{"product_id":"fuzzy-systems-engineering-toward-human-centric-computing-hardback-9780471788577","title":"Fuzzy Systems Engineering; Toward Human-Centric Computing (Hardback) 9780471788577","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eFuzzy Systems Engineering\u003c\/font\u003e\u003cbr\u003e\r\n\u003cfont size=\"5\"\u003eToward Human-Centric Computing\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eWitold Pedrycz (Author), Fernando Gomide (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9780471788577, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 31 August 2007\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e560 pages\u003cbr\u003e24.4 x 16.4 x 3.3 cm, 0.916 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003eA self-contained treatment of fuzzy systems engineering, offering conceptual fundamentals, design methodologies, development guidelines, and carefully selected illustrative material\u003cbr\u003e \u003cbr\u003e Forty years have passed since the birth of fuzzy sets, in which time a wealth of theoretical developments, conceptual pursuits, algorithmic environments, and other applications have emerged. Now, this reader-friendly book presents an up-to-date approach to fuzzy systems engineering, covering concepts, design methodologies, and algorithms coupled with interpretation, analysis, and underlying engineering knowledge. The result is a holistic view of fuzzy sets as a fundamental component of computational intelligence and human-centric systems.\u003cbr\u003e \u003cbr\u003e Throughout the book, the authors emphasize the direct applicability and limitations of the concepts being discussed, and historical and bibliographical notes are included in each chapter to help readers view the developments of fuzzy sets from a broader perspective. A radical departure from current books on the subject, Fuzzy Systems Engineering presents fuzzy sets as an enabling technology whose impact, contributions, and methodology stretch far beyond any specific discipline, making it applicable to researchers and practitioners in engineering, computer science, business, medicine, bioinformatics, and computational biology. Additionally, three appendices and classroom-ready electronic resources make it an ideal textbook for advanced undergraduate- and graduate-level courses in engineering and science.\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003ePreface.  \u003cp\u003e\u003cb\u003e1 Introduction.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Digital communities and a fundamental quest for human-centric systems.\u003c\/p\u003e \u003cp\u003e1.2 A historical overview: towards a non-Aristotelian perspective of the world.\u003c\/p\u003e \u003cp\u003e1.3 Granular Computing.\u003c\/p\u003e \u003cp\u003e1.4 Quantifying information granularity: generality versus specificity.\u003c\/p\u003e \u003cp\u003e1.5 Computational Intelligence.\u003c\/p\u003e \u003cp\u003e1.6 Granular Computing and Computational Intelligence.\u003c\/p\u003e \u003cp\u003e1.7 Conclusions.\u003c\/p\u003e \u003cp\u003eExercises and problems.\u003c\/p\u003e \u003cp\u003eHistorical notes.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Notions and Concepts of Fuzzy Sets.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Sets and fuzzy sets: a departure from the principle of dichotomy.\u003c\/p\u003e \u003cp\u003e2.2 Interpretation of fuzzy sets.\u003c\/p\u003e \u003cp\u003e2.3 Membership functions and their motivation.\u003c\/p\u003e \u003cp\u003e2.4 Fuzzy numbers and intervals.\u003c\/p\u003e \u003cp\u003e2.5 Linguistic variables.\u003c\/p\u003e \u003cp\u003e2.6 Conclusions.\u003c\/p\u003e \u003cp\u003eExercises and problems.\u003c\/p\u003e \u003cp\u003eHistorical notes.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Characterization of Fuzzy Sets.