93106 (United States)

    2015-08-27

    We construct various exact analytical solutions of the SO(3) BMN matrix model that correspond to rotating fuzzy spheres and rotating fuzzy tori. These are also solutions of Yang Mills theory compactified on a sphere times time and they are also translationally invariant solutions of the N=1{sup ∗} field theory with a non-trivial charge density. The solutions we construct have a ℤ{sub N} symmetry, where N is the rank of the matrices. After an appropriate ansatz, we reduce the problem to solving a set of polynomial equations in 2N real variables. These equations have a discrete set of solutions for each value of the angular momentum. We study the phase structure of the solutions for various values of N. Also the continuum limit where N→∞, where the problem reduces to finding periodic solutions of a set of coupled differential equations. We also study the topology change transition from the sphere to the torus.

  19. Fuzzy controllers based on some fuzzy implication operators and their response functions

    Institute of Scientific and Technical Information of China (English)

    LI Hongxing; YOU Fei; PENG Jiayin

    2004-01-01

    The fuzzy controllers constructed by 23 fuzzy implication operators based on CRI algorithm and their response functions are discussed.The conclusions show that the fuzzy controllers constructed by 9 fuzzy implication operators are universal approximators to continuous functions and can be used in practical fuzzy control systems.And these 9 fuzzy implication operators except for Einstein operator intersection are all the adjoint pairs of some fuzzy implication operators.Besides, there are 3 other fuzzy controllers formed by fuzzy implication operators being regarded approximately as fitted functions.

  20. Fuzzy controlofanylonpolymerizationsemi-batchreactor

    OpenAIRE

    Wakabayashi, C; Embiruçu, Marcelo; Fontes, Cristiano; Kalid, Ricardo

    2009-01-01

    Acesso restrito: Texto completo. p. 537-553 Batch and semi-batch polymerization reactors with specified trajectories for certain process variables present challenging control problems. This work reports, results and procedures related to the application of PI (proportional and integral) fuzzy control in a semi-batch reactor for the production of nylon 6. Closed loop simulation results were based on a phenomenological model adjusted for a commercial reactor and they attest to the potential ...

  1. FUZZY REASONING IN CYCLES

    Institute of Scientific and Technical Information of China (English)

    曹立明

    1990-01-01

    By the similarity between the syllogism in logic and a path proposition in graph theory,a new concept,fuzzy reasoning graph G has been given in this paper. Transitive closure has been studied and used to do reasoning related to self-loop in G,and an algorithm has been designed to cope with reasoning in other cycles in G. Both approaches are applicable and efficient.

  2. Fuzzy recurrence plots

    Science.gov (United States)

    Pham, T. D.

    2016-12-01

    Recurrence plots display binary texture of time series from dynamical systems with single dots and line structures. Using fuzzy recurrence plots, recurrences of the phase-space states can be visualized as grayscale texture, which is more informative for pattern analysis. The proposed method replaces the crucial similarity threshold required by symmetrical recurrence plots with the number of cluster centers, where the estimate of the latter parameter is less critical than the estimate of the former.

  3. Emergent fuzzy geometry and fuzzy physics in four dimensions

    Science.gov (United States)

    Ydri, Badis; Rouag, Ahlam; Ramda, Khaled

    2017-03-01

    A detailed Monte Carlo calculation of the phase diagram of bosonic mass-deformed IKKT Yang-Mills matrix models in three and six dimensions with quartic mass deformations is given. Background emergent fuzzy geometries in two and four dimensions are observed with a fluctuation given by a noncommutative U (1) gauge theory very weakly coupled to normal scalar fields. The geometry, which is determined dynamically, is given by the fuzzy spheres SN2 and SN2 × SN2 respectively. The three and six matrix models are effectively in the same universality class. For example, in two dimensions the geometry is completely stable, whereas in four dimensions the geometry is stable only in the limit M ⟶ ∞, where M is the mass of the normal fluctuations. The behaviors of the eigenvalue distribution in the two theories are also different. We also sketch how we can obtain a stable fuzzy four-sphere SN2 × SN2 in the large N limit for all values of M as well as models of topology change in which the transition between spheres of different dimensions is observed. The stable fuzzy spheres in two and four dimensions act precisely as regulators which is the original goal of fuzzy geometry and fuzzy physics. Fuzzy physics and fuzzy field theory on these spaces are briefly discussed.

  4. 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.

  5. fuzzy control technique fuzzy control technique applied to modified ...

    African Journals Online (AJOL)

    eobe

    ABSTRACT. In this paper, fuzzy control technique is applied to the modified mathematical model for malaria control presented ... be devised for rule-based systems that deals with continuous ... necessary to use fuzzy logic as it is not easy to follow a particular .... point movement and control is realized and designed. (e.g. α1 ...

  6. Almost Fuzzy Compactness in L-fuzzy Top ological Spaces

    Institute of Scientific and Technical Information of China (English)

    Li Hong-yan; Cui Wei

    2015-01-01

    In this paper, the notion of almost fuzzy compactness is defined in L-fuzzy topological spaces by means of inequality, where L is a completely distributive DeMorgan algebra. Its properties are discussed and many characterizations of it are presented.

  7. How to combine probabilistic and fuzzy uncertainties in fuzzy control

    Science.gov (United States)

    Nguyen, Hung T.; Kreinovich, Vladik YA.; Lea, Robert

    1991-01-01

    Fuzzy control is a methodology that translates natural-language rules, formulated by expert controllers, into the actual control strategy that can be implemented in an automated controller. In many cases, in addition to the experts' rules, additional statistical information about the system is known. It is explained how to use this additional information in fuzzy control methodology.

  8. A taxonomy fuzzy filtering approach

    Directory of Open Access Journals (Sweden)

    Vrettos S.

    2003-01-01

    Full Text Available Our work proposes the use of topic taxonomies as part of a filtering language. Given a taxonomy, a classifier is trained for each one of its topics. The user is able to formulate logical rules combining the available topics, e.g. (Topic1 AND Topic2 OR Topic3, in order to filter related documents in a stream. Using the trained classifiers, every document in the stream is assigned a belief value of belonging to the topics of the filter. These belief values are then aggregated using logical operators to yield the belief to the filter. In our study, Support Vector Machines and Naïve Bayes classifiers were used to provide topic probabilities. Aggregation of topic probabilities based on fuzzy logic operators was found to improve filtering performance on the Renters text corpus, as compared to the use of their Boolean counterparts. Finally, we deployed a filtering system on the web using a sample taxonomy of the Open Directory Project.

  9. Fuzzy Reasoning Methods by Choosing Different Fuzzy Counters and Analysis of Effect

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Different fuzzy reasoning methods were gave by choosing different fuzzy counters. This article generally introduced the basic structure of fuzzy controller,and compared and analysised the reasoning effect of fuzzy reasoning methods and the effect of computer simulating control basicly on different fuzzy counters.

  10. L-Fuzzy Semi-Preopen Operator in L-Fuzzy Topological Spaces

    CERN Document Server

    Ghareeb, A

    2010-01-01

    In this paper, we give the concept of L-fuzzy Semi-Preopen operator in L-fuzzy topological spaces, and use them to score L-fuzzy SP-cmpactnness in L-fuzzy topological spaces. We also study the relationship between L-fuzzy SP-compactness and SP-compactness in L-topological spaces.

  11. Fuzzy MCDM Based on Fuzzy Relational Degree Analysis

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    This paper presents a new fuzzy multiple criteria (both qualitative and quantitative) decision-making (MCDM) method based on fuzzy relational degree analysis. The concepts of fuzzy set theory are used to construct a weighted suitability decision matrix to evaluate the weighted suitability of different alternatives versus various criteria. The positive ideal solution and negative ideal solution are then obtained by using a method of ranking fuzzy numbers, and the fuzzy relational degrees of different alternatives versus positive ideal solution and negative ideal solution are calculated by using the proposed arithmetic. Finally, the relative relational degrees of various alternatives versus positive ideal solution are ranked to determine the best alternative. A numerical example is provided to illustrate the proposed method at the end of this paper.

  12. Evaluation of Fuzzy Pareto Solution Set by Using Fuzzy Relation Based Clustering Approach For Fuzzy Multi-Response Experiments

    Directory of Open Access Journals (Sweden)

    Özlem Türkşen

    2013-01-01

    Full Text Available The solution set of a multi-response experiment is characterized by Pareto solution set. In this paper, the multi-response experiment is dealed in a fuzzy framework. The responses and model parameters are considered as triangular fuzzy numbers which indicate the uncertainty of the data set. Fuzzy least square approach and fuzzy modified NSGA-II (FNSGA-II are used for modeling and optimization, respectively. The obtained fuzzy Pareto solution set is grouped by using fuzzy relational clustering approach. Therefore, it could be easier to choose the alternative solutions to make better decision. A fuzzy response valued real data set is used as an application.

  13. On Fuzzy Ideals of BL-Algebras

    Directory of Open Access Journals (Sweden)

    Biao Long Meng

    2014-01-01

    Full Text Available 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 ω0=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.

  14. (Fuzzy Ideals of BN-Algebras

    Directory of Open Access Journals (Sweden)

    Grzegorz Dymek

    2015-01-01

    set to be a fuzzy ideal are given. The relationships between ideals and fuzzy ideals of a BN-algebra are established. The homomorphic properties of fuzzy ideals of a BN-algebra are provided. Finally, characterizations of Noetherian BN-algebras and Artinian BN-algebras via fuzzy ideals are obtained.

  15. On Fuzzy Ideals of BL-Algebras

    Science.gov (United States)

    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

  16. FUZZY ALGEBRA IN TRIANGULAR NORM SYSTEM

    Institute of Scientific and Technical Information of China (English)

    宋晓秋; 潘志

    1994-01-01

    Triangular norm is a powerful tool in the theory research and application development of fuzzy sets. In this paper, using the triangular norm, we introduce some concepts such as fuzzy algebra, fuzzy o algebra and fuzzy monotone class, and discuss the relations among them, obtaining the following main conclusions.

  17. Set Theory and Arithmetic in Fuzzy Logic

    OpenAIRE

    Běhounek, L. (Libor); Haniková, Z. (Zuzana)

    2015-01-01

    This chapter offers a review of Petr Hájek’s contributions to first-order axiomatic theories in fuzzy logic (in particular, ZF-style fuzzy set theories, arithmetic with a fuzzy truth predicate, and fuzzy set theory with unrestricted comprehension schema). Generalizations of Hájek’s results in these areas to MTL as the background logic are presented and discussed.

  18. AN ALGORITHM OF TEST FOR FUZZY CODES

    Institute of Scientific and Technical Information of China (English)

    MoZhiwen; PenJiayin

    2001-01-01

    Abstract. How to verify that a given fuzzy set A∈F(X ) is a fuzzy code? In this paper, an al-gorithm of test has been introduced and studied with the example of test. The measure notionfor a fuzzy code and a precise formulation of fuzzy codes and words have been discussed.

  19. Fuzzy clustering with Minkowski distance

    NARCIS (Netherlands)

    P.J.F. Groenen (Patrick); U. Kaymak (Uzay); J.M. van Rosmalen (Joost)

    2006-01-01

    textabstractDistances in the well known fuzzy c-means algorithm of Bezdek (1973) are measured by the squared Euclidean distance. Other distances have been used as well in fuzzy clustering. For example, Jajuga (1991) proposed to use the L_1-distance and Bobrowski and Bezdek (1991) also used the L_inf

  20. Duality in Dynamic Fuzzy Systems

    OpenAIRE

    Yoshida, Yuji

    1995-01-01

    This paper shows the resolvent equation, the maximum principle and the co-balayage theorem for a dynamic fuzzy system. We define a dual system for the dynamic fuzzy system, and gives a duality for Snell's optimal stopping problem by the dual system.

  1. Efficient adaptive fuzzy control scheme

    NARCIS (Netherlands)

    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

  2. Egalitarianism in Convex Fuzzy Games

    NARCIS (Netherlands)

    Brânzei, R.; Dimitrov, D.A.; Tijs, S.H.

    2002-01-01

    In this paper the egalitarian solution for convex cooperative fuzzy games is introduced.The classical Dutta-Ray algorithm for finding the constrained egalitarian solution for convex crisp games is adjusted to provide the egalitarian solution of a convex fuzzy game.This adjusted algorithm is also a f

  3. Representation of Fuzzy Symmetric Relations

    Science.gov (United States)

    1986-03-19

    Std Z39-18 REPRESENTATION OF FUZZY SYMMETRIC RELATIONS L. Valverde Dept. de Matematiques i Estadistica Universitat Politecnica de Catalunya Avda...REPRESENTATION OF FUZZY SYMMETRIC RELATIONS L. "Valverde* Dept. de Matematiques i Estadistica Universitat Politecnica de Catalunya Avda. Diagonal, 649

  4. Teaching Machines to Think Fuzzy

    Science.gov (United States)

    Technology Teacher, 2004

    2004-01-01

    Fuzzy logic programs for computers make them more human. Computers can then think through messy situations and make smart decisions. It makes computers able to control things the way people do. Fuzzy logic has been used to control subway trains, elevators, washing machines, microwave ovens, and cars. Pretty much all the human has to do is push one…

  5. FINDCLUS : Fuzzy INdividual Differences CLUStering

    NARCIS (Netherlands)

    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

  6. Fuzzy Logic Control ASIC Chip

    Institute of Scientific and Technical Information of China (English)

    沈理

    1997-01-01

    A fuzzy logic control VLSI chip,F100,for industry process real-time control has been designed and fabricated with 0.8μm CMOS technology.The chip has the features of simplicity,felexibility and generality.This paper presents the Fuzzy control inrerence method of the chip,its VLSI implementation,and testing esign consideration.

  7. Fuzzy linguistic model for interpolation

    Energy Technology Data Exchange (ETDEWEB)

    Abbasbandy, S. [Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran 14778 (Iran, Islamic Republic of); Department of Mathematics, Faculty of Science, Imam Khomeini International University, Qazvin 34194-288 (Iran, Islamic Republic of); Adabitabar Firozja, M. [Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran 14778 (Iran, Islamic Republic of)

    2007-10-15

    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.

  8. ON FUZZY h-IDEALS OF HEMIRINGS

    Institute of Scientific and Technical Information of China (English)

    Xueling MA; Jianming ZHAN

    2007-01-01

    The concept of quasi-coincidence of a fuzzy interval value in an interval valued fuzzy set is considered. In fact, this concept is a generalized concept of the quasi-coincidence of a fuzzy point in a fuzzy set. By using this new concept, the authors define the notion of interval valued (∈, ∈ Vq)-fuzzy h-ideals of hemirings and study their related properties. In addition, the authors also extend the concept of a fuzzy subgroup with thresholds to the concept of an interval valued fuzzy h-ideal with thresholds in hemirings.

  9. A new fuzzy edge detection algorithm

    Institute of Scientific and Technical Information of China (English)

    SunWei; XiaLiangzheng

    2003-01-01

    Based upon the maximum entropy theorem of information theory, a novel fuzzy approach for edge detection is presented. Firsdy, a definition of fuzzy partition entropy is proposed after introducing the concepts of fuzzy probability and fuzzy partition. The relation of the probability partition and the fuzzy c-partition of the image gradient are used in the algorithm. Secondly, based on the conditional probabilities and the fuzzy partition, the optimal thresholding is searched adaptively through the maximum fuzzy entropy principle, and then the edge image is obtained. Lastly, an edge-enhancing procedure is executed on the edge image. The experimental results show that the proposed approach performs well.

  10. Image matching navigation based on fuzzy information

    Institute of Scientific and Technical Information of China (English)

    田玉龙; 吴伟仁; 田金文; 柳健

    2003-01-01

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

  11. On Intuitionistic Fuzzy Magnified Translation in Semigroups

    CERN Document Server

    Sardar, Sujit Kumar; Majumder, Samit Kumar

    2011-01-01

    The notion of intuitionistic fuzzy sets was introduced by Atanassov as a generalization of the notion of fuzzy sets. S.K Sardar and S.K. Majumder unified the idea of fuzzy translation and fuzzy multiplication of Vasantha Kandasamy to introduce the concept of fuzzy magnified translation in groups and semigroups. The purpose of this paper is to intuitionistically fuzzify(by using Atanassov's idea) the concept of fuzzy magnified translation in semigroups. Here among other results we obtain some characterization theorems of regular, intra-regular, left(right) regular semigroups in terms of intuitionistic fuzzy magnified translation.

  12. On the L-fuzzy topological spaces

    Energy Technology Data Exchange (ETDEWEB)

    Saadati, Reza [Islamic Azad University-Aiatollah Amoly Branch, Amol 678 (Iran, Islamic Republic of); Department of Mathematics and Computer Science, Amirkabir University of Technology, 424 Hafez Avenue, Tehran 15914 (Iran, Islamic Republic of)], E-mail: rsaadati@eml.cc

    2008-09-15

    As a natural generalization of fuzzy metric spaces due to George and Veeramani [George A, Veeramani P. On some result in fuzzy metric space. Fuzzy Sets Syst 1994;64:395-9], the present author defined the notion of L-fuzzy metric spaces. In this paper we prove some known results of metric spaces including Uniform continuity theorem and Ascoli-Arzela theorem for L-fuzzy metric spaces. We also prove that every L-fuzzy metric space has a countably locally finite basis and use this result to conclude that every L-fuzzy metric space is metrizable.

  13. Concept Approximation between Fuzzy Ontologies

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Fuzzy ontologies are efficient tools to handle fuzzy and uncertain knowledge on the semantic web; but there are heterogeneity problems when gaining interoperability among different fuzzy ontologies. This paper uses concept approximation between fuzzy ontologies based on instances to solve the heterogeneity problems. It firstly proposes an instance selection technology based on instance clustering and weighting to unify the fuzzy interpretation of different ontologies and reduce the number of instances to increase the efficiency. Then the paper resolves the problem of computing the approximations of concepts into the problem of computing the least upper approximations of atom concepts. It optimizes the search strategies by extending atom concept sets and defining the least upper bounds of concepts to reduce the searching space of the problem. An efficient algorithm for searching the least upper bounds of concept is given.

  14. Design of interpretable fuzzy systems

    CERN Document Server

    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.

  15. On Intuitionistic Fuzzy Sets Theory

    CERN Document Server

    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.

  16. Modelling on fuzzy control systems

    Institute of Scientific and Technical Information of China (English)

    LI; Hongxing(李洪兴); WANG; Jiayin(王加银); MIAO; Zhihong(苗志宏)

    2002-01-01

    A kind of modelling method for fuzzy control systems is first proposed here, which is calledmodelling method based on fuzzy inference (MMFI). It should be regarded as the third modelling method thatis different from two well-known modelling methods, that is, the first modelling method, mechanism modellingmethod (MMM), and the second modelling method, system identification modelling method (SlMM). Thismethod can, based on the interpolation mechanism on fuzzy logic system, transfer a group of fuzzy inferencerules describing a practice system into a kind of nonlinear differential equation with variable coefficients, calledHX equations, so that the mathematical model of the system can be obtained. This means that we solve thedifficult problem of how to get a model represented as differential equations on a complicated or fuzzy controlsystem.

  17. Fuzzy control in environmental engineering

    CERN Document Server

    Chmielowski, Wojciech Z

    2016-01-01

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

  18. Data fusion based on fuzzy measures

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Choquet integral based on fuzzy measure is a very popular data fusion approach. A major problem in applying the Choquet integral is how to determine a large number of fuzzy measures as the number of attributes increases. The λ-fuzzy measure proposed by Sugeno is a powerful method to resolve this problem. However, the modeling ability of the λ-fuzzy measure is too limited to satisfy actual requirements. In this paper, an extended λ-fuzzy measure is proposed using Shapley value index, and the limitation of the λ-fuzzy measure is significantly overcome under little additional computational loads. The extended fuzzy measure has stronger modeling power than the λ-fuzzy measure, straightforwardly representing interaction among attributes. We apply the extended fuzzy measure to an artificial data set and a real dataset in an iron-steel plant. The results verify the usefulness of the extended fuzzy measure compared with other main existing methods.

  19. On Fuzzy Improper Integral and Its Application for Fuzzy Partial Differential Equations

    OpenAIRE

    ElHassan ElJaoui; Said Melliani

    2016-01-01

    We establish some important results about improper fuzzy Riemann integrals; we prove some properties of fuzzy Laplace transforms, which we apply for solving some fuzzy linear partial differential equations of first order, under generalized Hukuhara differentiability.

  20. On Fuzzy Improper Integral and Its Application for Fuzzy Partial Differential Equations

    Directory of Open Access Journals (Sweden)

    ElHassan ElJaoui

    2016-01-01

    Full Text Available We establish some important results about improper fuzzy Riemann integrals; we prove some properties of fuzzy Laplace transforms, which we apply for solving some fuzzy linear partial differential equations of first order, under generalized Hukuhara differentiability.

  1. Web Fuzzy Clustering and a Case Study

    Institute of Scientific and Technical Information of China (English)

    LIU Mao-fu; HE Jing; HE Yan-xiang; HU Hui-jun

    2004-01-01

    We combine the web usage mining and fuzzy clustering and give the concept of web fuzzy clustering, and then put forward the web fuzzy clustering processing model which is discussed in detail. Web fuzzy clustering can be used in the web users clustering and web pages clustering. In the end, a case study is given and the result has proved the feasibility of using web fuzzy clustering in web pages clustering.

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

    Directory of Open Access Journals (Sweden)

    Behrouz Fathi-Vajargah

    2014-01-01

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

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

    Science.gov (United States)

    Tsaur, Ruey-Chyn

    2015-02-01

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

  4. Proposal for inclusion of the risk based inspection technique in Regulatory Standard NR 13; Proposta de inclusao da tecnica de inspecao baseada em risco na Norma Regulamentadora NR 13

    Energy Technology Data Exchange (ETDEWEB)

    Esteves, Vinicius Teixeira; Lima, Marco Aurelio Oliveira [Det Norske Veritas Ltda. (DNV), Rio de Janeiro, RJ (Brazil)

    2012-07-01

    In Brazil, the Regulatory Standard n. 13 (NR 13) establishes requirements for the inspection of boilers and pressure vessels which has main objective of preventing accidents with these types of equipment. Additionally, it has the Risk-Based Inspection (RBI) technique as an effective way to manage the mechanical integrity of various types of static mechanical equipment by through an inspection planning based on the risk factor. In this study, it is being proposed to include the RBI technique, in the NR 13, for the planning and definition of periods for the safety inspection of boilers and pressure vessels in order to promote an increase in the operational safety in process industries in Brazil. In this study it was carried out a critical analysis of NR 13 and RBI, and beyond that a bibliographic research of various international documents that relate the operational safety of pressurized equipment with the inspection activity, and the acceptability of RBI by governments, agencies and organizations around the world. It is considered that the inclusion and formal acceptance of RBI technique in the NR 13 must be accompanied by a rigorous control to avoid the 'trivialization' of its use and ensure the implementation rational, efficient and reliable. Finally, it was developed and suggested basic elements and minimum requirements to be inserted in the NR 13, to be attended, in order mandatory, by the companies that choose the implementation and use of the RBI technique as a tool for the planning of safety inspection of boilers and pressure vessels. It is concluded that the formal acceptance of the RBI technique in the NR 13 could aggregate much value to this standard, with regard to the prevention of accidents involving boilers or pressure vessels, and provide a technological jump to the companies that make use of RBI technique in Brazil. (author)

  5. Type-2 fuzzy granular models

    CERN Document Server

    Sanchez, Mauricio A; Castro, Juan R

    2017-01-01

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

  6. Strong sum distance in fuzzy graphs.

    Science.gov (United States)

    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.

  7. Implementation of Steiner point of fuzzy set.

    Science.gov (United States)

    Liang, Jiuzhen; Wang, Dejiang

    2014-01-01

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

  8. Fuzzy Clustering Methods and their Application to Fuzzy Modeling

    DEFF Research Database (Denmark)

    Kroszynski, Uri; Zhou, Jianjun

    1999-01-01

    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...... prediction of outputs. This article presents an overview of some of the most popular clustering methods, namely Fuzzy Cluster-Means (FCM) and its generalizations to Fuzzy C-Lines and Elliptotypes. The algorithms for computing cluster centers and principal directions from a training data-set are described....... 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...

  9. UNDERSTANDING OF FUZZY OPTIMIZATION:THEORIES AND METHODS

    Institute of Scientific and Technical Information of China (English)

    TANG Jiafu; WANG Dingwei; Richard Y K FUNG; Kai-Leung Yung

    2004-01-01

    A brief summary on and comprehensive understanding of fuzzy optimizationis presentedThis summary is made on aspects of fuzzy modelling and fuzzy optimization,classification and formulation for the fuzzy optimization problems, models and methods.The importance of interpretation of the problem and formulation of the optimal solutionin fuzzy sense are emphasized in the summary of the fuzzy optimization.

  10. Majorizational Choosing of SeveralDifferent Fuzzy Counter Operator

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Different fuzzy reasoning methods were made by choosing different fuzzy operater. This article generally introduced the basic structure of fuzzy controller ,and gave several different fuzzy controllers ,and compared and analyzed different fuzzy counters in theory and computer simulating control and realized majorizational choosing of several fuzzy counters.

  11. Fuzzy random variables — I. definitions and theorems

    NARCIS (Netherlands)

    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

  12. Fuzzy random variables — I. definitions and theorems

    NARCIS (Netherlands)

    Kwakernaak, Huibert

    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 rand

  13. A Bibliography on Fuzzy Automata, Grammars and Lanuages

    NARCIS (Netherlands)

    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 a

  14. A Bibliography on Fuzzy Automata, Grammars and Lanuages

    NARCIS (Netherlands)

    Asveld, Peter 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

  15. Fuzzy random variables — I. definitions and theorems

    NARCIS (Netherlands)

    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 rand

  16. Fuzzy Content-Based Retrieval in Image Databases.

    Science.gov (United States)

    Wu, Jian Kang; Narasimhalu, A. Desai

    1998-01-01

    Proposes a fuzzy-image database model and a concept of fuzzy space; describes fuzzy-query processing in fuzzy space and fuzzy indexing on complete fuzzy vectors; and uses an example image database, the computer-aided facial-image inference and retrieval system (CAFIIR), for explanation throughout. (Author/LRW)

  17. 13. workshop fuzzy systems. Proceedings; 13. Workshop Fuzzy Systeme. Beitraege

    Energy Technology Data Exchange (ETDEWEB)

    Mikut, R.; Reischl, M. (eds.)

    2003-11-01

    This volume contains the papers presented at the 13th workshop on fuzzy systems of TC 5.2.2 'Fuzzy Control' of the VDI/VDE-Gesellschaft fuer Mess- und Automatisierungstechnik (GMA) and the TG 'Fuzzy Systems and Soft Computing' of the Gesellschaft fuer Informatik (GI), which took place at Dortmund on November 19-21, 2003. New methods and applications of fuzzy logic, artificial neuronal nets and evolutionary algorithms were presented. The focus was on automation, e.g. in chemical engineering, energy engineering, motor car engineering, robotics and medical engineering. Other applications, e.g. data mining for technical and non-technical applications, were gone into as well. [German] Dieser Tagungsband enthaelt die Beitraege des 13. Workshops ''Fuzzy System'' des Fachausschusses 5.22 ''Fuzzy Control'' der VDI/VDE-Gesellschaft fuer Mess- und Automatisierungstechnik (GMA) und der Fachgruppe ''Fuzzy-Systeme und Soft-Computing'' der Gesellschaft fuer Informatik (GI), der vom 19.-21. November 2003 im Haus Bommerholz, Dortmund, stattfindet. Der jaehrliche Workshop unseres Fachausschusses bietet ein Forum zur Diskussion neuer methodischer Ansaetze und industrieller Anwendungen auf dem Gebiet der Fuzzy-Logik und in angrenzenden Gebieten wie Kuenstlichen Neuronalen Netzen und Evolutionaeren Algorithmen. Besondere Schwerpunkte sind automatisierungstechnische Anwendungen, z.B. in der Verfahrenstechnik, Energietechnik, Kfz-Technik, Robotik und Medizintechnik, aber auch Loesungen in anderen Problemgebieten (z.B. Data Mining fuer technische und nichttechnische Anwendungen) sind von Interesse. (orig.)

  18. FuzzySTAR: Fuzzy set theory of axiomatic design review

    OpenAIRE

    Huang, GQ; Jiang, Z

    2002-01-01

    Product development involves multiple phases. Design review (DR) is an essential activity formally conducted to ensure a smooth transition from one phase to another. Such a formal DR is usually a multicriteria decision problem, involving multiple disciplines. This paper proposes a systematic framework for DR using fuzzy set theory. This fuzzy approach to DR is considered particularly relevant for several reasons. First, information available at early design phases is often incomplete and impr...

  19. Rough Fuzzy Relation on Two Universal Sets

    Directory of Open Access Journals (Sweden)

    Xuan Thao Nguyen

    2014-03-01

    Full Text Available Fuzzy set theory was introduced by L.A. Zadeh in 1965. Immediately, it has many applications in practice and in building databases, one of which is the construction of a fuzzy relational database based on similar relationship. The study of cases of fuzzy relations in different environments will help us understand its applications. In this paper, the rough fuzzy relation on Cartesian product of two universe sets is defined, and then the algebraic properties of them, such as the max, min, and composition of two rough fuzzy relations are examined. Finally, reflexive, α-reflexive, symmetric and transitive rough fuzzy relations on two universe sets are also defined.

  20. 模糊Prime元%Fuzzy Prime Elements

    Institute of Scientific and Technical Information of China (English)

    饶三平

    2012-01-01

    基于完备剩余格,本文在模糊完备格中,引入模糊Prime元概念.给出了模糊Prime元的等价刻画,证明了所有的模糊Prime元构成的模糊集是模糊完全分配格.%Based on complete residuated lattices, the concept of fuzzy Prime elements in fuzzy complete lattices is given, then the equivalent characterization of fuzzy Prime elements is obtained. We also prove that the fuzzy subsets of fuzzy Prime elements is a fuzzy completely distributice lattice.

  1. FUZZY EPQ INVENTORY MODELS WITH BACKORDER

    Institute of Scientific and Technical Information of China (English)

    Xiaobin WANG; Wansheng TANG

    2009-01-01

    This paper considers the economic production quantity (EPQ) problem with backorder in which the setup cost, the holding cost and the backorder cost are characterized as fuzzy variables, respectively. Following expected value criterion and chance constrained criterion, a fuzzy expected value model (EVM) and a chance constrained programming (CCP) model are constructed. Then fuzzy simulations are employed to estimate the expected value of fuzzy variable and α-level minimal average cost. In order to solve the CCP model, a particle swarm optimization (PSO) algorithm based on the fuzzy simulation is designed. Finally, the effectiveness of PSO algorithm based on the fuzzy simulation is illustrated by a numerical example.

  2. Adaptive Fuzzy Control for CVT Vehicle

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    On the simple continuously variable transmission (CVT) driveline model, the design of adaptive fuzzy control system for CVT vehicle is presented. The adaptive fuzzy control system consists of a scaling factor self-tuning fuzzy-PI throttle controller, and a hybrid fuzzy-PID CVT ratio and brake controller. The presented adaptive fuzzy control strategy is vehicle model independent, which depends only on the instantaneous vehicle states, but does not depend on vehicle parameters. So it has good robustness against uncertain vehicle parameters and exogenous load disturbance. Simulation results show that the proposed adaptive fuzzy strategy has good adaptability and practicality value.

  3. Type-2 fuzzy fractional derivatives

    Science.gov (United States)

    Mazandarani, Mehran; Najariyan, Marzieh

    2014-07-01

    In this paper, we introduce two definitions of the differentiability of type-2 fuzzy number-valued functions of fractional order. The definitions are in the sense of Riemann-Liouville and Caputo derivative of order β ɛ (0, 1), and based on type-2 Hukuhara difference and H2-differentiability. The existence and uniqueness of the solutions of type-2 fuzzy fractional differential equations (T2FFDEs) under Caputo type-2 fuzzy fractional derivative and the definition of Laplace transform of type-2 fuzzy number-valued functions are also given. Moreover, the approximate solution to T2FFDE by a Predictor-Evaluate-Corrector-Evaluate (PECE) method is presented. Finally, the approximate solutions of two examples of linear and nonlinear T2FFDEs are obtained using the PECE method, and some cases of T2FFDEs applications in some sciences are presented.

  4. Intuitionistic fuzzy hierarchical clustering algorithms

    Institute of Scientific and Technical Information of China (English)

    Xu Zeshui

    2009-01-01

    Intuitionistic fuzzy set (IFS) is a set of 2-tuple arguments, each of which is characterized by a mem-bership degree and a nonmembership degree. The generalized form of IFS is interval-valued intuitionistic fuzzy set (IVIFS), whose components are intervals rather than exact numbers. IFSs and IVIFSs have been found to be very useful to describe vagueness and uncertainty. However, it seems that little attention has been focused on the clus-tering analysis of IFSs and IVIFSs. An intuitionistic fuzzy hierarchical algorithm is introduced for clustering IFSs, which is based on the traditional hierarchical clustering procedure, the intuitionistic fuzzy aggregation operator, and the basic distance measures between IFSs: the Hamming distance, normalized Hamming, weighted Hamming, the Euclidean distance, the normalized Euclidean distance, and the weighted Euclidean distance. Subsequently, the algorithm is extended for clustering IVIFSs. Finally the algorithm and its extended form are applied to the classifications of building materials and enterprises respectively.

  5. Fuzzy indicators for customer retention

    National Research Council Canada - National Science Library

    Valenzuela-Fernández, Leslier; Nicolas, Carolina; Gil-Lafuente, Jaime; Merigó, José M

    2016-01-01

    .... Nevertheless, one cannot ignore the existence of a gap on how to measure this relationship. Following this idea, this study proposes six fuzzy key performance indicators that aims to measure customer retention and loyalty of the portfolio...

  6. Semi-Hausdorff Fuzzy Filters

    Directory of Open Access Journals (Sweden)

    V. Lakshmana Gomathi Nayagam

    2007-01-01

    Full Text Available The notion of fuzzy filters was studied by Vicente and Aranguren (1988, Lowen (1979, and Ramakrishnan and Nayagam (2002. The notion of fuzzily compactness was introduced and studied by Ramakrishnan and Nayagam (2002. In this paper, an equivalent condition of fuzzily compactness is studied and a new notion of semi-Hausdorffness on fuzzy filters, which cannot be defined in crisp theory of filters, is introduced and studied.

  7. FUZZY LOGIC IN LEGAL EDUCATION

    Directory of Open Access Journals (Sweden)

    Z. Gonul BALKIR

    2011-04-01

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

  8. Fuzzy Logic Particle Tracking

    Science.gov (United States)

    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

  9. A novel definition of L-fuzzy lattice based on fuzzy set.

    Science.gov (United States)

    Zhang, Jun-Fang

    2013-01-01

    The concept of L-fuzzy lattice is presented by means of an L-fuzzy partially ordered set. An L-fuzzy partially ordered set A is an L-fuzzy lattice if and only if one of A[a], A([a]), and A(a) is a lattice.

  10. On The Transition Probabilities for the Fuzzy States of a Fuzzy Markov Chain

    Directory of Open Access Journals (Sweden)

    J.Earnest Lazarus Piriyakumar

    2015-12-01

    Full Text Available In this paper the theory of fuzzy logic is mixed with the theory of Markov systems and the abstraction of a Markov system with fuzzy states introduced. The notions such as fuzzy transient, fuzzy recurrent etc., were introduced. The results based on these notions are introduced.

  11. Supply chain management under fuzziness recent developments and techniques

    CERN Document Server

    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.

  12. Fuzzy-rough set and fuzzy ID3 decision approaches to knowledge discovery in datasets

    Directory of Open Access Journals (Sweden)

    O. G. Elbarbary

    2012-07-01

    Full Text Available Fuzzy rough sets are the generalization of traditional rough sets to deal with both fuzziness and vagueness in data. The existing researches on fuzzy rough sets mainly concentrate on the construction of approximation operators. Less effort has been put on the knowledge discovery in datasets with fuzzy rough sets. This paper mainly focuses on knowledge discovery in datasets with fuzzy rough sets. After analyzing the previous works on knowledge discovery with fuzzy rough sets, we introduce formal concepts of attribute reduction with fuzzy rough sets and completely study the structure of attribute reduction.

  13. Construction of Fuzzy Map for Autonomous Mobile Robots Based on Fuzzy Confidence Model

    Directory of Open Access Journals (Sweden)

    Jung-Fu Hou

    2014-01-01

    Full Text Available This paper presents the use of fuzzy models to explicitly consider sensor uncertainty and finite resolution in solving the SLAM (simultaneous localization and mapping problem for autonomous mobile robots. The approach establishes fuzzy confidence models in describing occupied obstacles and available space. The problem is transformed into an optimization task of minimizing the alignment error between newly scanned local fuzzy maps and selected parts of a developing global fuzzy map. In aligning local fuzzy maps into a global fuzzy map, we developed a prediction strategy to crop the most potential part from the sensed local fuzzy maps to be overlapped with the global fuzzy map. A mobile vehicle equipped with a laser range finder, the Hokuyo URG-04LX, is used to demonstrate the procedure of fuzzy map building. Experimental results show that the proposed architecture is effective in generating a comprehensive global fuzzy map, which is suitable for both human comprehension and path design during real-time navigation.

  14. FUZZY ARITHMETIC AND SOLVING OF THE STATIC GOVERNING EQUATIONS OF FUZZY FINITE ELEMENT METHOD

    Institute of Scientific and Technical Information of China (English)

    郭书祥; 吕震宙; 冯立富

    2002-01-01

    The key component of finite element analysis of structures with fuzzy parameters,which is associated with handling of some fuzzy information and arithmetic relation of fuzzy variables, was the solving of the governing equations of fuzzy finite element method. Based on a given interval representation of fuzzy numbers, some arithmetic rules of fuzzy numbers and fuzzy variables were developed in terms of the properties of interval arithmetic.According to the rules and by the theory of interval finite element method, procedures for solving the static governing equations of fuzzy finite element method of structures were presented. By the proposed procedure, the possibility distributions of responses of fuzzy structures can be generated in terms of the membership functions of the input fuzzy numbers.It is shown by a numerical example that the computational burden of the presented procedures is low and easy to implement. The effectiveness and usefulness of the presented procedures are also illustrated.

  15. The Relationship of Between Fuzzy Power Groups and Fuzzy Quotient Groups%Fuzzy幂群与Fuzzy商群的相互关系

    Institute of Scientific and Technical Information of China (English)

    闫广霞; 米洪海; 施雅婷

    2006-01-01

    In this paper, we extend the concept of fuzzy quotient groups. The structures of fuzzy power groups and fuzzy quotient groups are discussed. The relationship between fuzzy power groups and fuzzy quotient groups are considered.

  16. Uma aplicação de conjuntos difusos na otimização do prognóstico de consenso sazonal de chuva no Nordeste do Brasil An application of fuzzy sets at otimization of the rainfall seasonal consensus forecast in Brszil's Northeast

    Directory of Open Access Journals (Sweden)

    Emerson Mariano da Silva

    2007-04-01

    Full Text Available Esse estudo apresenta a aplicação da teoria de conjuntos difusos como ferramenta para otimizar a previsão de consenso (PC sazonal de chuva da Região Semi-Árida do Nordeste do Brasil (RSANEB para o período de 1985-1996. Foram utilizados como variáveis de entrada parâmetros termodinâmicos sobre e nos Oceanos Atlântico e Pacífico Tropicais. Os resultados mostraram que qualitativamente, na escala interanual, o resultado determinístico dessa técnica aplicada a PC foi capaz de prever pelo menos uma das categorias da variável de saída (total de chuva de fevereiro a maio da RSANEB. Quantitativamente, os menores erros foram observados para os anos classificados na variável de saída nas categorias de Normal (N, Chuvoso (C, e Muito Chuvoso (MC, com correlações que variam de 0,8 a 0,85, dependendo do método de desfuzificação usado. Esta técnica permite unificar em um resultado determinístico todas as informações climáticas usadas na previsão sazonal de chuva da RSANEB, possibilitando seu prognóstico em mais de uma categoria, informando a mais provável a vir a ocorrer em função do seu nível de pertinência.This study presents the application of fuzzy sets theory as a tool for sazonal rain forecast of Semi-Arid Northeast Region of Brazil for the period of 1985-1996. Thermodynamic parameters in Tropical Atlântic and Pacific Oceans were used as input variables. The results have shown that qualitatively, in an annual scale, this technique was able to forecast at least one of the categories of the output variable (total February/May rain in the of Semi-Arid Northeast Region of Brazil. Quantitatively, the smallest errors have been observed for the years classified according to the output variable in the categories of Normal (N, Rainy (C, and Very Rainy (MC, with correlation coefficients ranging fron 0.8 to 0.85, depending on the defuzzification method used. This technique allows for the unification of all the climatic information

  17. A CAD MODEL FOR FUZZY CONCURRENT TOLERANCE

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Research situation of concurrent tolerance design has been analyzed. As fuzzy factors are objective and unavoidable in concurrent tolerance design, fuzzy optimization theory is applied in the design. A new mathematical model of concurrent tolerance design is constructed.

  18. Analysis of Fuzzy Words in Legal English

    Institute of Scientific and Technical Information of China (English)

    赵波

    2015-01-01

    With the development of legal English,fuzzy words are poured into legislative language and judicial practice constantly.Hence,this paper aims at exploring the application and funtion of different kinds of fuzzy words in legal English.

  19. Compound Option Pricing under Fuzzy Environment

    Directory of Open Access Journals (Sweden)

    Xiandong Wang

    2014-01-01

    Full Text Available Considering the uncertainty of a financial market includes two aspects: risk and vagueness; in this paper, fuzzy sets theory is applied to model the imprecise input parameters (interest rate and volatility. We present the fuzzy price of compound option by fuzzing the interest and volatility in Geske’s compound option pricing formula. For each α, the α-level set of fuzzy prices is obtained according to the fuzzy arithmetics and the definition of fuzzy-valued function. We apply a defuzzification method based on crisp possibilistic mean values of the fuzzy interest rate and fuzzy volatility to obtain the crisp possibilistic mean value of compound option price. Finally, we present a numerical analysis to illustrate the compound option pricing under fuzzy environment.