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 A generic characterization of fuzzy sets: some fundamental descriptors.\u003c\/p\u003e \u003cp\u003e3.2 Equality and inclusion relationships in fuzzy sets.\u003c\/p\u003e \u003cp\u003e3.3 Energy and entropy measures of fuzziness.\u003c\/p\u003e \u003cp\u003e3.4 Specificity of fuzzy sets.\u003c\/p\u003e \u003cp\u003e3.5 Geometric interpretation of sets and fuzzy sets.\u003c\/p\u003e \u003cp\u003e3.6 Granulation of information.\u003c\/p\u003e \u003cp\u003e3.7 Characterization of the families of fuzzy sets.\u003c\/p\u003e \u003cp\u003e3.8 Fuzzy sets, sets, and the representation theorem.\u003c\/p\u003e \u003cp\u003e3.9 Conclusions.\u003c\/p\u003e \u003cp\u003eExercises and problems.\u003c\/p\u003e \u003cp\u003eHistorical notes.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 The Design of Fuzzy Sets.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Semantics of fuzzy sets: some general observations.\u003c\/p\u003e \u003cp\u003e4.2 Fuzzy set as a descriptor of feasible solutions.\u003c\/p\u003e \u003cp\u003e4.3 Fuzzy set as a descriptor of the notion of typicality.\u003c\/p\u003e \u003cp\u003e4.4 Membership functions in the visualization of preferences of solutions.\u003c\/p\u003e \u003cp\u003e4.5 Nonlinear transformation of fuzzy sets.\u003c\/p\u003e \u003cp\u003e4.6 Vertical and horizontal schemes of membership estimation.\u003c\/p\u003e \u003cp\u003e4.7 Saaty's priority method of pairwise membership function estimation.\u003c\/p\u003e \u003cp\u003e4.8 Fuzzy sets as granular representatives of numeric data.\u003c\/p\u003e \u003cp\u003e4.9 From numeric data to fuzzy sets.\u003c\/p\u003e \u003cp\u003e4.10 Fuzzy equalization.\u003c\/p\u003e \u003cp\u003e4.11 Linguistic approximation.\u003c\/p\u003e \u003cp\u003e4.12 Design guidelines for the construction of fuzzy sets.\u003c\/p\u003e \u003cp\u003e4.13 Conclusions.\u003c\/p\u003e \u003cp\u003eExercises and problems.\u003c\/p\u003e \u003cp\u003eHistorical notes.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Operations and Aggregations of Fuzzy Sets.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Standard operations on sets and fuzzy sets.\u003c\/p\u003e \u003cp\u003e5.2 Generic requirements for operations on fuzzy sets.\u003c\/p\u003e \u003cp\u003e5.3 Triangular norms.\u003c\/p\u003e \u003cp\u003e5.4 Triangular conorms.\u003c\/p\u003e \u003cp\u003e5.5 Triangular norms as a general category of logical operators.\u003c\/p\u003e \u003cp\u003e5.6 Aggregation operations.\u003c\/p\u003e \u003cp\u003e5.7 Fuzzy measure and integral.\u003c\/p\u003e \u003cp\u003e5.8 Negations.\u003c\/p\u003e \u003cp\u003e5.9 Conclusions.\u003c\/p\u003e \u003cp\u003eExercises and problems.\u003c\/p\u003e \u003cp\u003eHistorical notes.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Fuzzy Relations.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 The concept of relations.\u003c\/p\u003e \u003cp\u003e6.2 Fuzzy relations.\u003c\/p\u003e \u003cp\u003e6.3 Properties of the fuzzy relations.\u003c\/p\u003e \u003cp\u003e6.4 Operations on fuzzy relations.\u003c\/p\u003e \u003cp\u003e6.5 Cartesian product, projections and cylindrical extension of fuzzy sets.\u003c\/p\u003e \u003cp\u003e6.6 Reconstruction of fuzzy relations.\u003c\/p\u003e \u003cp\u003e6.7 Binary fuzzy relations.\u003c\/p\u003e \u003cp\u003e6.8 Conclusions.\u003c\/p\u003e \u003cp\u003eExercises and problems.\u003c\/p\u003e \u003cp\u003eHistorical notes.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Transformations of Fuzzy Sets.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 The extension principle.\u003c\/p\u003e \u003cp\u003e7.2 Compositions of fuzzy relations.\u003c\/p\u003e \u003cp\u003e7.3 Fuzzy relational equations.\u003c\/p\u003e \u003cp\u003e7.4 Associative Memories.