  20. Fuzzy differential equations in various approaches

    CERN Document Server

    Gomes, Luciana Takata; Bede, Barnabas

    2015-01-01

    This book may be used as reference for graduate students interested in fuzzy differential equations and researchers working in fuzzy sets and systems, dynamical systems, uncertainty analysis, and applications of uncertain dynamical systems. Beginning with a historical overview and introduction to fundamental notions of fuzzy sets, including different possibilities of fuzzy differentiation and metric spaces, this book moves on to an overview of fuzzy calculus thorough exposition and comparison of different approaches. Innovative theories of fuzzy calculus and fuzzy differential equations using fuzzy bunches of functions are introduced and explored. Launching with a brief review of essential theories, this book investigates both well-known and novel approaches in this field; such as the Hukuhara differentiability and its generalizations as well as differential inclusions and Zadeh’s extension. Through a unique analysis, results of all these theories are examined and compared.

  1. Fuzzy relational calculus theory, applications and software

    CERN Document Server

    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...

  2. The lattices of group fuzzy congruences and normal fuzzy subsemigroups on E-inversive semigroups.

    Science.gov (United States)

    Wang, Shoufeng

    2014-01-01

    The aim of this paper is to investigate the lattices of group fuzzy congruences and normal fuzzy subsemigroups on E-inversive semigroups. We prove that group fuzzy congruences and normal fuzzy subsemigroups determined each other in E-inversive semigroups. Moreover, we show that the set of group t-fuzzy congruences and the set of normal subsemigroups with tip t in a given E-inversive semigroup form two mutually isomorphic modular lattices for every t ∈ [0,1].

  3. An Intelligent Trading System with Fuzzy Rules and Fuzzy Capital Management

    OpenAIRE

    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...

  4. On Some Fuzzy Filters in Pseudo-BCI Algebras

    Directory of Open Access Journals (Sweden)

    Xiaohong Zhang

    2014-01-01

    Full Text Available Some new properties of fuzzy associative filters (also known as fuzzy associative pseudo-filters, fuzzy p-filter (also known as fuzzy pseudo-p-filters, and fuzzy a-filter (also known as fuzzy pseudo-a-filters in pseudo-BCI algebras are investigated. By these properties, the following important results are proved: (1 a fuzzy filter (also known as fuzzy pseudo-filters of a pseudo-BCI algebra is a fuzzy associative filter if and only if it is a fuzzy a-filter; (2 a filter (also known as pseudo-filter of a pseudo-BCI algebra is associative if and only if it is an a-filter (also call it pseudo-a filter; (3 a fuzzy filter of a pseudo-BCI algebra is fuzzy a-filter if and only if it is both a fuzzy p-filter and a fuzzy q-filter.

  5. Neuro-fuzzy Control of Integrating Processes

    Directory of Open Access Journals (Sweden)

    Anna Vasičkaninová

    2011-11-01

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

  6. An Investigation into Fuzzy Clustering and Classification.

    Science.gov (United States)

    1984-07-01

    Introduction to Fuzzy Sets The theory of fuzzy sets was developed by Lofti Zadeh in 1965(4). The impetus behind the introduction of the fuzzy set was...Syntactic Pattern Recoonition: An Introduction, Reading, Massachussetts, Addison-Wesley, 1978 4. Zadeh , Lofti A., "Fuzzy Sets", Information and...where the models based on crisp set theory fall short of providing a useful description of things, people, or places. So, as Professor Zadeh proposed

  7. FFLP problem with symmetric trapezoidal fuzzy numbers

    Directory of Open Access Journals (Sweden)

    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.

  8. 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....

  9. Operations on Intuitionistic Fuzzy Graph Structures

    Directory of Open Access Journals (Sweden)

    Muhammad Akram

    2016-12-01

    Full Text Available An intuitionistic fuzzy graph structure (IFGS is a generalization of an intuitionistic fuzzy graph. The concept of intuitionistic fuzzy graph structure is introduced and investigated in this paper. Some operations including union, join, Cartesian product, cross product, lexicographic product, strong product and composition on intuitionistic fuzzy graph structures are defined and elaborated with a number of examples. Some basic properties of these operations are also presented.

  10. Fuzzy Clustering Using C-Means Method

    Directory of Open Access Journals (Sweden)

    Georgi Krastev

    2015-05-01

    Full Text Available The cluster analysis of fuzzy clustering according to the fuzzy c-means algorithm has been described in this paper: the problem about the fuzzy clustering has been discussed and the general formal concept of the problem of the fuzzy clustering analysis has been presented. The formulation of the problem has been specified and the algorithm for solving it has been described.

  11. Aggregation Operator Based Fuzzy Pattern Classifier Design

    DEFF Research Database (Denmark)

    Mönks, Uwe; Larsen, Henrik Legind

    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......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...

  12. Fuzzy Based composition Control of Distillation Column

    Directory of Open Access Journals (Sweden)

    Guru.R

    2013-04-01

    Full Text Available This paper proposed a control scheme based on fuzzy logic for a methanol - water system of bubble cap distillation column. Fuzzy rule base and Inference System of fuzzy (FIS is planned to regulatethe reflux ratio (manipulated variable to obtain the preferred product composition (methanol for a distillation column. Comparisons are made with conventional controller and the results confirmed the potentials of the proposed strategy of fuzzy control.

  13. Consistent linguistic fuzzy preference relations method with ranking fuzzy numbers

    Science.gov (United States)

    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.

  14. Decomposed fuzzy systems and their application in direct adaptive fuzzy control.

    Science.gov (United States)

    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.

  15. On T-Fuzzy Ideals in Nearrings

    Directory of Open Access Journals (Sweden)

    Muhammad Akram

    2007-01-01

    Full Text Available We introduce the notion of fuzzy ideals in nearrings with respect to a t-norm T and investigate some of their properties. Using T-fuzzy ideals, characterizations of Artinian and Noetherian nearrings are established. Some properties of T-fuzzy ideals of the quotient nearrings are also considered.

  16. The fuzzy approach to statistical analysis

    NARCIS (Netherlands)

    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;

  17. Forecasting Enrollments with Fuzzy Time Series.

    Science.gov (United States)

    Song, Qiang; Chissom, Brad S.

    The concept of fuzzy time series is introduced and used to forecast the enrollment of a university. Fuzzy time series, an aspect of fuzzy set theory, forecasts enrollment using a first-order time-invariant model. To evaluate the model, the conventional linear regression technique is applied and the predicted values obtained are compared to the…

  18. Fuzzy image processing in sun sensor

    Science.gov (United States)

    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.

  19. Function Approximation Using Probabilistic Fuzzy Systems

    NARCIS (Netherlands)

    J.H. van den Berg (Jan); U. Kaymak (Uzay); R.J. Almeida e Santos Nogueira (Rui Jorge)

    2011-01-01

    textabstractWe consider function approximation by fuzzy systems. Fuzzy systems are typically used for approximating deterministic functions, in which the stochastic uncertainty is ignored. We propose probabilistic fuzzy systems in which the probabilistic nature of uncertainty is taken into account.

  20. The majority rule in a fuzzy environment.

    OpenAIRE

    Montero, Javier

    1986-01-01

    In this paper, an axiomatic approach to rational decision making in a fuzzy environment is studied. In particular, the majority rule is proposed as a rational way for aggregating fuzzy opinions in a group, when such agroup is defined as a fuzzy set.

  1. 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.

  2. Compactness in L-Fuzzy Topological Spaces

    CERN Document Server

    Luna-Torres, Joaquin

    2010-01-01

    We give a definition of compactness in L-fuzzy topological spaces and provide a characterization of compact L-fuzzy topological spaces, where L is a complete quasi-monoidal lattice with some additional structures, and we present a version of Tychonoff's theorem within the category of L-fuzzy topological spaces.

  3. Full averaging of fuzzy impulsive differential inclusions

    Directory of Open Access Journals (Sweden)

    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.

  4. Design New Robust Self Tuning Fuzzy Backstopping Methodology

    OpenAIRE

    Omid Avatefipour; Farzin Piltan; Mahmoud Reza Safaei Nasrabad; Ghasem Sahamijoo; Alireza Khalilian

    2014-01-01

    This research is focused on proposed Proportional-Integral (PI) like fuzzy adaptive backstopping fuzzy algorithms based on Proportional-Derivative (PD) fuzzy rule base with the adaptation laws derived in the Lyapunov sense. Adaptive SISO PI like fuzzy adaptive backstopping fuzzy method has two main objectives; the first objective is design a SISO fuzzy system to compensate for the model uncertainties of the system, and the second objective is focused on the design PI like fuzzy controller bas...

  5. On Characterization of Rough Type-2 Fuzzy Sets

    OpenAIRE

    Tao Zhao; Zhenbo Wei

    2016-01-01

    Rough sets theory and fuzzy sets theory are important mathematical tools to deal with uncertainties. Rough fuzzy sets and fuzzy rough sets as generalizations of rough sets have been introduced. Type-2 fuzzy set provides additional degree of freedom, which makes it possible to directly handle high uncertainties. In this paper, the rough type-2 fuzzy set model is proposed by combining the rough set theory with the type-2 fuzzy set theory. The rough type-2 fuzzy approximation operators induced f...

  6. Competencies assessment using fuzzy logic

    Directory of Open Access Journals (Sweden)

    Matej Jevšček

    2016-06-01

    Full Text Available Research Question: Competencies evaluation is complex. The question is how to evaluate a competency which was assessed with 360° feedback, in one result using fuzzy logic tools so the result represents an actual competency development in an individual. Purpose: The purpose and goal of the study is to determine a possible process of competency evaluation that would enable creating a single competency assessment using fuzzy logic methods. Method: The theoretical part examines the current state and terminology of competencies and fuzzy logic. The empirical part consists of a quantitative research study. Data from the survey questionnaire was used for model testing. Results: An example of an »Initiative« competency evaluation model is created and tested in the research study. Testing confirmed that evaluation using fuzzy logic is efficient. Organization: The study directly affects the development of the HR function in organizations. It enables an easier and more oriented competency evaluation. Society: The study enables easier orientation in competencies development that can improve the social order as well as social responsibility and the environment indirectly. Originality: The study presents a new competency evaluation model using fuzzy logic. Limitations/Future Research: The study is restricted to one competency and certain assessors. Further research could explore the model with several assessors of the same rank.

  7. 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.

  8. Fuzzy Logic for Incidence Geometry.

    Science.gov (United States)

    Tserkovny, Alex

    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.

  9. Fuzzy Logic for Incidence Geometry

    Science.gov (United States)

    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

  10. A fuzzy system for cloacal temperature prediction of broiler chickens Sistema fuzzy para a predição da temperatura cloacal de frangos de corte

    Directory of Open Access Journals (Sweden)

    Leandro Ferreira

    2012-01-01

    Full Text Available Cloacal temperature (CT of broiler chickens is an important parameter to classify its comfort status; therefore its prediction can be used as decision support to turn on acclimatization systems. The aim of this research was to develop and validate a system using the fuzzy set theory for CT prediction of broiler chickens. The fuzzy system was developed based on three input variables: air temperature (T, relative humidity (RH and air velocity (V. The output variable was the CT. The fuzzy inference system was performed via Mamdani's method which consisted in 48 rules. The defuzzification was done using center of gravity method. The fuzzy system was developed using MAPLE® 8. Experimental results, used for validation, showed that the average standard deviation between simulated and measured values of CT was 0.13°C. The proposed fuzzy system was found to satisfactorily predict CT based on climatic variables. Thus, it could be used as a decision support system on broiler chicken growth.A temperatura cloacal (TC de frangos de corte é um importante parâmetro para classificar a sua condição de conforto, portanto, a sua predição pode ser usada no suporte à decisão de acionamento de sistemas de climatização. Objetivou-se com a presente pesquisa desenvolver e validar um sistema, utilizando a teoria dos conjuntos fuzzy para predição da TC de frangos de corte. O sistema fuzzy foi desenvolvido com base em três variáveis de entrada: temperatura do ar (T, umidade relativa (UR e velocidade do ar (V, tendo, como variável de saída, a TC. A inferência fuzzy foi realizada por meio do método tipo Mamdani, que consistiu na elaboração de 48 regras e a defuzzificação por meio do método do Centro de Gravidade. O sistema fuzzy foi desenvolvido no ambiente computacional MAPLE® 8. Resultados experimentais, usados para a validação, mostraram que o desvio padrão médio entre os valores simulados e medidos de TC foi de 0,13°C. O sistema fuzzy

  11. Implementing fuzzy polynomial interpolation (FPI and fuzzy linear regression (LFR

    Directory of Open Access Journals (Sweden)

    Maria Cristina Floreno

    1996-05-01

    Full Text Available This paper presents some preliminary results arising within a general framework concerning the development of software tools for fuzzy arithmetic. The program is in a preliminary stage. What has been already implemented consists of a set of routines for elementary operations, optimized functions evaluation, interpolation and regression. Some of these have been applied to real problems.This paper describes a prototype of a library in C++ for polynomial interpolation of fuzzifying functions, a set of routines in FORTRAN for fuzzy linear regression and a program with graphical user interface allowing the use of such routines.

  12. Need for fuzzy morphology: erosion as a fuzzy marker

    Science.gov (United States)

    Dougherty, Edward R.; Sinha, Divyendu

    1992-03-01

    The need for fuzzy mathematical morphology is explained in terms of the need for fuzzy erosion in certain types of applications, especially where erosion is serving as a marker, as with hit-or-miss shape recognition. Since erosion is defined by fitting, there at once arises a need for relating fuzzified set inclusion and mathematical morphology. The result is a very general class of Minkowski algebras based upon an axiomatic description of indicator functions that yield acceptable set-inclusion fuzzifications and a subclass of richer Minkowski algebras resulting from an analytic formulation for indicators that is constrained by the axioms.

  13. Fuzzy evaluation method using fuzzy rule approach in multicriteria analysis

    Directory of Open Access Journals (Sweden)

    Othman Mahmod

    2008-01-01

    Full Text Available A multicriteria analysis in ranking the quality of teaching using fuzzy rule is proposed. The proposed method uses the application of fuzzy sets and approximate reasoning in deciding the ranking of the quality of teaching in several courses. The proposed method introduces normalizing data which dampen the extreme value that exists in the data. The use of the model is suitable in evaluating situations that involve subjectivity, vagueness and imprecise information. Experimental results are comparable and the method performs better in some domains. .

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

    Directory of Open Access Journals (Sweden)

    Rodrigo Jensen

    2011-02-01

    potencial y representa un vasto campo para investigaciones.Este estudo teve como objetivo realizar revisão integrativa, investigando como a lógica fuzzy tem sido utilizada em pesquisas com participação de enfermeiros. A busca dos artigos foi realizada nas bases de dados CINAHL, Embase, Scopus, MEDLINE e PubMed, sem intervalo de anos especificado. Foram incluídos artigos na língua portuguesa, inglesa e espanhola; com temática relacionada à enfermagem e à lógica fuzzy, e autoria ou participação de enfermeiros. A amostra final foi de 21 artigos, de oito países. Para análise, os artigos foram distribuídos nas categorias: teoria, método e modelo. Na enfermagem, a lógica fuzzy tem contribuído significativamente para a compreensão de temas relativos à imprecisão ou à necessidade do especialista, como método de pesquisa e no desenvolvimento de modelos ou sistemas de apoio à decisão e de tecnologias duras. O uso da lógica fuzzy, na enfermagem, tem demonstrado grande potencial e representa vasto campo para pesquisas.

  15. Accurate segmentation of leukocyte in blood cell images using Atanassov's intuitionistic fuzzy and interval Type II fuzzy set theory.

    Science.gov (United States)

    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.

  16. Reverse triple I method of fuzzy reasoning

    Institute of Scientific and Technical Information of China (English)

    宋士吉; 吴澄

    2002-01-01

    A theory of reverse triple I method with sustention degree is presented by using the implication operator R0 in every step of the fuzzy reasoning. Its computation formulas of supremum for fuzzy modus ponens and infimum for fuzzy modus tollens are given respectively. Moreover, through the generalization of this problem, the corresponding formulas of ?-reverse triple I method with sustention degree are also obtained. In addition, the theory of reverse triple I method with restriction degree is proposed as well by using the operator R0, and the computation formulas of infimum for fuzzy modus ponens and supremum for fuzzy modus tollens are shown.

  17. Relationship between fuzzy controllers and PID controllers

    Institute of Scientific and Technical Information of China (English)

    李洪兴

    1999-01-01

    The internal relations between fuzzy controllers and PID controllers are revealed. First, it is pointed out that a fuzzy controller with one input and one output is just a piecewise P controller. Then it is proved that a fuzzy controller with two inputs and one output is just a piecewise PD (or I) controller with interaction between P and D (or PI). At last, the conclusion that a fuzzy controller with three inputs and one output is just a piecewise PID controller with interaction among P, I and D is given. Moreover, a kind of difference scheme of fuzzy controllers is designed.

  18. 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.

  19. Truth-value transmittal fuzzy reasoning interpolator

    Institute of Scientific and Technical Information of China (English)

    YAN Jianping; LEUNG Yee

    2005-01-01

    In this paper, we firstly associate fuzzy reasoning algorithm with the interpolation algorithm and discuss the limitation of defuzzification methods used commonly in the fuzzy reasoning algorithm. Secondly, we give a new fuzzy reasoning algorithm in case of single input, called the truth-value transmittal method, and discuss its properties. Finally, we analyze the rationality to adopy the truth-value transmittal method as the defuzzification method of full implication triple I method, and show that although CRI and triple I fuzzy reasoning method are different from fuzzy output set, they are uniform finally under the truth-value transmittal defuzzification method.

  20. Generalized fuzzy ideals of near-rings

    Institute of Scientific and Technical Information of China (English)

    ZHAN Jian-ming; Dawaz B.

    2009-01-01

    The concept of ((∈),(∈)V (q))-fuzzy subnear-rings (ideals) of a near-ring is introduced and some of its related properties are investigated. In particular, the relationships among ordinary fuzzy subnear-rings (ideals), (∈,∈V q)-fuzzy subnear-rings (ideals) and ((∈),(∈)V (q))-fuzzy subnearrings (ideals) of near-rings are described. Finally, some characterization of [μ]t is given by means of (∈,∈V q)-fuzzy ideals.

  1. A novel fuzzy sensor fusion algorithm

    Institute of Scientific and Technical Information of China (English)

    FU Hua; YANG Yi-kui; MA Ke; LIU Yu-jia

    2011-01-01

    A novel fusion algorithm was given based on fuzzy similarity and fuzzy integral theory.First,it calculated the fuzzy similarity among a certain sensor's measurement values and the multiple sensors' objective prediction values to determine the importance weight of each sensor and realize multi-sensor data fusion.Then according to the determined importance weight,an intelligent fusion system based on fuzzy integral theory was given,which can solve FEI-DEO and DEI-DEO fusion problems and realize the decision fusion.Simulation results were proved that fuzzy integral algorithm has enhanced the capability of handling the uncertain information and improved the intelligence degrees.

  2. CONSIDERING NEIGHBORHOOD INFORMATION IN IMAGE FUZZY CLUSTERING

    Institute of Scientific and Technical Information of China (English)

    Huang Ning; Zhu Minhui; Zhang Shourong

    2002-01-01

    Fuzzy C-means clustering algorithm is a classical non-supervised classification method.For image classification, fuzzy C-means clustering algorithm makes decisions on a pixel-by-pixel basis and does not take advantage of spatial information, regardless of the pixels' correlation. In this letter, a novel fuzzy C-means clustering algorithm is introduced, which is based on image's neighborhood system. During classification procedure, the novel algorithm regards all pixels'fuzzy membership as a random field. The neighboring pixels' fuzzy membership information is used for the algorithm's iteration procedure. As a result, the algorithm gives a more smooth classification result and cuts down the computation time.

  3. Fuzzy clustering of mechanisms

    Indian Academy of Sciences (India)

    Amitabha Ghosh; Dilip Kumar Pratihar; M V V Amarnath; Guenter Dittrich; Jorg Mueller

    2012-10-01

    During the course of development of Mechanical Engineering, a large number of mechanisms (that is, linkages to perform various types of tasks) have been conceived and developed. Quite a few atlases and catalogues were prepared by the designers of machines and mechanical systems. However, often it is felt that a clustering technique for handling the list of large number of mechanisms can be very useful,if it is developed based on a scientific principle. In this paper, it has been shown that the concept of fuzzy sets can be conveniently used for this purpose, if an adequate number of properly chosen attributes (also called characteristics) are identified. Using two clustering techniques, the mechanisms have been classified in the present work and in future, it may be extended to develop an expert system, which can automate type synthesis phase of mechanical design. To the best of the authors’ knowledge, this type of clustering of mechanisms has not been attempted before. Thus, this is the first attempt to cluster the mechanisms based on some quantitative measures. It may help the engineers to carry out type synthesis of the mechanisms.

  4. Metrics on Noncompact Fuzzy Number Space (E^)n

    Institute of Scientific and Technical Information of China (English)

    冯玉瑚

    2004-01-01

    The theory of metric spaces of fuzzy numbers has been established and found very convenient in many research fields on fuzzy analysis such as fuzzy integrals and differentials, fuzzy differential equations, fuzzy random variables and fuzzy stochastic processes etc.. But, a large part of this theory heavily depends on the condition that fuzzy number has to have compact support set and so fails to analyze and apply noncompact fuzzy numbers. The purpose of this paper is to introduce three classes of metrics on noncompact fuzzy number space and to discuss their basic properties, completeness and separability in detail.

  5. Fuzzy Entropy: Axiomatic Definition and Neural Networks Model

    Institute of Scientific and Technical Information of China (English)

    QINGMing; CAOYue; HUANGTian-min

    2004-01-01

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

  6. Application of fuzzy logic to social choice theory

    CERN Document Server

    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

  7. Weakly continuous functions on mixed fuzzy topological spaces

    Directory of Open Access Journals (Sweden)

    Binod Chandra Tripathy

    2014-04-01

    Full Text Available The notions of continuity was generalized in the fuzzy setting by Chang (1968. Later on Azad (1981 introduced some weaker form of fuzzy continuity like fuzzy almost continuity, fuzzy semi-continuity and fuzzy weak continuity. These are natural generalization of the corresponding weaker forms of continuity in topological spaces. Recently Arya and Singal (2001a and b introduce another weaker form of fuzzy continuity, namely fuzzy subweakly continuity as a natural generalization of subweak continuity introduced by Rose (1984. In this paper we introduce fuzzy weak continuity in mixed fuzzy topological space.

  8. 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.

  9. Cooperative Answering of Fuzzy Queries

    Institute of Scientific and Technical Information of China (English)

    Narjes Hachani; Mohamed Ali Ben Hassine; Hanène Chettaoui; Habib Ounelli

    2009-01-01

    The majority of existing information systems deals with crisp data through crisp database systems. Traditional Database Management Systems (DBMS) have not taken into account imprecision so one can say there is some sort of lack of flexibility. The reason is that queries retrieve only elements which precisely match to the given Boolean query. That is, an element belongs to the result if the query is true for this element; otherwise, no answers are returned to the user. The aim of this paper is to present a cooperative approach to handling empty answers of fuzzy conjunctive queries by referring to the Formal Concept Analysis (FCA) theory and fuzzy logic. We present an architecture which combines FCA and databases. The processing of fuzzy queries allows detecting the minimal reasons of empty answers. We also use concept lattice in order to provide the user with the nearest answers in the case of a query failure.

  10. Identification Filtering with fuzzy estimations

    Directory of Open Access Journals (Sweden)

    J.J Medel J

    2012-10-01

    Full Text Available A digital identification filter interacts with an output reference model signal known as a black-box output system. The identification technique commonly needs the transition and gain matrixes. Both estimation cases are based on mean square criterion obtaining of the minimum output error as the best estimation filtering. The evolution system represents adaptive properties that the identification mechanism includes considering the fuzzy logic strategies affecting in probability sense the evolution identification filter. The fuzzy estimation filter allows in two forms describing the transition and the gain matrixes applying actions that affect the identification structure. Basically, the adaptive criterion conforming the inference mechanisms set, the Knowledge and Rule bases, selecting the optimal coefficients in distribution form. This paper describes the fuzzy strategies applied to the Kalman filter transition function, and gain matrixes. The simulation results were developed using Matlab©.

  11. Contra continuity and almost contra continuity in generalized fuzzy topological spaces

    Science.gov (United States)

    Bhattacharya, Baby; Chakraborty, Jayasree

    2015-05-01

    In this paper we introduce fuzzy contra continuity and almost contra continuity in generalized fuzzy topological space. Fuzzy almost contra continuity is weaker than fuzzy contra continuity in generalized fuzzy topological space. Then we investigate their characterizations and properties. We also established some equivalent relation on fuzzy contra continuity and fuzzy almost contra continuity in generalized fuzzy topological spaces.

  12. Parallel Fuzzy P+Fuzzy I+Fuzzy D Controller:Design and Performance Evaluation

    Institute of Scientific and Technical Information of China (English)

    Vineet Kumar; A.P.Mittal

    2010-01-01

    In this paper,a parallel fuzzy proportional plus fuzzy integral plus fuzzy derivative (FP+FI+FD) controller is proposed.It is derived from the conventional parallel proportional-integral-derivative (PID) controller.It preserves the linear structure of a conventional parallel PID controller,with analytical formulas.The final shape of the controller is a discrete-time fuzzy version of a conventional parallel PID controller.Computer simulations are performed to evaluate the performance of the FP+FI+FD controller for setpoint tracking and load-disturbance rejection for some complex processes,such as first-and second-order processes with delay,inverse response process with and without delay and higher order processes.Also,the performance of the proposed fuzzy controller is evaluated experimentally on highly nonlinear liquid-flow process with a hysteresis characteristic due to a pneumatic control valve.The simulation and real time control is done using National InstrumentTM hardware and software (LabVIEWTM).The response of the FP+FI+FD controller is compared with the conventional parallel PID controller,tuned with the Ziegler-Nichols (Z-H) and (A)str(o)mH(a)gglund (A-H) tuning technique.It is observed that the FP+FI+FD controller performed much better than the conventional PI/PID controller.Simulation and experimental results demonstrate the effectiveness of the proposed parallel FP+FI+FD controller.

  13. Hypotheses testing for fuzzy robust regression parameters

    Energy Technology Data Exchange (ETDEWEB)

    Kula, Kamile Sanli [Ahi Evran University, Department of Mathematics, 40200 Kirsehir (Turkey)], E-mail: sanli2004@hotmail.com; Apaydin, Aysen [Ankara University, Department of Statistics, 06100 Ankara (Turkey)], E-mail: apaydin@science.ankara.edu.tr

    2009-11-30

    The classical least squares (LS) method is widely used in regression analysis because computing its estimate is easy and traditional. However, LS estimators are very sensitive to outliers and to other deviations from basic assumptions of normal theory [Huynh H. A comparison of four approaches to robust regression. Psychol Bull 1982;92:505-12; Stephenson D. 2000. Available from: (http://folk.uib.no/ngbnk/kurs/notes/node38.html); Xu R, Li C. Multidimensional least-squares fitting with a fuzzy model. Fuzzy Sets and Systems 2001;119:215-23.]. If there exists outliers in the data set, robust methods are preferred to estimate parameters values. We proposed a fuzzy robust regression method by using fuzzy numbers when x is crisp and Y is a triangular fuzzy number and in case of outliers in the data set, a weight matrix was defined by the membership function of the residuals. In the fuzzy robust regression, fuzzy sets and fuzzy regression analysis was used in ranking of residuals and in estimation of regression parameters, respectively [Sanli K, Apaydin A. Fuzzy robust regression analysis based on the ranking of fuzzy sets. Inernat. J. Uncertainty Fuzziness and Knowledge-Based Syst 2008;16:663-81.]. In this study, standard deviation estimations are obtained for the parameters by the defined weight matrix. Moreover, we propose another point of view in hypotheses testing for parameters.

  14. Anaesthesia monitoring using fuzzy logic.

    Science.gov (United States)

    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.

  15. Fuzzy Stochastic Optimization Theory, Models and Applications

    CERN Document Server

    Wang, Shuming

    2012-01-01

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

  16. Introduction to fuzzy logic using Matlab

    CERN Document Server

    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.

  17. Fuzzy Clustering - Principles, Methods and Examples

    DEFF Research Database (Denmark)

    Kroszynski, Uri; Zhou, Jianjun

    1998-01-01

    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...... 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)....

  18. Adaptive fuzzy controllers based on variable universe

    Institute of Scientific and Technical Information of China (English)

    李洪兴

    1999-01-01

    Adaptive fuzzy controllers by means of variable universe are proposed based on interpolation forms of fuzzy control. First, monotonicity of control rules is defined, and it is proved that the monotonicity of interpolation functions of fuzzy control is equivalent to the monotonicity of control rules. This means that there is not any contradiction among the control rules under the condition for the control rules being monotonic. Then structure of the contraction-expansion factor is discussed. At last, three models of adaptive fuzzy control based on variable universe are given which are adaptive fuzzy control model with potential heredity, adaptive fuzzy control model with obvious heredity and adaptive fuzzy control model with successively obvious heredity.

  19. Strong Limit Theorems for Arbitrary Fuzzy Stochastic Sequences

    Institute of Scientific and Technical Information of China (English)

    FEI Wei-yin

    2008-01-01

    Based on fuzzy random variables, the concept of fuzzy stochastic sequences is defined. Strong limit theorems for fuzzy stochastic sequences are established. Some known results in non-fuzzy stochastic sequences are extended. In order to prove results of this paper, the notion of fuzzy martingale difference sequences is also introduced.

  20. Some Duality Results for Fuzzy Nonlinear Programming Problem

    OpenAIRE

    Sangeeta Jaiswal; Geetanjali Panda

    2012-01-01

    The concept of duality plays an important role in optimization theory. This paper discusses some relations between primal and dual nonlinear programming problems in fuzzy environment. Here, fuzzy feasible region for a general fuzzy nonlinear programming is formed and the concept of fuzzy feasible solution is defined. First order dual relation for fuzzy nonlinear programming problem is studied.

  1. Generalized semi-extremally disconnectedness in double fuzzy topological spaces

    Directory of Open Access Journals (Sweden)

    Fatimah M. Mohammed

    2017-03-01

    Full Text Available In this paper we introduce the concepts of (r, s-generalized fuzzy semi-extremally disconnectedness spaces and study the effect of generalized double fuzzy semi-irresolute and generalized double fuzzy semiopen functions in this space. Moreover, we investigate some interesting relationship between generalized double fuzzy semiopen functions and (r, s-generalized fuzzy semi-extremally disconnectedness spaces.

  2. Fuzzy simulation in concurrent engineering

    Science.gov (United States)

    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.

  3. The semantics of fuzzy logic

    Science.gov (United States)

    Ruspini, Enrique H.

    1991-01-01

    Summarized here are the results of recent research on the conceptual foundations of fuzzy logic. The focus is primarily on the principle characteristics of a model that quantifies resemblance between possible worlds by means of a similarity function that assigns a number between 0 and 1 to every pair of possible worlds. Introduction of such a function permits one to interpret the major constructs and methods of fuzzy logic: conditional and unconditional possibility and necessity distributions and the generalized modus ponens of Zadeh on the basis of related metric relationships between subsets of possible worlds.

  4. Fuzzy sets and autonomous navigation

    Science.gov (United States)

    Lea, Robert N.

    1987-01-01

    The use of fuzzy sets in modeling the human expert for certain Space Shuttle navigation problems is discussed with particular reference to onboard and ground console data monitoring tasks traditionally performed by astronauts and engineers. Specific problems include determining the quality of sensor data and of the filter state. The results obtained in this study indicate that fuzzy sets can be successfully used in modeling human reaction to rules in decision-making processes. They can also be used within software systems where guidelines have traditionally been used to set strict tolerances.

  5. Fuzzy simulation in concurrent engineering

    Science.gov (United States)

    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.

  6. Universal fuzzy models and universal fuzzy controllers for discrete-time nonlinear systems.

    Science.gov (United States)

    Gao, Qing; Feng, Gang; Dong, Daoyi; Liu, Lu

    2015-05-01

    This paper investigates the problems of universal fuzzy model and universal fuzzy controller for discrete-time nonaffine nonlinear systems (NNSs). It is shown that a kind of generalized T-S fuzzy model is the universal fuzzy model for discrete-time NNSs satisfying a sufficient condition. The results on universal fuzzy controllers are presented for two classes of discrete-time stabilizable NNSs. Constructive procedures are provided to construct the model reference fuzzy controllers. The simulation example of an inverted pendulum is presented to illustrate the effectiveness and advantages of the proposed method. These results significantly extend the approach for potential applications in solving complex engineering problems.

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

    Science.gov (United States)

    Ma, Shengquan; Li, Shenggang

    2014-01-01

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

  8. Fuzzy PID controller combines with closed-loop optimal fuzzy reasoning for pitch control system

    Science.gov (United States)

    Li, Yezi; Xiao, Cheng; Sun, Jinhao

    2013-03-01

    PID and fuzzy PID controller are applied into the pitch control system. PID control has simple principle and its parameters setting are rather easy. Fuzzy control need not to establish the mathematical of the control system and has strong robustness. The advantages of fuzzy PID control are simple, easy in setting parameters and strong robustness. Fuzzy PID controller combines with closed-loop optimal fuzzy reasoning (COFR), which can effectively improve the robustness, when the robustness is special requirement. MATLAB software is used for simulations, results display that fuzzy PID controller which combines with COFR has better performances than PID controller when errors exist.

  9. Complex fuzzy set-valued complex fuzzy measures and their properties.

    Science.gov (United States)

    Ma, Shengquan; Li, Shenggang

    2014-01-01

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

  10. CALCULATION OF FUZZY RELIABILITYIN THE CASE OF RANDOM STRESSAND FUZZY FATIGUE STRENGTH

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    The fuzzy sets theory is introduced into the fatigue reliability analysis.The concepts of maximizing set and minimizing set are developed to decide the ordering value of each fuzzy number,and these values can be used to determine the order of the fuzzy numbers.On the basis of the works mentioned above,the membership function defining the fuzzy safety event can be calculated,and then the fuzzy reliability in the case of random stress and fuzzy fatigue strength is deduced.An example is given to illustrate the method.

  11. Análise sensorial sob o enfoque da decisão fuzzy Sensorial analysis under the focus of fuzzy logic

    Directory of Open Access Journals (Sweden)

    Regina Serrão Lanzillotti

    1999-08-01

    Full Text Available Este estudo é uma tentativa de aplicação da lógica fuzzy na tomada de decisão em análise sensorial como uma alternativa para avaliar alimentos e preparações alimentares, especialmente em Alimentação Coletiva. A lógica fuzzy permite trabalhar com ambiguidade, abrindo uma perspectiva alternativa de estrutura que substitui a lei do meio excludente de Aristóteles pela lógica de Bertrand Russel, onde uma afirmativa ambígua pode ter valores entre zero e 1. Esta lógica subjetiva, baseada na linguagem natural, é expressa por variável lingüística mapeada pelo conjunto fuzzy. Iniciou-se por quatro hipóteses para verificar a aplicabilidade da lógica fuzzy para tomada de decisão ao avaliar produtos em testes hedônicos. Este estudo usou banco de dados armazenados em uma planilha referente a uma aplicação de testes sensoriais com consumidores, de ambos os sexos, com idade entre 18 a 55 anos; 48 testaram geléia de casca de banana e 50, doce de entrecasca da melancia. Os achados permitem utilizar a lógica fuzzy como uma alternativa às análises clássicas. Enquanto a ANOVA e a MANOVA são usadas em testes para interação entre atributos, a lógica fuzzy mapeia a sensação de "prazer/desprazer" decidindo pela convergência das funções de pertinência de forma holística.This study is an attempt to apply "fuzzy logic" in the decision-making process in sensorial analysis as a way to validate a faster method to evaluate foods and food preparations, specially in Collective Food. Fuzzy logic permits to work with ambiguity, opening a perspective of quantity alternative structure that replaces the Aristotle's law of excluding enviromment by the Bertrand Russel's logic, where an ambiguous affirmative can have values between 0 and 1.This subjective logic, based on a natural language, is mapped by "fuzzy sets". It started by four hypotheses in verify the applicability of fuzzy logic to making decision to accept products in hedonistic tests

  12. A fuzzy control design case: The fuzzy PLL

    Science.gov (United States)

    Teodorescu, H. N.; Bogdan, I.

    1992-01-01

    The aim of this paper is to present a typical fuzzy control design case. The analyzed controlled systems are the phase-locked loops (PLL's)--classic systems realized in both analogic and digital technology. The crisp PLL devices are well known.

  13. Fuzzy set applications in engineering optimization: Multilevel fuzzy optimization

    Science.gov (United States)

    Diaz, Alejandro R.

    1989-01-01

    A formulation for multilevel optimization with fuzzy objective functions is presented. With few exceptions, formulations for fuzzy optimization have dealt with a one-level problem in which the objective is the membership function of a fuzzy set formed by the fuzzy intersection of other sets. In the problem examined here, the goal set G is defined in a more general way, using an aggregation operator H that allows arbitrary combinations of set operations (union, intersection, addition) on the individual sets Gi. This is a straightforward extension of the standard form, but one that makes possible the modeling of interesting evaluation strategies. A second, more important departure from the standard form will be the construction of a multilevel problem analogous to the design decomposition problem in optimization. This arrangement facilitates the simulation of a system design process in which different components of the system are designed by different teams, and different levels of design detail become relevant at different time stages in the process: global design features early, local features later in the process.

  14. Fuzzy Logic Indoor Positioning System

    Directory of Open Access Journals (Sweden)

    Roberto García Sánz

    2008-12-01

    Full Text Available The GPS system is not valid for positioning indoors, thus positioning systems are designed using Wi-Fi technology that allows location of a device inside buildings. The use of fuzzy logic is argued by the failure to find positioning systems based on this technology, which seeks toobserve how their use in this field

  15. Fuzzy C P2 spacetimes

    Science.gov (United States)

    Chaney, A.; Stern, A.

    2017-02-01

    Four-dimensional manifolds with changing signature are obtained by taking the large N limit of fuzzy C P2 solutions to a Lorentzian matrix model. The regions of Lorentzian signature give toy models of closed universes which exhibit cosmological singularities. These singularities are resolved at finite N , as the underlying C P2 solutions are expressed in terms of finite matrix elements.

  16. Rankings from Fuzzy Pairwise Comparisons

    NARCIS (Netherlands)

    Broek, van den Pim; Noppen, Joost; Mohammadian, M.

    2006-01-01

    We propose a new method for deriving rankings from fuzzy pairwise comparisons. It is based on the observation that quantification of the uncertainty of the pairwise comparisons should be used to obtain a better crisp ranking, instead of a fuzzified version of the ranking obtained from crisp pairwise

  17. Fuzzy logic controllers on chip

    OpenAIRE

    Acosta, Nelson; Simonelli, Daniel Horacio

    2002-01-01

    This paper analyzes a fuzzy logic (FL) oriented instruction set (micro)controller and their implementations on FIPSOC1. VHDL code is synthesized using a small portion of FIPSOC FPGA2. This circuits are used from the mP8051 FIPSOC built-in microcontroller to provide efficient arithmetic operations such as multipliers, dividers, minimums and maximums.

  18. 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.

  19. Fuzzy Evidence in Identification, Forecasting and Diagnosis

    CERN Document Server

    Rotshtein, Alexander P

    2012-01-01

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

  20. Learning fuzzy logic control system

    Science.gov (United States)

    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

  1. Fuzzy Prime Ideals in Fuzzy Semigroups%Fuzzy半群中的Fuzzy素理想

    Institute of Scientific and Technical Information of China (English)

    谭宜家

    2001-01-01

    探讨Fuzzy半群中Fuzzy素理想、Fuzzy完全素理想与Fuzzy理想的根的一些代数性质,证明Fuzzy半群中每一个Fuzzy理想是Fuzzy完全半素理想当且仅当它可表为一族Fuzzy完全素理想之交。%In this paper,we obtain some algebraic properties of fuzzy prime ideals,fuzzy completely prime ideals and radicals of fuzzy ideals in fuzzy semigroups,and show that a fuzzy ideal in a fuzzy simigroup is a fuzzy completely semiprime ideal if and only if it is an intersectin of a family of fuzzy completely prime ideals.

  2. An Enhanced Fuzzy Multi Criteria Decision Making Model with A proposed Polygon Fuzzy Number

    Directory of Open Access Journals (Sweden)

    Samah Bekheet

    2014-06-01

    Full Text Available Decisions in real world applications are often made under the presence of conflicting, uncertain, incomplete and imprecise information. Fuzzy multi Criteria Decision making (FMCDM approach provides a powerful approach for drawing rational decisions under uncertainty given in the form of linguistic values. Linguistic values are usually represented as fuzzy numbers. Most of researchers adopt either triangle or trapezoidal fuzzy numbers. Since triangle, intervals, and even singleton are special cases of Trapezoidal fuzzy numbers, so, for most researchers Trapezoidal fuzzy numbers are considered Generalized fuzzy numbers (GFN. In this paper, we introduce polygon fuzzy number (PFN as the actual form of GFN. The proposed form of PFN provides higher flexibility to decision makers to express their own linguistic rather than other form of fuzzy numbers. The given illustrative example ensures such ability for better handling of the FMCDM problems.

  3. Fuzzy Control Strategies in Human Operator and Sport Modeling

    CERN Document Server

    Ivancevic, Tijana T; Markovic, Sasa

    2009-01-01

    The motivation behind mathematically modeling the human operator is to help explain the response characteristics of the complex dynamical system including the human manual controller. In this paper, we present two different fuzzy logic strategies for human operator and sport modeling: fixed fuzzy-logic inference control and adaptive fuzzy-logic control, including neuro-fuzzy-fractal control. As an application of the presented fuzzy strategies, we present a fuzzy-control based tennis simulator.

  4. FUZZY STABILITY ANALYSIS OF MODE COUPLING CHATTER ON CUTTING PROCESS

    Institute of Scientific and Technical Information of China (English)

    1998-01-01

    The influence of fuzzy uncertainty factors is considered on the analysis of chatter occurring during machine tool cutting process. Using fuzzy mathematics analysis methods, a detailed discussion over fuzzy stability analysis problems is presented related to the mode coupling chatter with respect to intrinsic structure fuzzy factors, and the possibility distribution of the fuzzy stability cutting range and the confidence level expressions of the fuzzy stability cutting width are given.