\u003c\/p\u003e \u003cp\u003e7.5 Fuzzy numbers and fuzzy arithmetic.\u003c\/p\u003e \u003cp\u003e7.6 Conclusions.\u003c\/p\u003e \u003cp\u003eExercises and problems.\u003c\/p\u003e \u003cp\u003eHistorical notes.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Generalizations and Extensions of Fuzzy Sets.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Fuzzy sets of higher order.\u003c\/p\u003e \u003cp\u003e8.2 Rough fuzzy sets and fuzzy rough sets.\u003c\/p\u003e \u003cp\u003e8.3 Interval-valued fuzzy sets.\u003c\/p\u003e \u003cp\u003e8.4 Type-2 fuzzy sets.\u003c\/p\u003e \u003cp\u003e8.5 Shadowed sets as a three-valued logic characterization of fuzzy sets.\u003c\/p\u003e \u003cp\u003e8.6 Probability and fuzzy sets.\u003c\/p\u003e \u003cp\u003e8.7 Probability of fuzzy events.\u003c\/p\u003e \u003cp\u003e8.8 Conclusions.\u003c\/p\u003e \u003cp\u003eExercises and problems.\u003c\/p\u003e \u003cp\u003eHistorical notes.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Interoperability Aspects of Fuzzy Sets.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Fuzzy set and its family of s-cuts.\u003c\/p\u003e \u003cp\u003e9.2 Fuzzy sets and their interfacing with the external world.\u003c\/p\u003e \u003cp\u003e9.3 Encoding and decoding as an optimization problem of vector quantization.\u003c\/p\u003e \u003cp\u003e9.4 Decoding of a fuzzy set through a family of fuzzy sets.\u003c\/p\u003e \u003cp\u003e9.5 Taxonomy of data in structure description with shadowed sets.\u003c\/p\u003e \u003cp\u003e9.6 Conclusions.\u003c\/p\u003e \u003cp\u003eExercises and problems.\u003c\/p\u003e \u003cp\u003eHistorical notes.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10. Fuzzy Modeling: Principles and Methodology.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 The architectural blueprint of fuzzy models.\u003c\/p\u003e \u003cp\u003e10.2 Key phases of the development and use of fuzzy models.\u003c\/p\u003e \u003cp\u003e10.3 Main categories of fuzzy models: an overview.\u003c\/p\u003e \u003cp\u003e10.4 Verification and validation of fuzzy models.\u003c\/p\u003e \u003cp\u003e10.5 Conclusions.\u003c\/p\u003e \u003cp\u003eExercises and problems.\u003c\/p\u003e \u003cp\u003eHistorical notes.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Rule-based Fuzzy Models.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Fuzzy rules as a vehicle of knowledge representation.\u003c\/p\u003e \u003cp\u003e11.2 General categories of fuzzy rules and their semantics.\u003c\/p\u003e \u003cp\u003e11.3 Syntax of fuzzy rules.\u003c\/p\u003e \u003cp\u003e11.4 Basic Functional Modules: Rule base, Database, and Inference scheme.\u003c\/p\u003e \u003cp\u003e11.5 Types of Rule-Based Systems and Architectures.\u003c\/p\u003e \u003cp\u003e11.6 Approximation properties of fuzzy rule-based models.\u003c\/p\u003e \u003cp\u003e11.7 Development of Rule-Based Systems.\u003c\/p\u003e \u003cp\u003e11.8 Parameter estimation procedure for functional rule-based systems.\u003c\/p\u003e \u003cp\u003e11.9 Design issues of rule-based systems - consistency, completeness, and the curse of dimensionality.\u003c\/p\u003e \u003cp\u003e11.10 The curse of dimensionality in rule-based systems.\u003c\/p\u003e \u003cp\u003e11.11 Development scheme of fuzzy rule-based models.\u003c\/p\u003e \u003cp\u003e11.12 Conclusions.\u003c\/p\u003e \u003cp\u003eExercises and problems.\u003c\/p\u003e \u003cp\u003eHistorical notes.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 From Logic Expressions to Fuzzy Logic Networks.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction.\u003c\/p\u003e \u003cp\u003e12.2 Main categories of fuzzy neurons.\u003c\/p\u003e \u003cp\u003e12.3 Uninorm-based fuzzy neurons.\u003c\/p\u003e \u003cp\u003e12.4 Architectures of logic networks.