  5. Compound fuzzy model for thermal performance of refrigeration compressors

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    The fuzzy method is introduced to the calculation of thermal performance of refrigeration compressors. A compound model combining classical thermodynamic theory and fuzzy theory is presented and compared with a simple fuzzy model without classical thermodynamic fundamentals. Case study of refrigeration compressors shows that the compound fuzzy model and the simple fuzzy model are both more efficient than the classical thermodynamic method. However, the compound fuzzy model is of better precision and adaptability.

  6. Applications of the Fuzzy Sumudu Transform for the Solution of First Order Fuzzy Differential Equations

    Directory of Open Access Journals (Sweden)

    Norazrizal Aswad Abdul Rahman

    2015-07-01

    Full Text Available In this paper, we study the classical Sumudu transform in fuzzy environment, referred to as the fuzzy Sumudu transform (FST. We also propose some results on the properties of the FST, such as linearity, preserving, fuzzy derivative, shifting and convolution theorem. In order to show the capability of the FST, we provide a detailed procedure to solve fuzzy differential equations (FDEs. A numerical example is provided to illustrate the usage of the FST.

  7. A note on the solution of fuzzy transportation problem using fuzzy linear system

    Directory of Open Access Journals (Sweden)

    P. Senthilkumar

    2013-08-01

    Full Text Available In this paper, we discuss the solution of a fuzzy transportation problem, with fuzzy quantities. The problem is solved in two stages. In the first stage, the fuzzy transportation problem is reduced to crisp system by using the lower and upper bounds of fuzzy quantities. In the second stage, the crisp transportation problems are solved by usual simplex method. The procedure is illustrated with numerical examples.

  8. Taste Identification of Tea Through a Fuzzy Neural Network Based on Fuzzy C-means Clustering

    Institute of Scientific and Technical Information of China (English)

    ZHENG Yan; ZHOU Chun-guang

    2003-01-01

    In this paper, we present a fuzzy neural network model based on Fuzzy C-Means (FCM) clustering algorithm to realize the taste identification of tea. The proposed method can acquire the fuzzy subset and its membership function in an automatic way with the aid of FCM clustering algorithm. Moreover, we improve the fuzzy weighted inference approach. The proposed model is illustrated with the simulation of taste identification of tea.

  9. Fuzzy-TOPSIS Method with Multi-goal

    Institute of Scientific and Technical Information of China (English)

    PANG Jin-hui; ZHANG Qiang

    2009-01-01

    To develop the technique for order preference by similarity to an ideal solution,namely,TOPSIS method with multi-goal in fuzzy decision environment.Firstly,a new approach to constructing fuzzy decision matrix by Choquet integral was proposed in muhi-goal decision system.Secondly,the concepts of fuzzy positive-ideal solution and fuzzy negative-ideal solution related to the fuzzy decision matrix were given.Finally,the credibility measure was adopted to calculate the distances to fuzzy positive-ideal solution and fuzzy negative-ideal solution.The presented fuzzy-TOPSIS method embodies well both the predetermined preferences and the weights of goals.

  10. A fuzzy expert system for diabetes decision support application.

    Science.gov (United States)

    Lee, Chang-Shing; Wang, Mei-Hui

    2011-02-01

    An increasing number of decision support systems based on domain knowledge are adopted to diagnose medical conditions such as diabetes and heart disease. It is widely pointed that the classical ontologies cannot sufficiently handle imprecise and vague knowledge for some real world applications, but fuzzy ontology can effectively resolve data and knowledge problems with uncertainty. This paper presents a novel fuzzy expert system for diabetes decision support application. A five-layer fuzzy ontology, including a fuzzy knowledge layer, fuzzy group relation layer, fuzzy group domain layer, fuzzy personal relation layer, and fuzzy personal domain layer, is developed in the fuzzy expert system to describe knowledge with uncertainty. By applying the novel fuzzy ontology to the diabetes domain, the structure of the fuzzy diabetes ontology (FDO) is defined to model the diabetes knowledge. Additionally, a semantic decision support agent (SDSA), including a knowledge construction mechanism, fuzzy ontology generating mechanism, and semantic fuzzy decision making mechanism, is also developed. The knowledge construction mechanism constructs the fuzzy concepts and relations based on the structure of the FDO. The instances of the FDO are generated by the fuzzy ontology generating mechanism. Finally, based on the FDO and the fuzzy ontology, the semantic fuzzy decision making mechanism simulates the semantic description of medical staff for diabetes-related application. Importantly, the proposed fuzzy expert system can work effectively for diabetes decision support application.

  11. Combinational reasoning of quantitative fuzzy topological relations for simple fuzzy regions.

    Science.gov (United States)

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

    2015-01-01

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

  12. Combinational reasoning of quantitative fuzzy topological relations for simple fuzzy regions.

    Directory of Open Access Journals (Sweden)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Zahran, A.M. [Department of Mathematics, Faculty of Science, Al azhar University, Assuit (Egypt)], E-mail: zahran15@hotmail.com; Abd-Allah, M. Azab. [Department of Mathematics, Faculty of Science, Assuit University, Assuit (Egypt)], E-mail: mazab57@yahoo.com; Abd El-Rahman, Abd El-Nasser G. [Department of Mathematics, Faculty of Science, South valley University, Qena 83523 (Egypt)], E-mail: ghareeb_nasser@yahoo.com

    2009-02-15

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

  14. Terrorism Event Classification Using Fuzzy Inference Systems

    CERN Document Server

    Inyaem, Uraiwan; Meesad, Phayung; Tran, Dat

    2010-01-01

    Terrorism has led to many problems in Thai societies, not only property damage but also civilian casualties. Predicting terrorism activities in advance can help prepare and manage risk from sabotage by these activities. This paper proposes a framework focusing on event classification in terrorism domain using fuzzy inference systems (FISs). Each FIS is a decision-making model combining fuzzy logic and approximate reasoning. It is generated in five main parts: the input interface, the fuzzification interface, knowledge base unit, decision making unit and output defuzzification interface. Adaptive neuro-fuzzy inference system (ANFIS) is a FIS model adapted by combining the fuzzy logic and neural network. The ANFIS utilizes automatic identification of fuzzy logic rules and adjustment of membership function (MF). Moreover, neural network can directly learn from data set to construct fuzzy logic rules and MF implemented in various applications. FIS settings are evaluated based on two comparisons. The first evaluat...

  15. Bayesian system reliability assessment under fuzzy environments

    Energy Technology Data Exchange (ETDEWEB)

    Wu, H.-C

    2004-03-01

    The Bayesian system reliability assessment under fuzzy environments is proposed in this paper. In order to apply the Bayesian approach, the fuzzy parameters are assumed as fuzzy random variables with fuzzy prior distributions. The (conventional) Bayes estimation method will be used to create the fuzzy Bayes point estimator of system reliability by invoking the well-known theorem called 'Resolution Identity' in fuzzy sets theory. On the other hand, we also provide the computational procedures to evaluate the membership degree of any given Bayes point estimate of system reliability. In order to achieve this purpose, we transform the original problem into a nonlinear programming problem. This nonlinear programming problem is then divided into four subproblems for the purpose of simplifying computation. Finally, the subproblems can be solved by using any commercial optimizers, e.g. GAMS or LINGO.

  16. Analysis of inventory difference using fuzzy controllers

    Energy Technology Data Exchange (ETDEWEB)

    Zardecki, A.

    1994-08-01

    The principal objectives of an accounting system for safeguarding nuclear materials are as follows: (a) to provide assurance that all material quantities are present in the correct amount; (b) to provide timely detection of material loss; and (c) to estimate the amount of any loss and its location. In fuzzy control, expert knowledge is encoded in the form of fuzzy rules, which describe recommended actions for different classes of situations represented by fuzzy sets. The concept of a fuzzy controller is applied to the forecasting problem in a time series, specifically, to forecasting and detecting anomalies in inventory differences. This paper reviews the basic notion underlying the fuzzy control systems and provides examples of application. The well-known material-unaccounted-for diffusion plant data of Jaech are analyzed using both feedforward neural networks and fuzzy controllers. By forming a deference between the forecasted and observed signals, an efficient method to detect small signals in background noise is implemented.

  17. Fuzzy associative memories for instrument fault detection

    Energy Technology Data Exchange (ETDEWEB)

    Heger, A.S. [New Mexico Univ., Albuquerque, NM (United States). Dept. of Chemical and Nuclear Engineering; Holbert, K.E.; Ishaque, A.M. [Arizona State Univ., Tempe, AZ (United States)

    1996-06-01

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

  18. FUZZY OPTIMIZATION USING EXTENDED KALMAN FILTER

    Directory of Open Access Journals (Sweden)

    M.DIVYA

    2013-01-01

    Full Text Available Fuzzy Logic is based on the idea that in fuzzy sets each element in the set can assume a value from 0 to 1, not only 0 or 1, as in crisp set theory. The degree of membership function is defined as the gradation in the extent to which an element is belonging to the relevant sets. Optimizing the membership functions of a fuzzy system can be viewed as a system identification problem for nonlinear dynamic system. In this paper two input and one output fuzzy controller is designed for the dynamic process of aircraft. The addition of an EKF in the feedback loop improved the system response by blocking possible effects of measurement error based on Predictor-Corrector algorithm. An Extended Kalman Filter approach to optimize the membership functions of the inputs and outputs of the fuzzy controller. The performance of the fuzzy system before and after the optimization are compared, as well as the membership functions.

  19. (Fuzzy) Ideals of BN-Algebras

    Science.gov (United States)

    Walendziak, Andrzej

    2015-01-01

    The notions of an ideal and a fuzzy ideal in BN-algebras are introduced. The properties and characterizations of them are investigated. The concepts of normal ideals and normal congruences of a BN-algebra are also studied, the properties of them are displayed, and a one-to-one correspondence between them is presented. Conditions for a fuzzy set to be a fuzzy ideal are given. The relationships between ideals and fuzzy ideals of a BN-algebra are established. The homomorphic properties of fuzzy ideals of a BN-algebra are provided. Finally, characterizations of Noetherian BN-algebras and Artinian BN-algebras via fuzzy ideals are obtained. PMID:26125050

  20. Semi-Continuity of Complex Fuzzy Functions

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    This paper introduces the concept of semi-continuity of complex fuzzy functions, and discusses some of their elementary properties, such as the sum of two complex fuzzy functions of type I upper (lower)semi-continuity is type I upper (lower) semi-continuous, and the opposite of complex fuzzy functions of type I upper (lower) semi-continuity is type I lower (upper) semi-continuous. Based on some assumptions on two complex fuzzy functions of type I upper (lower) semi-continuity, it is shown that their product is type I upper (lower) semi-continuous. The paper also investigates the convergence of complex fuzzy functions. In particular, sign theorem, boundedness theorem, and Cauchy's criterion for convergence are kept. In this paper the metrics introduced by Zhang Guangquan was used. This paper gives a contribution to the study of complex fuzzy functions, and extends the corresponding work of Zhang Guangquan.

  1. Fuzzy Identities and Attribute-Based Encryption

    Science.gov (United States)

    Sahai, Amit; Waters, Brent

    We introduce a new type of Identity-Based Encryption (IBE) scheme that we call Fuzzy Identity-Based Encryption. In fuzzy IBE, we view an identity as a set of descriptive attributes. A fuzzy IBE scheme allows for a private key for an identity,ωù, to decrypt a ciphertext encrypted with an identity, ùω´, if and only if the identities ùω and ùω´are close to each other as measured by the "set overlap" distance metric. A fuzzy IBE scheme can be applied to enable encryption using biometric inputs as identities; the error-tolerance property of a fuzzy IBE scheme is precisely what allows for the use of biometric identities, which inherently will have some noise each time they are sampled. Additionally, we show that fuzzy IBE can be used for a type of application that we term "attribute-based encryption."

  2. Optical Generation of Fuzzy-Based Rules

    Science.gov (United States)

    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.

  3. Advanced Control Techniques with Fuzzy Logic

    Science.gov (United States)

    2014-06-01

    AFRL-RQ-WP-TR-2014-0175 ADVANCED CONTROL TECHNIQUES WITH FUZZY LOGIC James E. Combs Structural Validation Branch Aerospace Vehicles...TECHNIQUES WITH FUZZY LOGIC 5a. CONTRACT NUMBER In-house 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 62201F 6. AUTHOR(S) James E. Combs...unlimited. 13. SUPPLEMENTARY NOTES PA Case Number: 88ABW-2014-3281; Clearance Date: 09 Jul 2014. 14. ABSTRACT Research on the Fuzzy Logic control

  4. Investment Portfolio Evaluation by the Fuzzy Approach

    Directory of Open Access Journals (Sweden)

    Lambovska Maya

    2011-09-01

    Full Text Available This paper presents a new fuzzy approach for the evaluation of investment portfolio, where the approach is viewed by the authors as a sub-phase of the management process of these portfolios. The approach defines the mutual and delayed effects among the significant variables of the investment portfolio. The evaluation of the effects is described as fuzzy trapezoidal numbers and they are aggregated by mathematical operations with incidence matrices and fuzzy functions “experton”.

  5. Fuzzy Law and the Boundaries of Secularism

    Directory of Open Access Journals (Sweden)

    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.

  6. Fuzzy Functional Dependencies and Bayesian Networks

    Institute of Scientific and Technical Information of China (English)

    LIU WeiYi(刘惟一); SONG Ning(宋宁)

    2003-01-01

    Bayesian networks have become a popular technique for representing and reasoning with probabilistic information. The fuzzy functional dependency is an important kind of data dependencies in relational databases with fuzzy values. The purpose of this paper is to set up a connection between these data dependencies and Bayesian networks. The connection is done through a set of methods that enable people to obtain the most information of independent conditions from fuzzy functional dependencies.

  7. Fuzzy Clustering of Multiple Instance Data

    Science.gov (United States)

    2015-11-30

    NO. 0704-0188 3. DATES COVERED (From - To) - UU UU UU UU 10-03-2016 Approved for public release; distribution is unlimited. Fuzzy Clustering of...RETURN YOUR FORM TO THE ABOVE ADDRESS. University of Louisville 2301 S. Third Street Jouett Hall Louisville, KY 40208 -1838 ABSTRACT Fuzzy Clustering ...and identify K target concepts simultaneously. The proposed algorithm, called Fuzzy Clustering of Multiple Instance data (FCMI), is tested and

  8. Fuzzy multiple linear regression: A computational approach

    Science.gov (United States)

    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.

  9. New Definition and Properties of Fuzzy Entropy

    Institute of Scientific and Technical Information of China (English)

    Qing Ming; Qin Yingbing

    2006-01-01

    Let X = (x1,x2 ,…,xn ) and F(X) be a fuzzy set on a universal set X. A new definition of fuzzy entropy about a fuzzy set A on F(X), e*, is defined based on the order relation "≤" on [0,1/2] n. It is proved that e* is a σ-entropy under an additional requirement. Besides, some entropy formulas are presented and related properties are discussed.

  10. MINIMAL FUZZY MICROCONTROLLER IMPLEMENTATION FOR DIDACTIC APPLICATIONS

    OpenAIRE

    F. Lara-Rojo; E. N. Sánchez; D. Zaldívar-Navarro

    2003-01-01

    Fuzzy techniques have been successfully used in control in several fields, and engineers and researchers are today considering fuzzy logic algorithms in order to implement intelligent functions in embedded systems. We have started to develop a set of teaching tools to support our courses on intelligent control. Low cost implementations of didactic systems are particularly important in developing countries. In this paper we present the implementation of a minimal PD fuzzy four-rule algorithm i...

  11. 12. workshop fuzzy systems. Proceedings; 12. Workshop Fuzzy Systeme. Proceedings

    Energy Technology Data Exchange (ETDEWEB)

    Mikut, R.; Reischl, M. (eds.)

    2002-11-01

    This annual workshop is a forum for discussing new methods and industrial applications in fuzzy logic and related fields like artificial neuronal nets and evolutionary algorithms. The focus is on applications in automation, e.g. in chemical engineering, energy engineering, automobile engineering, robotics and medical engineering. Other areas of interest are, e.g. data mining for technical and non-technical applications. [German] Der jaehrliche Workshop unseres Fachausschusses bietet ein Forum zur Diskussion neuer methodischer Ansaetze und industrieller Anwendungen auf dem Gebiet der Fuzzy-Logik und in angrenzenden Gebieten wie Kuenstlichen Neuronalen Netzen und Evolutionaeren Algorithmen. Besondere Schwerpunkte sind automatisierungstechnische Anwendungen, z.B. in der Verfahrenstechnik, Enegietechnik, Kfz-Technik, Robotik und Medizintechnik, aber auch Loesungen in anderen Problemgebieten (z.B. Data Mining fuer technische und nichttechnische Anwendungen) sind von Interesse. (orig.)

  12. Supplier Segmentation using Fuzzy Linguistic Preference Relations and Fuzzy Clustering

    Directory of Open Access Journals (Sweden)

    Pegah Sagheb Haghighi

    2014-04-01

    Full Text Available In an environment characterized by its competitiveness, managing and monitoring relationships with suppliers are of the essence. Supplier management includes supplier segmentation. Existing literature demonstrates that suppliers are mostly segmented by computing their aggregated scores, without taking each supplier’s criterion value into account. The principle aim of this paper is to propose a supplier segmentation method that compares each supplier’s criterion value with exactly the same criterion of other suppliers. The Fuzzy Linguistic Preference Relations (LinPreRa based Analytic Hierarchy Process (AHP is first used to find the weight of each criterion. Then, Fuzzy c-means algorithm is employed to cluster suppliers based on their membership degrees. The obtained results show that the proposed method enhances the quality of the previous findings.

  13. GATE TYPE SELECTION BASED ON FUZZY MAPPING

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Gate type selection is very important for mould design. Improper gate type may lead to poor product quality and low production efficiency. Although numerical simulation approach could be used to optimize gate location, the determination of gate type is still up to designers' experience. A novel method for selecting gate type based on fuzzy logic is proposed. The proposed methodology follows three steps:Design requirements for gate is extracted and generalized; Possible gate types (design schemes) are presented; The fuzzy mapping relationship between gate design requirements and gate design scheme is established based on fuzzy composition and fuzzy relation transition matrices that are assigned by domain experts.

  14. Isolated Word Recognition Using Fuzzy Set Theory.

    Science.gov (United States)

    1982-12-01

    chapter. 19 III. Fuzzy Set Theory Introduction The concept of Fuzzy Set Theory was first introduced by Lofti A. Zadeh in 1965 (Ref 19). Since’then...New York: Plenum Press, 1980. 19. Zadeh , L. A. "Fuzzy Sets," Information and Control, 8: 338-353 (1965). A 20. Zadeh , L. A. "Toward a Theory of Fuzzy...Systems," Aspects of Network and Systems Theory. New York: Holt, Rinehart, and Winston, 1971. 21. Zadeh , L. A. "Outline of a New Approach to the

  15. Fuzzy logic control and optimization system

    Science.gov (United States)

    Lou, Xinsheng [West Hartford, CT

    2012-04-17

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

  16. Fuzzy neural network theory and application

    CERN Document Server

    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

  17. Application of Adaptive Fuzzy PID Leveling Controller

    Directory of Open Access Journals (Sweden)

    Ke Zhang

    2013-05-01

    Full Text Available Aiming at the levelling precision, speed and stability of suspended access platform, this paper put forward a new adaptive fuzzy PID control levelling algorithm by fuzzy theory. The method is aided design by using the SIMULINK toolbox of MATLAB, and setting the membership function and the fuzzy-PID control rule. The levelling algorithm can real-time adjust the three parameters of PID according to the fuzzy rules due to the current state. It is experimented, which is verified the algorithm have better stability and dynamic performance.

  18. Fuzzy Design Method of Product Quality Robustness

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    In order to express information on the quality grade of product, designed, the target value of product quality design was described with a fuzzy number in this paper. The rule of robust design with a fuzzy target was analyzed with fuzzy probability theory,then the principle and modeling method of fuzzy robust design for a high quality product were put forward. With this new method used, the high-quality ratio of the product de-signed could be increased, and the ability to resist the influence of various disturbing fac-tors ang noise factors could be enhanced.

  19. Fuzzy sets, rough sets, multisets and clustering

    CERN Document Server

    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.

  20. A computationally efficient fuzzy control s

    Directory of Open Access Journals (Sweden)

    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.

  1. Fuzzy logic control for camera tracking system

    Science.gov (United States)

    Lea, Robert N.; Fritz, R. H.; Giarratano, J.; Jani, Yashvant

    1992-01-01

    A concept utilizing fuzzy theory has been developed for a camera tracking system to provide support for proximity operations and traffic management around the Space Station Freedom. Fuzzy sets and fuzzy logic based reasoning are used in a control system which utilizes images from a camera and generates required pan and tilt commands to track and maintain a moving target in the camera's field of view. This control system can be implemented on a fuzzy chip to provide an intelligent sensor for autonomous operations. Capabilities of the control system can be expanded to include approach, handover to other sensors, caution and warning messages.

  2. Refining fuzzy logic controllers with machine learning

    Science.gov (United States)

    Berenji, Hamid R.

    1994-01-01

    In this paper, we describe the GARIC (Generalized Approximate Reasoning-Based Intelligent Control) architecture, which learns from its past performance and modifies the labels in the fuzzy rules to improve performance. It uses fuzzy reinforcement learning which is a hybrid method of fuzzy logic and reinforcement learning. This technology can simplify and automate the application of fuzzy logic control to a variety of systems. GARIC has been applied in simulation studies of the Space Shuttle rendezvous and docking experiments. It has the potential of being applied in other aerospace systems as well as in consumer products such as appliances, cameras, and cars.

  3. Equipment Selection by using Fuzzy TOPSIS Method

    Science.gov (United States)

    Yavuz, Mahmut

    2016-10-01

    In this study, Fuzzy TOPSIS method was performed for the selection of open pit truck and the optimal solution of the problem was investigated. Data from Turkish Coal Enterprises was used in the application of the method. This paper explains the Fuzzy TOPSIS approaches with group decision-making application in an open pit coal mine in Turkey. An algorithm of the multi-person multi-criteria decision making with fuzzy set approach was applied an equipment selection problem. It was found that Fuzzy TOPSIS with a group decision making is a method that may help decision-makers in solving different decision-making problems in mining.

  4. Characterization of convergence in fuzzy topological spaces

    Directory of Open Access Journals (Sweden)

    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.

  5. Emergent fuzzy geometry and fuzzy physics in $4$ dimensions

    CERN Document Server

    Ydri, Badis; Khaled, Ramda

    2016-01-01

    A detailed Monte Carlo calculation of the phase diagram of bosonic IKKT Yang-Mills matrix models in three and six dimensions with quartic mass deformations is given. Background emergent fuzzy geometries in two and four dimensions are observed with a fluctuation given by a noncommutative $U(1)$ gauge theory very weakly coupled to normal scalar fields. The geometry, which is determined dynamically, is given by the fuzzy spheres ${\\bf S}^2_N$ and ${\\bf S}^2_N\\times{\\bf S}^2_N$ respectively. The three and six matrix models are in the same universality class with some differences. For example, in two dimensions the geometry is completely stable, whereas in four dimensions the geometry is stable only in the limit $M\\longrightarrow \\infty$, where $M$ is the mass of the normal fluctuations. The behavior of the eigenvalue distribution in the two theory is also different. We also sketch how we can obtain a stable fuzzy four-sphere ${\\bf S}^2_N\\times{\\bf S}^2_N$ in the large $N$ limit for all values of $M$ as well as mo...

  6. A KIND OF FUZZY MULTI-OBJECTIVE LINEAR PROGRAMMING PROBLEMS BASED ON INTERVAL VALUED FUZZY SETS

    Institute of Scientific and Technical Information of China (English)

    XU Jiuping

    2001-01-01

    This paper presents a general solution procedure and an interactive fuzzy satisfying method for a kind of fuzzy multi-objective linear programming problems based on interval valued fuzzy sets. Firstly, a fuzzy set of the fuzzy solutions, which can be focused on providing complete information for the final decision, can be obtained by the proposed tolerance analysis of a non-dominated set. Secondly, the satisfying solution for the decisionmaker can be derived from Pareto optimal solutions by updating the current reference membership levels on the basis of the current levels of the membership functions together with the trade-off rates between the membership functions.

  7. A method for solving fully fuzzy linear system with trapezoidal fuzzy numbers

    Directory of Open Access Journals (Sweden)

    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.

  8. A New Method for Solving Fuzzy Linear Programs with Trapezoidal Fuzzy Numbers

    Directory of Open Access Journals (Sweden)

    Jagdeep Kaur

    2011-12-01

    Full Text Available Ganesan and Veeramani [Fuzzy linear programs with trapezoidal fuzzy numbers, Annals of Operations Research 143 (2006 305-315.] proposed a new method for solving a special type of fuzzy linear programming problems. In this paper a new method, named as Mehar's method, is proposed for solving the same type of fuzzy linear programming problems and it is shown that it is easy to apply the Mehar's method as compared to the existing method for solving the same type of fuzzy linear programming problems.

  9. INDIRECT ACCELERATED ADAPTIVE FUZZY CONTROLLER

    Institute of Scientific and Technical Information of China (English)

    ZHU Liye; FANG Yuan; ZHANG Weidong

    2008-01-01

    According to a type of normal nonlinear system, an indirect adaptive fuzzy (IAF) controller has been applied to those systems where no accurate mathematical models of the systems under control are available. To satisfy with system performance, an indirect accelerated adaptive fuzzy (IAAF) controller is proposed, and its general form is presented. The general form IAAF controller ensures necessary control criteria and system's global stability using Lyapunov Theorem. It has been proved that the close-loop system error converges to a small neighborhood of equilibrium point. The optimal IAAF controller is derived to guarantee the process's shortest settling time. Simulation results indicate the IAAF controller make the system more stable, accurate, and fast.

  10. Matrix dynamics of fuzzy spheres

    CERN Document Server

    Jatkar, D P; Wadia, S R; Yogendran, K P; Jatkar, Dileep P.; Mandal, Gautam; Wadia, Spenta R.

    2002-01-01

    We study the dynamics of fuzzy two-spheres in a matrix model which represents string theory in the presence of RR flux. We analyze the stability of known static solutions of such a theory which contain commuting matrices and SU(2) representations. We find that irreducible as well as reducible representations are stable. Since the latter are of higher energy, this stability poses a puzzle. We resolve this puzzle by noting that reducible representations have marginal directions corresponding to non-spherical deformations. We obtain new static solutions by turning on these marginal deformations. These solutions now have instability or tachyonic directions. We discuss condensation of these tachyons which correspond to classical trajectories interpolating from multiple, small fuzzy spheres to a single, large sphere. We briefly discuss spatially independent configurations of a D3/D5 system described by the same matrix model which now possesses a supergravity dual.

  11. A recurrent fuzzy network for fuzzy temporal sequence processing and gesture recognition.

    Science.gov (United States)

    Juang, Chia-Feng; Ku, Ksuan-Chun

    2005-08-01

    A fuzzified Takagi-Sugeno-Kang (TSK)-type recurrent fuzzy network (FTRFN) for handling fuzzy temporal information is proposed in this paper. The FTRFN extends our previously proposed network, TRFN, to deal with fuzzy temporal signals represented by Gaussian or triangular fuzzy numbers. In the precondition part of FTRFN, matching degrees between input fuzzy variables and fuzzy antecedent sets is performed by similarity measure. In the TSK-type consequence, a linear combination of fuzzy variables is computed, where two sets of combination coefficients, one for the center and the other for the width of each fuzzy number, are used. Derivation of the linear combination results and final network output is based on left-right fuzzy number operation. There are no rules in FTRFN initially; they are constructed online by concurrent structure and parameter learning, where all free parameters in the precondition/consequence of FTRFN are all tunable. FTRFN can be applied on a variety of domains related to fuzzy temporal information processing. In this paper, it has been applied on one-dimensional and two-dimensional fuzzy temporal sequence prediction and CCD-based temporal gesture recognition. The performance of FTRFN is verified from these examples.

  12. Weighted Fuzzy Interpolative Reasoning Based on the Slopes of Fuzzy Sets and Particle Swarm Optimization Techniques.

    Science.gov (United States)

    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.

  13. A COMPARISON OF ALTERNATIVE CRITERIA FOR DEFINING FUZZY BOUNDARIES ON FUZZY CATEGORICAL MAPS

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    This paper provides a brief introduction to the methods for generating fuzzy categorical maps from remotely sensed images (in graphical and digital forms). This is followed by a description of the slicing process for deriving fuzzy boundaries from fuzzy categorical maps, which can be based on the maximum fuzzy membership values, confusion index, or measure of entropy. Results from an empirical test preformed in an Edinburgh suburb show that fuzzy boundaries of land cover can be derived from aerial photographs and satellite images by using the three criteria with small differences, and that slicing based on the maximum fuzzy membership values is the easiest and most straightforward solution. This, in turn, implies the suitability of maintaining both a crisp classification and its underlying certainty map for deriving fuzzy boundaries at different thresholds, which is a flexible and compact management of categorical map data and their uncertainty.

  14. Intuitionistic Fuzzy Weighted Linear Regression Model with Fuzzy Entropy under Linear Restrictions.

    Science.gov (United States)

    Kumar, Gaurav; Bajaj, Rakesh Kumar

    2014-01-01

    In fuzzy set theory, it is well known that a triangular fuzzy number can be uniquely determined through its position and entropies. In the present communication, we extend this concept on triangular intuitionistic fuzzy number for its one-to-one correspondence with its position and entropies. Using the concept of fuzzy entropy the estimators of the intuitionistic fuzzy regression coefficients have been estimated in the unrestricted regression model. An intuitionistic fuzzy weighted linear regression (IFWLR) model with some restrictions in the form of prior information has been considered. Further, the estimators of regression coefficients have been obtained with the help of fuzzy entropy for the restricted/unrestricted IFWLR model by assigning some weights in the distance function.

  15. m-Polar fuzzy sets: an extension of bipolar fuzzy sets.

    Science.gov (United States)

    Chen, Juanjuan; Li, Shenggang; Ma, Shengquan; Wang, Xueping

    2014-01-01

    Recently, bipolar fuzzy sets have been studied and applied a bit enthusiastically and a bit increasingly. In this paper we prove that bipolar fuzzy sets and [0,1](2)-sets (which have been deeply studied) are actually cryptomorphic mathematical notions. Since researches or modelings on real world problems often involve multi-agent, multi-attribute, multi-object, multi-index, multi-polar information, uncertainty, or/and limit process, we put forward (or highlight) the notion of m-polar fuzzy set (actually, [0,1] (m)-set which can be seen as a generalization of bipolar fuzzy set, where m is an arbitrary ordinal number) and illustrate how many concepts have been defined based on bipolar fuzzy sets and many results which are related to these concepts can be generalized to the case of m-polar fuzzy sets. We also give examples to show how to apply m-polar fuzzy sets in real world problems.

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

    Directory of Open Access Journals (Sweden)

    Dhruba Das

    2015-04-01

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

  17. Probabilistic and fuzzy logic in clinical diagnosis.

    Science.gov (United States)

    Licata, G

    2007-06-01

    In this study I have compared classic and fuzzy logic and their usefulness in clinical diagnosis. The theory of probability is often considered a device to protect the classical two-valued logic from the evidence of its inadequacy to understand and show the complexity of world [1]. This can be true, but it is not possible to discard the theory of probability. I will argue that the problems and the application fields of the theory of probability are very different from those of fuzzy logic. After the introduction on the theoretical bases of fuzzy approach to logic, I have reported some diagnostic argumentations employing fuzzy logic. The state of normality and the state of disease often fight their battle on scalar quantities of biological values and it is not hard to establish a correspondence between the biological values and the percent values of fuzzy logic. Accordingly, I have suggested some applications of fuzzy logic in clinical diagnosis and in particular I have utilised a fuzzy curve to recognise subjects with diabetes mellitus, renal failure and liver disease. The comparison between classic and fuzzy logic findings seems to indicate that fuzzy logic is more adequate to study the development of biological events. In fact, fuzzy logic is useful when we have a lot of pieces of information and when we dispose to scalar quantities. In conclusion, increasingly the development of technology offers new instruments to measure pathological parameters through scalar quantities, thus it is reasonable to think that in the future fuzzy logic will be employed more in clinical diagnosis.

  18. Fuzzy clustering, genetic algorithms and neuro-fuzzy methods compared for hybrid fuzzy-first principles modeling

    NARCIS (Netherlands)

    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

  19. Fuzzy Clustering, Genetic Algorithms and Neuro-Fuzzy Methods Compared for Hybrid Fuzzy-First Principles Modeling

    NARCIS (Netherlands)

    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

  20. A combination of extended fuzzy AHP and fuzzy GRA for government E-tendering in hybrid fuzzy environment.

    Science.gov (United States)

    Wang, Yan; Xi, Chengyu; Zhang, Shuai; Yu, Dejian; Zhang, Wenyu; Li, Yong

    2014-01-01

    The recent government tendering process being conducted in an electronic way is becoming an inevitable affair for numerous governmental agencies to further exploit the superiorities of conventional tendering. Thus, developing an effective web-based bid evaluation methodology so as to realize an efficient and effective government E-tendering (GeT) system is imperative. This paper firstly investigates the potentiality of employing fuzzy analytic hierarchy process (AHP) along with fuzzy gray relational analysis (GRA) for optimal selection of candidate tenderers in GeT process with consideration of a hybrid fuzzy environment with incomplete weight information. We proposed a novel hybrid fuzzy AHP-GRA (HFAHP-GRA) method that combines an extended fuzzy AHP with a modified fuzzy GRA. The extended fuzzy AHP which combines typical AHP with interval AHP is proposed to obtain the exact weight information, and the modified fuzzy GRA is applied to aggregate different types of evaluation information so as to identify the optimal candidate tenderers. Finally, a prototype system is built and validated with an illustrative example for GeT to confirm the feasibility of our approach.

  1. Fuzzy Clustering, Genetic Algorithms and Neuro-Fuzzy Methods Compared for Hybrid Fuzzy-First Principles Modeling

    NARCIS (Netherlands)

    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 transfe

  2. Fuzzy Clustering, Genetic Algorithms and Neuro-Fuzzy Methods Compared for Hybrid Fuzzy-First Principles Modeling

    NARCIS (Netherlands)

    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 transfe

  3. Fuzzy logic based robotic controller

    Science.gov (United States)

    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.

  4. Evaluation of remedial options for a benzene-contaminated site through a simulation-based fuzzy-MCDA approach.

    Science.gov (United States)

    Yang, A L; Huang, G H; Qin, X S; Fan, Y R

    2012-04-30

    A simulation-based fuzzy multi-criteria decision analysis (SFMCDA) method is developed for supporting the selection of remediation strategies for petroleum contaminated sites. SFMCDA integrates process modeling (using BIOPLUME III) and fuzzy ranking (based on fuzzy TOPSIS) into a general management framework, and can compare various remediation alternatives, in light of both cost-risk tradeoffs and uncertainty impacts. The proposed method is applied to a hypothetical contaminated site suffering from a benzene leakage problem. Six remediation alternatives are taken into consideration, including natural attenuation (NA), pump-and-treat (PAT), enhanced natural attenuation (ENA), and a number of their combinations. Six fuzzy criteria, including both cost and risk information, are used to compare different alternatives through fuzzy TOPSIS. The results demonstrates that the proposed method can help systematically analyze fuzzy inputs from contaminant transport modeling, cost implications and stakeholders' preferences, and provide useful ranking information covering a variety of decision-relevant remediation options for decision makers. Crown Copyright © 2012. Published by Elsevier B.V. All rights reserved.

  5. Estimate of the weight of japanese quail eggs through fuzzy sets theory Estimativa do peso dos ovos de codornas japonesas por meio da teoria dos conjuntos fuzzy

    Directory of Open Access Journals (Sweden)

    Jaqueline de Oliveira Castro

    2012-02-01

    Full Text Available Quail breeding is a viable alternative for animal production and due to its low investment, fast return of invested capital, use of small areas and creation of jobs has aroused much interest in Brazil. The aim of this study was to develop a model based on fuzzy set theory to predict the weight of eggs from Japanese quails. The proposed fuzzy model was based on data from field measurement experiments, as well as from literature referring to the influence of environment over the weight of eggs. To develop the fuzzy system, air dry-bulb temperature (t db, ° C and relative air humidity (RH, % were defined as input variables and trapezoidal and triangular membership functions were used, respectively. The absolute deviation between the values for observed egg weight and egg weight estimated by the fuzzy system, varied between 0.01 g and 0.32 g, and the average deviation was 0.14 g. The average error found was 2.33%, and the determination coefficient (R² was equal to 0.668. The fuzzy system developed to estimate the weight of Japanese quail eggs, based on the t db and RH provided low values for absolute deviation and percentage error, allows a realistic estimate of the weight of eggs in different environmental conditions.A cotornicultura é uma alternativa na produção animal que, pelo baixo investimento, rápido retorno do capital investido, utilização de pequenas áreas e à gereção de novos empregos, tem despertado grande interesse no Brasil. Neste trabalho, objetivou-se desenvolver um modelo baseado na teoria dos conjuntos fuzzy para a predição do peso de ovos de codornas japonesas. O modelo fuzzy proposto foi elaborado com base em dados experimentais oriundos de medições em campo, bem como da literatura, a respeito da influência do ambiente sobre o peso de ovos de codornas japonesas de postura. Para o desenvolvimento do sistema fuzzy, foram definidas, como variáveis de entrada, a temperatura de bulo seco (t bs, °C e a umidade

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

    CERN Document Server

    Jiménez-Losada, Andrés

    2017-01-01

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

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

    Directory of Open Access Journals (Sweden)

    K. A. Halim

    2011-01-01

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

  8. 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.

  9. Fuzzy modeling and synchronization of hyper chaotic systems

    Energy Technology Data Exchange (ETDEWEB)

    Zhang Hongbin [Center for Nonlinear and Complex Systems, School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 610054 (China)] e-mail: zhanghb@uestc.edu.cn; Liao Xiaofeng [Center for Nonlinear and Complex Systems, School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 610054 (China); Institute of Computer Science, Chongqing University, Chongqing 400044 (China); Yu Juebang [Center for Nonlinear and Complex Systems, School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 610054 (China)

    2005-11-01

    This paper presents fuzzy model-based designs for synchronization of hyper chaotic systems. The T-S fuzzy models for hyper chaotic systems are exactly derived. Based on the T-S fuzzy hyper chaotic models, the fuzzy controllers for hyper chaotic synchronization are designed via the exact linearization techniques. Numerical examples are given to demonstrate the effectiveness of the proposed method.

  10. INDUCTION OF DECISION TREES BASED ON A FUZZY NEURAL NETWORK

    Institute of Scientific and Technical Information of China (English)

    Tang Bin; Hu Guangrui; Mao Xiaoquan

    2002-01-01

    Based on a fuzzy neural network, the letter presents an approach for the induction of decision trees. The approach makes use of the weights of fuzzy mappings in the fuzzy neural network which has been trained. It can realize the optimization of fuzzy decision trees by branch cutting, and improve the ratio of correctness and efficiency of the induction of decision trees.

  11. 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 $widetilde{A}widetilde{X}= widetilde{lambda} widetilde{X}.$

  12. Some Structure Properties of the Cyclic Fuzzy Group Family

    Institute of Scientific and Technical Information of China (English)

    Hacl Akta(s); Naim (C)a(g)man

    2005-01-01

    In crisp environment, the notion of cyclic group on a set is well known. We study an extension of this classical notion to the fuzzy sets to define the concept of cyclic fuzzy subgroups. By using these cyclic fuzzy subgroups, we then define a cyclic fuzzy group family and investigate its structure properties.

  13. Minimal solution of singular LR fuzzy linear systems.

    Science.gov (United States)

    Nikuie, M; Ahmad, M Z

    2014-01-01

    In this paper, the singular LR fuzzy linear system is introduced. Such systems are divided into two parts: singular consistent LR fuzzy linear systems and singular inconsistent LR fuzzy linear systems. The capability of the generalized inverses such as Drazin inverse, pseudoinverse, and {1}-inverse in finding minimal solution of singular consistent LR fuzzy linear systems is investigated.

  14. Expected Value Method for Fuzzy Multiple Attribute Decision Making

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    This paper presents a fuzzy multiple attribute decision-making (FMADM) method in which the attribute weights and decision matrix elements (attribute values) are fuzzy variables. Fuzzy arithmetic and the expected value operator of fuzzy variables are used to develop the expected value method to solve the FMADM problem. A numerical example is given to demonstrate the feasibility and effectiveness of the method.

  15. Fuzzy GML Modeling Based on Vague Soft Sets

    Directory of Open Access Journals (Sweden)

    Bo Wei

    2017-01-01

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

  16. A Fuzzy Neural Network for Fault Pattern Recognition

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    This paper combines fuzzy set theory with AR T neural network, and demonstrates some important properties of the fuzzy ART neural network algorithm. The results from application on a ball bearing diagnosis indicate that a fuzzy ART neural network has an effect of fast stable recognition for fuzzy patterns.

  17. An inclusion measure between fuzzy sets

    Science.gov (United States)

    Wang, Jing

    2017-01-01

    In this paper, we propose a new inclusion measure between fuzzy sets. Firstly, we select an axiomatic definition for the inclusion measure. Then, we present a new computation formula based on the selected axiomatic definition, and demonstrate its two properties. Finally, we give examples to validate its performance. The results show that the new inclusion measure is rational for fuzzy sets.

  18. Modeling Research Project Risks with Fuzzy Maps

    Science.gov (United States)

    Bodea, Constanta Nicoleta; Dascalu, Mariana Iuliana

    2009-01-01

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

  19. Bounded Rationality of Generalized Abstract Fuzzy Economies

    Directory of Open Access Journals (Sweden)

    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.

  20. The Self-Organising Fuzzy Controller

    DEFF Research Database (Denmark)

    Jantzen, Jan

    1998-01-01

    A marginally stable test system, with a large dead time and an integrator, is stabilised by a self-organising fuzzy controller in a simulation study. It acts as a case study, to explain the self-organising controller to engineering students. The paper is one of a series of tutorial papers...... for a course in fuzzy control....

  1. Using Fuzzy Lists for Playlist Management

    DEFF Research Database (Denmark)

    Deliege, Francois; Pedersen, Torben Bach

    2008-01-01

    a concrete scenario to illustrate their possibilities. Additionally, to enable the development of playlist management tools, a formal foundation is provided. Therefore, the concept of fuzzy lists is defined and a corresponding algebra is developed. Fuzzy lists offer a solution perfectly suited to meet...

  2. Fuzzy logic mode switching in helicopters

    Science.gov (United States)

    Sherman, Porter D.; Warburton, Frank W.