\u003c\/p\u003e \u003cp\u003e12.5 The development mechanisms of the fuzzy neural networks.\u003c\/p\u003e \u003cp\u003e12.6 Interpretation of the fuzzy neural networks.\u003c\/p\u003e \u003cp\u003e12.7 From fuzzy logic networks to Boolean functions and their minimization through learning.\u003c\/p\u003e \u003cp\u003e12.8 Interfacing the fuzzy neural network.\u003c\/p\u003e \u003cp\u003e12.9 Interpretation aspects - a refinement of induced rule-based system.\u003c\/p\u003e \u003cp\u003e12.10 Reconciliation of perception of information granules and granular mappings.\u003c\/p\u003e \u003cp\u003e12.11 Conclusions.\u003c\/p\u003e \u003cp\u003eExercises and problems.\u003c\/p\u003e \u003cp\u003eHistorical notes.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13. Fuzzy Systems and Computational Intelligence.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1 Computational Intelligence.\u003c\/p\u003e \u003cp\u003e13.2 Recurrent neurofuzzy systems.\u003c\/p\u003e \u003cp\u003e13.3 Genetic fuzzy systems.\u003c\/p\u003e \u003cp\u003e13.4 Coevolutionary hierarchical genetic fuzzy system.\u003c\/p\u003e \u003cp\u003e13.5 Hierarchical collaborative relations.\u003c\/p\u003e \u003cp\u003e13.6 Evolving fuzzy systems.\u003c\/p\u003e \u003cp\u003e13.7 Conclusions.\u003c\/p\u003e \u003cp\u003eExercises and problems.\u003c\/p\u003e \u003cp\u003eHistorical notes.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14. Granular Models and Human Centric Computing.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e14.1 The cluster-based representation of the input - output mappings.\u003c\/p\u003e \u003cp\u003e14.2 Context-based clustering in the development of granular models.\u003c\/p\u003e \u003cp\u003e14.3 Granular neuron as a generic processing element in granular networks.\u003c\/p\u003e \u003cp\u003e14.4 Architecture of granular models based on conditional fuzzy clustering.\u003c\/p\u003e \u003cp\u003e14.5 Refinements of granular models.\u003c\/p\u003e \u003cp\u003e14.6 Incremental granular models.\u003c\/p\u003e \u003cp\u003e14.7 Human-centric fuzzy clustering.\u003c\/p\u003e \u003cp\u003e14.8 Participatory learning in fuzzy clustering.\u003c\/p\u003e \u003cp\u003e14.9 Conclusions.\u003c\/p\u003e \u003cp\u003eExercises and problems.\u003c\/p\u003e \u003cp\u003eHistorical notes.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15. Emerging Trends in Fuzzy Systems.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e15.1 Relational ontology in information retrieval.\u003c\/p\u003e \u003cp\u003e15.2 Multiagent fuzzy systems.\u003c\/p\u003e \u003cp\u003e15.3 Distributed fuzzy control.\u003c\/p\u003e \u003cp\u003e15.4 Conclusions.\u003c\/p\u003e \u003cp\u003eExercises and problems.\u003c\/p\u003e \u003cp\u003eHistorical notes.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003eAppendix A: Mathematical Prerequisites.\u003c\/p\u003e \u003cp\u003eAppendix B: Neurocomputing.\u003c\/p\u003e \u003cp\u003eAppendix C: Biologically Inspired Optimization.\u003c\/p\u003e \u003cp\u003eIndex.\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Electronics \u0026amp; communications engineering [\u003ca title=\"See our other books on Electronics \u0026amp; communications engineering\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Electronics%20\u0026amp;%20communications%20engineering%20%5BTJ%5D%22\"\u003eTJ\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley-IEEE Press","offers":[{"title":"Brand New","offer_id":52405526397208,"sku":"9780471788577","price":114.55,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9780471788577.jpg?v=1784136177","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/fuzzy-systems-engineering-toward-human-centric-computing-hardback-9780471788577","provider":"Freshly Printed Books","version":"1.0","type":"link"}