    1993-01-01

    The application of fuzzy logic to a wide range of control problems has been gaining momentum internationally, fueled by a concentrated Japanese effort. Advanced Research & Development within the Engineering Department at Sikorsky Aircraft undertook a fuzzy logic research effort designed to evaluate how effective fuzzy logic control might be in relation to helicopter operations. The mode switching module in the advanced flight control portion of Sikorsky's motion based simulator was identified as a good candidate problem because it was simple to understand and contained imprecise (fuzzy) decision criteria. The purpose of the switching module is to aid a helicopter pilot in entering and leaving coordinated turns while in flight. The criteria that determine the transitions between modes are imprecise and depend on the varied ranges of three flight conditions (i.e., simulated parameters): Commanded Rate, Duration, and Roll Attitude. The parameters were given fuzzy ranges and used as input variables to a fuzzy rulebase containing the knowledge of mode switching. The fuzzy control program was integrated into a real time interactive helicopter simulation tool. Optimization of the heading hold and turn coordination was accomplished by interactive pilot simulation testing of the handling quality performance of the helicopter dynamic model. The fuzzy logic code satisfied all the requirements of this candidate control problem.

  3. Numerical method for solving fuzzy wave equation

    Science.gov (United States)

    Kermani, M. Afshar

    2013-10-01

    In this study a numerical method for solving "fuzzy partial differential equation" (FPDE) is considered. We present difference method to solve the FPDEs such as fuzzy hyperbolic equation, then see if stability of this method exist, and conditions for stability are given.

  4. Fuzzy Control in the Process Industry

    DEFF Research Database (Denmark)

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

    1999-01-01

    Control problems in the process industry are dominated by non-linear and time-varying behaviour, many inner loops, and much interaction between the control loops. Fuzzy controllers have in some cases nevertheless mimicked the control actions of a human operator. Simple fuzzy controllers can...

  5. CRUISE FUZZY CONTROL FOR AUTOMOBILE WITH CVT

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    To develop cruise control system of an automobile with the metal pushing V-belt type CVT, the dynamic model of automobile travelling longitudinally is established, and the fuzzy controller of control system is designed. Considering uncertainty system parameter and exterior resistance disturbances, the stability of controller is investigated by simulating. The results of its simulation show that the fuzzy controller designed has practicability.

  6. 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...

  7. The Self-Organising Fuzzy Controller

    DEFF Research Database (Denmark)

    Jantzen, Jan

    1998-01-01

    A marginally stable test system, with a large dead time and an integrator, is stabilised by a self-organising fuzzy controller in a simulation study. It acts as a case study, to explain the self-organising controller to engineering students. The paper is one of a series of tutorial papers...... for a course in fuzzy control....

  8. Scalar Field Theory on Fuzzy S^4

    CERN Document Server

    Medina, J; Medina, Julieta; Connor, Denjoe O'

    2003-01-01

    Scalar fields are studied on fuzzy $S^4$ and a solution is found for the elimination of the unwanted degrees of freedom that occur in the model. The resulting theory can be interpreted as a Kaluza-Klein reduction of CP^3 to S^4 in the fuzzy context.

  9. 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.

  10. Intuitionistic fuzzy segmentation of medical images.

    Science.gov (United States)

    Chaira, Tamalika

    2010-06-01

    This paper proposes a novel and probably the first method, using Attanassov intuitionistic fuzzy set theory to segment blood vessels and also the blood cells in pathological images. This type of segmentation is very important in detecting different types of human diseases, e.g., an increase in the number of vessels may lead to cancer in prostates, mammary, etc. The medical images are not properly illuminated, and segmentation in that case becomes very difficult. A novel image segmentation approach using intuitionistic fuzzy set theory and a new membership function is proposed using restricted equivalence function from automorphisms, for finding the membership values of the pixels of the image. An intuitionistic fuzzy image is constructed using Sugeno type intuitionistic fuzzy generator. Local thresholding is applied to threshold medical images. The results showed a much better performance on poor contrast medical images, where almost all the blood vessels and blood cells are visible properly. There are several fuzzy and intuitionistic fuzzy thresholding methods, but these methods are not related to the medical images. To make a comparison with the proposed method with other thresholding methods, the method is compared with six nonfuzzy, fuzzy, and intuitionistic fuzzy methods.

  11. Homeopathic drug selection using Intuitionistic fuzzy sets.

    Science.gov (United States)

    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.

  12. 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 ...

  13. An Investment Decision using Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    Marius Bălaş

    2011-06-01

    Full Text Available The paper presents a decision-making case study: the choice of a production line for natural juices, among 10 offers com-ing from 5 countries. 6 performance criteria are applied, some of them being fuzzy. Two solutions are provided: a conventional one, based on the affiliation degrees calculus and a fuzzy-interpolative one.

  14. Stability of Cascaded Fuzzy Systems and Observers

    NARCIS (Netherlands)

    Lendek, Z.; Babuska, R.; De Schutter, B.

    2009-01-01

    A large class of nonlinear systems can be well approximated by Takagi-Sugeno (TS) fuzzy models with linear or affine consequents. It is well known that the stability of these consequent models does not ensure the stability of the overall fuzzy system. Therefore, several stability conditions have bee

  15. VARIATIONAL PRINCIPLE FOR FUZZY GIBBS MEASURES

    NARCIS (Netherlands)

    Verbitskiy, Evgeny

    2010-01-01

    In this paper we study a large class of renormalization transformations of measures on lattices. An image of a Gibbs measure under such transformation is called a fuzzy Gibbs measure. Transformations of this type and fuzzy Gibbs measures appear naturally in many fields. Examples include the hidden M

  16. A Simplified Description of Fuzzy TOPSIS

    CERN Document Server

    Sodhi, Balwinder

    2012-01-01

    A simplified description of Fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Situation) is presented. We have adapted the TOPSIS description from existing Fuzzy theory literature and distilled the bare minimum concepts required for understanding and applying TOPSIS. An example has been worked out to illustrate the application of TOPSIS for a multi-criteria group decision making scenario.

  17. Decompositions of Revised Monotone Signed Fuzzy Measures

    Institute of Scientific and Technical Information of China (English)

    张强; 刘克

    2003-01-01

    The concept of fuzzy measure was introduced by Sugeno in 1974. A notion of signed fuzzy measure is introduced in this paper, and its elementary properties are briefly discussed. An analogue of Hahn decomposition theorem is established under the null-null-additive condition. A version of the Jordan decomposition theorem is proved under the null-additive condition.

  18. On the Power of Fuzzy Markup Language

    CERN Document Server

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

    2013-01-01

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

  19. On mathematical structures of fuzzy rough set algebras

    Institute of Scientific and Technical Information of China (English)

    WU Wei-zhi

    2008-01-01

    In rough set theory, the lower and upper approximation operators are important notions defined by a binary rela-tion. In this paper, we introduce a general type of relation-based fuzzy rough model determined by a triangular norm. Prop-erties of fuzzy rough approximation operators are examined. The fuzzy rough approximation operators are also characterized by axioms. A comparative study of the fuzzy rough set algebra with other mathematical structures such as fuzzy topological spaces, fuzzy measurable spaces, and fuzzy belief structures is investigated.

  20. Fabric Wrinkle Grade Assessment Based on Fuzzy Pattern Recognition

    Institute of Scientific and Technical Information of China (English)

    YANG Xiao-bo

    2006-01-01

    The basic principle of fuzzy pattern recognition is brief introduced firstly in this paper, which mainly includes fuzzy rules and fuzzy inference system. Then, the algorithm procedure of fuzzy pattern recognition is proposed. Finally,the application of Mamdani fuzzy model is introduced to evaluate fabric wrinkle grade in detail, and used the correlation coefficient between subject and object evaluation to verify the reliability of fuzzy pattern recognition. It shows the method of fuzzy pattern recognition needs not a large number of testing data and the accuracy of evaluation is up to 97.38%.

  1. Transportation optimization with fuzzy trapezoidal numbers based on possibility theory.

    Science.gov (United States)

    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.

  2. Describing fuzzy sets using a new concept:fuzzify functor

    Institute of Scientific and Technical Information of China (English)

    魏克新; 王兆霞; 王权

    2009-01-01

    This paper proposed a fuzzify functor as an extension of the concept of fuzzy sets.The fuzzify functor and the first-order operated fuzzy set are defined.From the theory analysis,it can be observed that when the fuzzify functor acts on a simple crisp set,we get the first order fuzzy set or type-1 fuzzy set.By operating the fuzzify functor on fuzzy sets,we get the higher order fuzzy sets or higher type fuzzy sets and their membership functions.Using the fuzzify functor we can exactly describe the type-1 fuzz...

  3. A FUZZY FILTERING MODEL FOR CONTOUR DETECTION

    Directory of Open Access Journals (Sweden)

    T.C. Rajakumar

    2011-04-01

    Full Text Available Contour detection is the basic property of image processing. Fuzzy Filtering technique is proposed to generate thick edges in two dimensional gray images. Fuzzy logic is applied to extract value for an image and is used for object contour detection. Fuzzy based pixel selection can reduce the drawbacks of conventional methods(Prewitt, Robert. In the traditional methods, filter mask is used for all kinds of images. It may succeed in one kind of image but fail in another one. In this frame work the threshold parameter values are obtained from the fuzzy histogram of the input image. The Fuzzy inference method selects the complete information about the border of the object and the resultant image has less impulse noise and the contrast of the edge is increased. The extracted object contour is thicker than the existing methods. The performance of the algorithm is tested with Peak Signal Noise Ratio(PSNR and Complex Wavelet Structural Similarity Metrics(CWSSIM.

  4. Fuzzy modeling and control theory and applications

    CERN Document Server

    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.

  5. Robust Visual Tracking via Fuzzy Kernel Representation

    Directory of Open Access Journals (Sweden)

    Zhiqiang Wen

    2013-05-01

    Full Text Available A robust visual kernel tracking approach is presented for solving the problem of existing background pixels in object model. At first, after definition of fuzzy set on image is given, a fuzzy factor is embedded into object model to form the fuzzy kernel representation. Secondly, a fuzzy membership functions are generated by center-surround approach and log likelihood ratio of feature distributions. Thirdly, details about fuzzy kernel tracking algorithm is provided. After that, methods of parameter selection and performance evaluation for tracking algorithm are proposed. At last, a mass of experimental results are done to show our method can reduce the influence of the incomplete representation of object model via integrating both color features and background features.

  6. Improvement on fuzzy controller design techniques

    Science.gov (United States)

    Wang, Paul P.

    1993-01-01

    This paper addresses three main issues, which are somewhat interrelated. The first issue deals with the classification or types of fuzzy controllers. Careful examination of the fuzzy controllers designed by various engineers reveals distinctive classes of fuzzy controllers. Classification is believed to be helpful from different perspectives. The second issue deals with the design according to specifications, experiments related to the tuning of fuzzy controllers, according to the specification, will be discussed. General design procedure, hopefully, can be outlined in order to ease the burden of a design engineer. The third issue deals with the simplicity and limitation of the rule-based IF-THEN logical statements. The methodology of fuzzy-constraint network is proposed here as an alternative to the design practice at present. It is our belief that predicate calculus and the first order logic possess much more expressive power.

  7. Smart Spectrometer for Distributed Fuzzy Control

    CERN Document Server

    Benoit, Eric

    2009-01-01

    If the main use of colour measurement is the metrology, it is now possible to find industrial control applications which uses this information. Using colour in process control leads to specific problems where human perception has to be replaced by colour sensors. This paper relies on the fuzzy representation of colours that can be taken into account by fuzzy controllers. If smart sensors already include intelligent functionalities like signal processing, or configuration, only few of them include functionalities to elaborate the fuzzy representation of measurements. In this paper, we develop a solution where the numeric processing is performed locally by the sensor, and where fuzzy processing is exported towards another computing resource by means of the CAN network. This paper presents the concept and the application to a smart fuzzy spectrometer.

  8. Flows in networks under fuzzy conditions

    CERN Document Server

    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-...

  9. FUZZY ECCENTRICITY AND GROSS ERROR IDENTIFICATION

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    The dominant and recessive effect made by exceptional interferer is analyzed in measurement system based on responsive character, and the gross error model of fuzzy clustering based on fuzzy relation and fuzzy equipollence relation is built. The concept and calculate formula of fuzzy eccentricity are defined to deduce the evaluation rule and function of gross error, on the base of them, a fuzzy clustering method of separating and discriminating the gross error is found. Utilized in the dynamic circular division measurement system, the method can identify and eliminate gross error in measured data, and reduce measured data dispersity. Experimental results indicate that the use of the method and model enables repetitive precision of the system to improve 80% higher than the foregoing system, to reach 3.5 s, and angle measurement error is less than 7 s.

  10. Statistical mechanics of fuzzy random polymer networks

    Institute of Scientific and Technical Information of China (English)

    陈晓红

    1995-01-01

    A statistical mechanics framework of fuzzy random polymer networks is established based on the theories of fuzzy systems. The entanglement effect is manifested quantitatively by introducing an entanglement tensor and membership function and the amorphous structure is treated as the fuzzy random network made up of macromolecular coils entangled randomly. A random tetrahedral entangled-crosslinked cell is chosen as an average representative unit of the fuzzy random polymer network structure. By making use of the theory of fuzzy probability and statistical mechanics, the expression for the free energy of deformation is given, which fits well with the experimental data on rubber elasticity under various deformation modes. Both classical statistical theory and Mooney-Rivlin equation can be taken as its special cases.

  11. 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.

  12. Markowitz portfolio optimization model employing fuzzy measure

    Science.gov (United States)

    Ramli, Suhailywati; Jaaman, Saiful Hafizah

    2017-04-01

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

  13. Molecular processors: from qubits to fuzzy logic.

    Science.gov (United States)

    Gentili, Pier Luigi

    2011-03-14

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

  14. N-topo nilpotency in fuzzy neighborhood rings

    Directory of Open Access Journals (Sweden)

    Fawzi Al-Thukair

    2004-03-01

    Full Text Available We introduce the notion of N-topo nilpotent fuzzy set in a fuzzy neighborhood ring and develop some fundamental results. Here we show that a fuzzy neighborhood ring is locally inversely bounded if and only if for all 0<α<1, the α-level topological rings are locally inversely bounded. This leads us to prove a characterization theorem which says that if a fuzzy neighborhood ring on a division ring is Wuyts-Lowen WNT2 and locally inversely bounded, then the fuzzy neighborhood ring is a fuzzy neighborhood division ring. We also present another characterization theorem which says that a fuzzy neighborhood ring on a division ring is a fuzzy neighborhood division ring if the fuzzy neighborhood ring contains an N-topo nilpotent fuzzy neighborhood of zero.

  15. Fuzzy statistical decision-making theory and applications

    CERN Document Server

    Kabak, Özgür

    2016-01-01

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

  16. 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.)

  17. A Generalized Mazur-Ulam Theorem for Fuzzy Normed Spaces

    Directory of Open Access Journals (Sweden)

    J. J. Font

    2014-01-01

    Full Text Available We introduce fuzzy norm-preserving maps, which generalize the concept of fuzzy isometry. Based on the ideas from Vogt, 1973, and Väisälä, 2003, we provide the following generalized version of the Mazur-Ulam theorem in the fuzzy context: let X, Y be fuzzy normed spaces and let f:X→Y be a fuzzy norm-preserving surjection satisfying f(0=0. Then f is additive.

  18. A novel fuzzy neural network and its approximation capability

    Institute of Scientific and Technical Information of China (English)

    刘普寅

    2001-01-01

    The polygonal fuzzy numbers are employed to define a new fuzzy arithmetic. A novel extension principle is also introduced for the increasing function σ: R→R. Thus it is convenient to construct a fuzzy neural network model with succinct learning algorithms. Such a system possesses some universal approximation capabilities, that is, the corresponding three layer feedforward fuzzy neural networks can be universal approximators to the continuously increasing fuzzy functions.

  19. A New Method for Solving General Dual Fuzzy Linear Systems

    Directory of Open Access Journals (Sweden)

    M. Otadi

    2013-09-01

    Full Text Available . According to fuzzy arithmetic, general dual fuzzy linear system (GDFLS cannot be replaced by a fuzzy linear system (FLS. In this paper, we use new notation of fuzzy numbers and convert a GDFLS to two linear systems in crisp case, then we discuss complexity of the proposed method. Conditions for the existence of a unique fuzzy solution to n × n GDFLS are derived

  20. Vývojové prostředí pro umělou inteligenci Modul fuzzy čísel

    OpenAIRE

    Pergl, Miroslav

    2009-01-01

    Diplomová práce pojednává o matematických operacích s fuzzy čísly. V první části práce jsou zavedeny pojmy z oblasti fuzzy logiky, jako jsou definice fuzzy množiny, fuzzy čísla, universa a pěti funkcí příslušnosti používaných v programu. Je rozebrána metoda α – řezu pro práci s fuzzy čísly v podobě uzavřených intervalů na jednotlivých hladinách. Druhá část práce popisuje program vytvořený v rámci této diplomové práce, sloužící pro provádění matematických operací s fuzzy čísly. Jsou zde p...

  1. Convergence of Fuzzy Set Sequences

    Institute of Scientific and Technical Information of China (English)

    FENG Yu-hu

    2002-01-01

    There are more than one mode of convergence with respect to the fuzzy set sequences. In this paper,common six modes of convergence and their relationships are discussed. These six modes are convergence in uniform metric D, convergence in separable metric Dp or D*p, 1 ≤ p <∞, convergence in level set, strong convergence in level set and weak convergence. Suitable counterexamples are given. The necessary and sufficient conditions of convergence in uniform metric D are described. Some comme nts on the convergence of LRfuzzy number sequences are represented.

  2. 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.

  3. Application of Fuzzy Algebra in Coding Theory

    Directory of Open Access Journals (Sweden)

    Kharatti Lal

    2016-01-01

    Full Text Available Fuzziness means different things depending upon the domain of application and the way it is measured. By means of fuzzy sets, vague notions can be described mathematically now a vigorous area of research with manifold applications. It should be mentioned that there are natural ways (not necessarily trivial to fuzzily various mathematical structures such as topological spaces, algebraic structure etc. The notion of L-fuzzy sets later more generalizations were also made using various membership sets and operations. In this section we let F denote the field of integers module 2, we define a fuzzy code as a fuzzy subset of Fn where F n = {(a1, ....an | a i  F, i = 1, ...n} and n is a fixed arbitrary positive integers we recall that Fn is a vector space over F. We give an analysis of the Hamming distance between two fuzzy code words and the error – correcting capability of a code in terms of its corresponding fuzzy codes. The results appearing in the first part of this section are from [17].

  4. Design of supply chain in fuzzy environment

    Science.gov (United States)

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

    2013-05-01

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

  5. Fuzzy Object Skeletonization: Theory, Algorithms, and Applications.

    Science.gov (United States)

    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.

  6. Towards the future of fuzzy logic

    CERN Document Server

    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 ...

  7. Decentralized adaptive fuzzy control of robot manipulators.

    Science.gov (United States)

    Jin, Y

    1998-01-01

    This paper develops a decentralized adaptive fuzzy control scheme for robot manipulators via a combination of genetic algorithm and gradient method. The controller for each link consists of a feedforward fuzzy torque-computing system and a feedback fuzzy PD system. The feedforward fuzzy system is trained and optimized off-line by an improved genetic algorithm, that is to say, not only the parameters but also the structure of the fuzzy system are self-organized. Because genetic algorithm can operate successfully without the system model, no exact inverse dynamics of the robot system are required. The feedback fuzzy PD system, on the other hand, is tuned on-line using gradient method. In this way, the proportional and derivative gains are adjusted properly to keep the closed-loop system stable. The proposed controller has the following merits: (1) it needs no exact dynamics of the robot systems and the computation is time-saving because of the simple structure of the fuzzy systems; and (2) the controller is insensitive to various dynamics and payload uncertainties in robot systems. These are demonstrated by analyses of the computational complexity and various computer simulations.

  8. Security analysis for fingerprint fuzzy vaults

    Science.gov (United States)

    Hartloff, Jesse; Bileschi, Maxwell; Tulyakov, Sergey; Dobler, Jimmy; Rudra, Atri; Govindaraju, Venu

    2013-05-01

    In this work we place some of the traditional biometrics work on fingerprint verification via the fuzzy vault scheme within a cryptographic framework. We show that the breaking of a fuzzy vault leads to decoding of Reed-Solomon codes from random errors, which has been proposed as a hard problem in the cryptography community. We provide a security parameter for the fuzzy vault in terms of the decoding problem, which gives context for the breaking of the fuzzy vault, whereas most of the existing literature measures the strength of the fuzzy vault in terms of its resistance to pre-defined attacks or by the entropy of the vault. We keep track of our security parameter, and provide it alongside ROC statistics. We also aim to be more aware of the nature of the fingerprints when placing them in the fuzzy vault, noting that the distribution of minutiae is far from uniformly random. The results we show provide additional support that the fuzzy vault can be a viable scheme for secure fingerprint verification.

  9. Fuzzy Constraint-Based Agent Negotiation

    Institute of Scientific and Technical Information of China (English)

    Menq-Wen Lin; K. Robert Lai; Ting-Jung Yu

    2005-01-01

    Conflicts between two or more parties arise for various reasons and perspectives. Thus, resolution of conflicts frequently relies on some form of negotiation. This paper presents a general problem-solving framework for modeling multi-issue multilateral negotiation using fuzzy constraints. Agent negotiation is formulated as a distributed fuzzy constraint satisfaction problem (DFCSP). Fuzzy constrains are thus used to naturally represent each agent's desires involving imprecision and human conceptualization, particularly when lexical imprecision and subjective matters are concerned. On the other hand, based on fuzzy constraint-based problem-solving, our approach enables an agent not only to systematically relax fuzzy constraints to generate a proposal, but also to employ fuzzy similarity to select the alternative that is subject to its acceptability by the opponents. This task of problem-solving is to reach an agreement that benefits all agents with a high satisfaction degree of fuzzy constraints, and move towards the deal more quickly since their search focuses only on the feasible solution space. An application to multilateral negotiation of a travel planning is provided to demonstrate the usefulness and effectiveness of our framework.

  10. INTELLIGENT USER INTERFACE IN FUZZY ENVIRONMENT

    Directory of Open Access Journals (Sweden)

    Ben Khayut

    2014-01-01

    Full Text Available Human-Computer Interaction with the traditional User Interface is done using a specified in advance script dialog “menu”, mainly based on human intellect and unproductive use of navigation. This approach doesn’t lead to making qualitative decision in control systems, where the situations and processes cannot be structured in advance. Any dynamic changes in the controlled business process (as example, in organizational unit of the information fuzzy control system make it necessary to modify the script dialogue in User Interface. This circumstance leads to a redesign of the components of the User Interface and of the entire control system. In the Intelligent User Interface, where the dialog situations are unknown in advance, fuzzy structured and artificial intelligence is crucial, the redesign described above is impossible. To solve this and other problems, we propose the data, information and knowledge based technology of Smart/ Intelligent User Interface (IUI design, which interacts with users and systems in natural and other languages, utilizing the principles of Situational Control and Fuzzy Logic theories, Artificial Intelligence, Linguistics, Knowledge Base technologies and others. The proposed technology of IUI design is defined by multi-agents of a Situational Control and of data, information and knowledge, b modelling of Fuzzy Logic Inference, c Generalization, Representation and Explanation of knowledge, c Planning and Decisionmaking, d Dialog Control, e Reasoning and Systems Thinking, f Fuzzy Control of organizational unit in real-time, fuzzy conditions, heterogeneous domains, and g multi-lingual communication under uncertainty and in Fuzzy Environment.

  11. Application of fuzzy Laplace transforms for solving fuzzy partial Volterra integro-differential equations

    OpenAIRE

    Ullah, Saif; Farooq, Muhammad; Ahmad, Latif; Abdullah, Saleem

    2014-01-01

    Fuzzy partial integro-differential equations have a major role in the fields of science and engineering. In this paper, we propose the solution of fuzzy partial Volterra integro-differential equation with convolution type kernel using fuzzy Laplace transform method (FLTM) under Hukuhara differentiability. It is shown that FLTM is a simple and reliable approach for solving such equations analytically. Finally, the method is illustrated with few examples to show the ability of the proposed method.

  12. A new fuzzy Monte Carlo method for solving SLAE with ergodic fuzzy Markov chains

    Directory of Open Access Journals (Sweden)

    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.

  13. Enric Trillas a passion for fuzzy sets : a collection of recent works on fuzzy logic

    CERN Document Server

    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.

  14. Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA

    Science.gov (United States)

    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

  15. 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...

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

    Science.gov (United States)

    Shah, Mazlina Muzafar; Wahab, Abdul Fatah

    2017-08-01

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

  17. PENGENALAN KEPRIBADIAN SESEORANG BERDASARKAN SIDIK JARI DENGAN METODE FUZZY LEARNING VECTOR QUANTIZATION DAN FUZZY BACKPROPAGATION

    Directory of Open Access Journals (Sweden)

    I Gede Sujana Eka Putra

    2014-12-01

    Full Text Available Kepribadian dapat diidentifikasi melalui analisis pola sidik jari. Pengenalan kepribadian umumnyamenggunakan uji psikometri melalui serangkaian tahapan yang relatif panjang. Melalui analisis pola sidik jari, dapatdiidentifikasi kepribadian secara lebih efisien. Penelitian ini mengajukan algoritma klasifikasi Fuzzy LearningVector Quantization (Fuzzy LVQ karena waktu komputasi yang lebih cepat dan tingkat pengenalan yang tinggi, dandengan metode Fuzzy Backpropagation yang mampu menyelesaikan model data non linier. Tahapan penelitianterdiri dari akuisisi dan klasifikasi. Tahapan pertama melalui akuisisi sidik jari, ekstraksi fitur, proses pelatihan, danpre-klasifikasi. Selanjutnya tahap klasifikasi, melalui klasifikasi fitur sidik jari uji menggunakan algoritma FuzzyLVQ, dibandingkan dengan Fuzzy Backpropagation. Kepribadian diidentifikasi melalui pola hasil klasifikasimenggunakan basis pengetahuan dermatoglyphics. Unjuk kerja diukur dari pencocokan pola hasil pre-klasifikasidan hasil klasifikasi. Hasil penelitian menunjukkan klasifikasi Fuzzy LVQ tingkat kecocokan tertinggi 93,78%dengan iterasi pelatihan maksimum=100 epoh pada target error 10-6. Sedangkan Fuzzy Backpropagation dengantingkat kecocokan tertinggi 93,30% dengan iterasi maksimum diatas 1000 epoh pada target error 10-3. Hal inimenunjukkan Fuzzy LVQ memiliki unjuk kerja lebih baik dibandingkan Fuzzy Backpropagation. Survey respondendilakukan untuk menguji kesesuaian analisa kepribadian sistem dibandingkan dengan kepribadian responden, danhasil survey menunjukkan analisa kepribadian sistem sebagian besar cocok dengan kepribadian responden.

  18. Fuzzy Optimization and Normal Simulation for Solving Fuzzy Web Queuing System Problems

    Directory of Open Access Journals (Sweden)

    Xidong Zheng

    2005-04-01

    Full Text Available In this paper, we use both fuzzy optimization and normal simulation methods to solve fuzzy web planning model problems, which are queuing system problems for designing web servers. We apply fuzzy probabilities to the queuing system models with customers arrival rate l and servers?service rate m, and then compute fuzzy system performance variables, including Utilization, Number (of requests in the System, Throughput, and Response Time. For the fuzzy optimization method, we apply two-step calculation, first use fuzzy calculation to get the maximum and minimum values of fuzzy steady state probabilities, and then we compute the fuzzy system performance variables. For the simulation method, we use one-step normal queuing theory to simulate the whole system performance and its variables. We deal with queuing systems with a single server and multiple servers?cases, and compare the results of these two cases, giving a mathematical explanation of the difference. Keywords: Fuzzy Optimization, Normal Simulation, Queuing Theory, Web Planning Model.

  19. Fuzzy image processing and applications with Matlab

    CERN Document Server

    Chaira, Tamalika

    2009-01-01

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

  20. Relative aggregation operator in database fuzzy querying

    Directory of Open Access Journals (Sweden)

    Luminita DUMITRIU

    2005-12-01

    Full Text Available Fuzzy selection criteria querying relational databases include vague terms; they usually refer linguistic values form the attribute linguistic domains, defined as fuzzy sets. Generally, when a vague query is processed, the definitions of vague terms must already exist in a knowledge base. But there are also cases when vague terms must be dynamically defined, when a particular operation is used to aggregate simple criteria in a complex selection. The paper presents a new aggregation operator and the corresponding algorithm to evaluate the fuzzy query.

  1. Image Edge Extraction via Fuzzy Reasoning

    Science.gov (United States)

    Dominquez, Jesus A. (Inventor); Klinko, Steve (Inventor)

    2008-01-01

    A computer-based technique for detecting edges in gray level digital images employs fuzzy reasoning to analyze whether each pixel in an image is likely on an edge. The image is analyzed on a pixel-by-pixel basis by analyzing gradient levels of pixels in a square window surrounding the pixel being analyzed. An edge path passing through the pixel having the greatest intensity gradient is used as input to a fuzzy membership function, which employs fuzzy singletons and inference rules to assigns a new gray level value to the pixel that is related to the pixel's edginess degree.

  2. A Simple Fuzzy Time Series Forecasting Model

    DEFF Research Database (Denmark)

    Ortiz-Arroyo, Daniel

    2016-01-01

    In this paper we describe a new first order fuzzy time series forecasting model. We show that our automatic fuzzy partitioning method provides an accurate approximation to the time series that when combined with rule forecasting and an OWA operator improves forecasting accuracy. Our model does...... not attempt to provide the best results in comparison with other forecasting methods but to show how to improve first order models using simple techniques. However, we show that our first order model is still capable of outperforming some more complex higher order fuzzy time series models....

  3. Adaptive Fuzzy Systems in Computational Intelligence

    Science.gov (United States)

    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.

  4. Fuzzy stability and synchronization of hyperchaos systems

    Energy Technology Data Exchange (ETDEWEB)

    Wang Junwei [School of Mathematics and Computational Science, Zhongshan University Guangzhou 510275 (China)], E-mail: wangjunweilj@yahoo.com.cn; Xiong Xiaohua [School of Mathematics and Computational Science, Zhongshan University Guangzhou 510275 (China); Department of Computer Science, Jiangxi Normal University, Nanchang 330027 (China); Zhao Meichun [School of Mathematics and Computational Science, Zhongshan University Guangzhou 510275 (China); Department of Mathematics, Guangdong University of Finance, Gunangzhou 510521 (China); Zhang Yanbin [School of Mathematics and Computational Science, Zhongshan University Guangzhou 510275 (China)

    2008-03-15

    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.

  5. Temperature Control System Using Fuzzy Logic Technique

    Directory of Open Access Journals (Sweden)

    Isizoh A N

    2012-06-01

    Full Text Available Fuzzy logic technique is an innovative technology used in designing solutions for multi-parameter and non-linear control models for the definition of a control strategy. As a result, it delivers solutions faster than the conventional control design techniques. This paper thus presents a fuzzy logic based-temperature control system, which consists of a microcontroller, temperature sensor, and operational amplifier, Analogue to Digital Converter, display interface circuit and output interface circuit. It contains a design approach that uses fuzzy logic technique to achieve a controlled temperature output function.

  6. Scheduling By Using Fuzzy Logic in Manufacturing

    Directory of Open Access Journals (Sweden)

    Miss. Ashwini. A. Mate

    2014-07-01

    Full Text Available This paper represents the scheduling process in furniture manufacturing unit. It gives the fuzzy logic application in flexible manufacturing system. Flexible manufacturing systems are production system in furniture manufacturing unit. FMS consist of same multipurpose numerically controlled machines. Here in this project the scheduling has been done in FMS by using fuzzy logic tool in Matlab software. The fuzzy logic based scheduling model in this paper will deals with the job and best alternative route selection with multi-criteria of machine. Here two criteria for job and sequencing and routing with rules. This model is applicable to the scheduling of any manufacturing industry.

  7. Fuzzy Hybrid Deliberative/Reactive Paradigm (FHDRP)

    Science.gov (United States)

    Sarmadi, Hengameth

    2004-01-01

    This work aims to introduce a new concept for incorporating fuzzy sets in hybrid deliberative/reactive paradigm. After a brief review on basic issues of hybrid paradigm the definition of agent-based fuzzy hybrid paradigm, which enables the agents to proceed and extract their behavior through quantitative numerical and qualitative knowledge and to impose their decision making procedure via fuzzy rule bank, is discussed. Next an example performs a more applied platform for the developed approach and finally an overview of the corresponding agents architecture enhances agents logical framework.

  8. Conditions of existence of fuzzy explanations and approximate solutions in fuzzy abduction; Fuzzy abduction ni okeru setsumei no sonzai joken to kinji kaiho

    Energy Technology Data Exchange (ETDEWEB)

    Yamada, K. [Nagaoka Technical Coll., Niigata (Japan)] Mukaidono, M. [Meiji Univ., Tokyo (Japan)

    1998-09-30

    Abduction is a procedure to derive a set of hypotheses which explains a set of observed events under given knowledge. The obtained set of hypotheses is called explanation. Previously, the authors proposed fuzzy abduction that was an extension of the abduction with the fuzzy theory and showed the way to derive fuzzy explanation. In this theory, observed events and hypotheses are expressed and the given knowledge is expressed by a set of implications with a truth value between zero and one. However, there is no guarantee that fuzzy explanations always exist. This paper clarifies the necessary and sufficient conditions of the existence of fuzzy explanations and proposes a method to obtain approximate solutions when fuzzy explanations do not exist. Fuzzy abduction is a procedure similar to the inverse operation of fuzzy relational equations, however, the proposed method does not require iterative calculation whose number of times cannot be obtain beforehand. 10 refs., 1 fig.

  9. Simulation of Fuzzy Inductance Motor using PI Control Application

    Directory of Open Access Journals (Sweden)

    S.V.Halse

    2013-06-01

    Full Text Available Fuzzy control has been widely used in industrial controls, particularly in situations where conventional control design techniques have been difficult to apply. Number of fuzzy rules is very important for real time fuzzy control applications. This study is motivated by the increasing need in the industry to design highly reliable, efficiency and low complexity controllers. The proposed fuzzy controller is constructed by several fuzzy controllers with less fuzzy rules to carry out control tasks. Performances of the proposed fuzzy controller are investigated and compared to those obtained from the conventional fuzzy controller. Fuzzy logic control method has the ability to handle errors in control operation with system nonlinearity and its performance is less affected by system parameter variations.

  10. Models of neural networks with fuzzy activation functions

    Science.gov (United States)

    Nguyen, A. T.; Korikov, A. M.

    2017-02-01

    This paper investigates the application of a new form of neuron activation functions that are based on the fuzzy membership functions derived from the theory of fuzzy systems. On the basis of the results regarding neuron models with fuzzy activation functions, we created the models of fuzzy-neural networks. These fuzzy-neural network models differ from conventional networks that employ the fuzzy inference systems using the methods of neural networks. While conventional fuzzy-neural networks belong to the first type, fuzzy-neural networks proposed here are defined as the second-type models. The simulation results show that the proposed second-type model can successfully solve the problem of the property prediction for time – dependent signals. Neural networks with fuzzy impulse activation functions can be widely applied in many fields of science, technology and mechanical engineering to solve the problems of classification, prediction, approximation, etc.

  11. Fuzzy α-minimum spanning tree problem: definition and solutions

    Science.gov (United States)

    Zhou, Jian; Chen, Lu; Wang, Ke; Yang, Fan

    2016-04-01

    In this paper, the minimum spanning tree problem is investigated on the graph with fuzzy edge weights. The notion of fuzzy ? -minimum spanning tree is presented based on the credibility measure, and then the solutions of the fuzzy ? -minimum spanning tree problem are discussed under different assumptions. First, we respectively, assume that all the edge weights are triangular fuzzy numbers and trapezoidal fuzzy numbers and prove that the fuzzy ? -minimum spanning tree problem can be transformed to a classical problem on a crisp graph in these two cases, which can be solved by classical algorithms such as the Kruskal algorithm and the Prim algorithm in polynomial time. Subsequently, as for the case that the edge weights are general fuzzy numbers, a fuzzy simulation-based genetic algorithm using Prüfer number representation is designed for solving the fuzzy ? -minimum spanning tree problem. Some numerical examples are also provided for illustrating the effectiveness of the proposed solutions.

  12. Objective probability and quantum fuzziness

    CERN Document Server

    Mohrhoff, U

    2007-01-01

    This paper offers a critique of the Bayesian approach to quantum mechanics in general and of a recent paper by Caves, Fuchs, and Schack in particular (quant-ph/0608190 v2). In this paper the Bayesian interpretation of Born probabilities is defended against what the authors call the "objective-preparations view". The fact that Caves et al. and the proponents of this view equally misconstrue the time dependence of quantum states, voids the arguments pressed by the former against the latter. After tracing the genealogy of this common error, I argue that the real oxymoron is not an unknown quantum state, as the Bayesians hold, but an unprepared quantum state. I further argue that the essential role of probability in quantum theory is to define and quantify an objective fuzziness. This, more than anything, legitimizes conjoining "objective" to "probability". The measurement problem is essentially the problem of finding a coherent way of thinking about this objective fuzziness, and about the supervenience of the ma...

  13. Fuzzy logic for personalized healthcare and diagnostics: FuzzyApp--a fuzzy logic based allergen-protein predictor.

    Science.gov (United States)

    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.

  14. Fuzzy C e-I(ec, eo) and Fuzzy Completely C e-I(rc, eo) Functions via Fuzzy e-Open Sets

    Science.gov (United States)

    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

  15. Discussion on Type-I fuzzy boundary and Research on Boundary Definition of High Order Fuzzy Region

    Directory of Open Access Journals (Sweden)

    Cui Tiejun

    2012-10-01

    Full Text Available The definition of fuzzy boundary is crucial in research of modeling and analysis of fuzzy geographical phenomena. The problem “boundary syndrome” has been a longstanding problem in this domain, and this problem has seriously affected the research and application of fuzzy geographical model. The existing fuzzy boundary models were discussed at first, and then some models based on type-I fuzzy sets were analyzed in detail. This paper pointed out the fuzzy boundary models should have three kinds of meaning: “frontier”, “transition” and “division”. Three types of boundary models of high order fuzzy region were proposed based on interval type-2 fuzzy set, and they embody three kinds of meaning of fuzzy boundary respectively. The models proposed by this paper have a positive effect to high order geographical phenomena modeling and analysis.

  16. DYNAMIC CHARACTERISTIC ANALYSIS OF FUZZY- STOCHASTIC TRUSS STRUCTURES BASED ON FUZZY FACTOR METHOD AND RANDOM FACTOR METHOD

    Institute of Scientific and Technical Information of China (English)

    MA Juan; CHEN Jian-jun; XU Ya-lan; JIANG Tao

    2006-01-01

    A new fuzzy stochastic finite element method based on the fuzzy factor method and random factor method is given and the analysis of structural dynamic characteristic for fuzzy stochastic truss structures is presented. Considering the fuzzy randomness of the structural physical parameters and geometric dimensions simultaneously, the structural stiffness and mass matrices are constructed based on the fuzzy factor method and random factor method; from the Rayleigh's quotient of structural vibration, the structural fuzzy random dynamic characteristic is obtained by means of the interval arithmetic;the fuzzy numeric characteristics of dynamic characteristic are then derived by using the random variable's moment function method and algebra synthesis method. Two examples are used to illustrate the validity and rationality of the method given. The advantage of this method is that the effect of the fuzzy randomness of one of the structural parameters on the fuzzy randomness of the dynamic characteristic can be reflected expediently and objectively.

  17. Bi-Objective Bilevel Programming Problem: A Fuzzy Approach

    Directory of Open Access Journals (Sweden)

    Haseen S.

    2015-12-01

    Full Text Available In this paper, a likely situation of a set of decision maker’s with bi-objectives in case of fuzzy multi-choice goal programming is considered. The problem is then carefully formulated as a bi-objective bilevel programming problem (BOBPP with multiple fuzzy aspiration goals, fuzzy cost coefficients and fuzzy decision variables. Using Ranking method the fuzzy bi-objective bilevel programming problem (FBOBPP is converted into a crisp model. The transformed problem is further solved by adopting a two level Stackelberg game theory and fuzzy decision model of Sakawa. A numerical with hypothetical values is also used to illustrate the problem.

  18. Research on Fuzzy Control for Automatic Transmission of Tracked Vehicles

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    A principle of fuzzy control for tracked vehicles is proposed to make its automatic transmission system be able to adapt complex running conditions, and a model of its power train is established to be used in simulation. Based on the fuzzy control method, a fuzzy shift control system composed of a basic shift strategy and a fuzzy modification module is developed to improve the dynamic characteristics and cross-country maneuverability. Simulation results show that the fuzzy shift strategy can improve the shift quality under manifold driving conditions and avoid cycled shift effectively. Therefore,the proposed fuzzy shift strategies are proved to be feasible and practicable.

  19. Mathematical Foundation of Basic Algorithms of Fuzzy Reasoning

    Institute of Scientific and Technical Information of China (English)

    潘正华

    2005-01-01

    Algorithm of fuzzy reasoning has been successful applied in fuzzy control, but its theoretical foundation of algorithms has not been thoroughly investigated. In this paper, structure of basic algorithms of fuzzy reasoning was studied, its rationality was discussed from the viewpoint of logic and mathematics, and three theorems were proved. These theorems shows that there always exists a mathematical relation (that is, a bounded real function) between the premises and the conclusion for fuzzy reasoning, and in fact various algorithms of fuzzy reasoning are specific forms of this function. Thus these results show that algorithms of fuzzy reasoning are theoretically reliable.

  20. FPGA Fuzzy Controller Design for Magnetic Ball Levitation

    Directory of Open Access Journals (Sweden)

    Basil Hamed

    2012-09-01

    Full Text Available this paper presents a fuzzy controller design for nonlinear system using FPGA. A magnetic levitation system is considered as a case study and the fuzzy controller is designed to keep a magnetic object suspended in the air counteracting the weight of the object. Fuzzy controller will be implemented using FPGA chip. The design will use a high-level programming language HDL for implementing the fuzzy logic controller using the Xfuzzy tools to implement the fuzzy logic controller into HDL code. This paper, advocates a novel approach to implement the fuzzy logic controller for magnetic ball levitation system by using FPGA.