LEADER 05094nam  2200721Ia 450 
001 9910453555403321
005 20200520144314.0
010   $a9786611956370
010   $a1-281-95637-6
010   $a981-281-073-0
035   $a(CKB)1000000000538123
035   $a(EBL)1679316
035   $a(SSID)ssj0000161591
035   $a(PQKBManifestationID)11155014
035   $a(PQKBTitleCode)TC0000161591
035   $a(PQKBWorkID)10198288
035   $a(PQKB)10694958
035   $a(SSID)ssj0000297330
035   $a(PQKBManifestationID)12115701
035   $a(PQKBTitleCode)TC0000297330
035   $a(PQKBWorkID)10332713
035   $a(PQKB)24810909
035   $a(MiAaPQ)EBC1679316
035   $a(WSP)00004177
035   $a(Au-PeEL)EBL1679316
035   $a(CaPaEBR)ebr10255772
035   $a(CaONFJC)MIL195637
035   $a(OCoLC)879023390
035   $a(EXLCZ)991000000000538123
100   $a20010812d2001      uy             0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 00$aGenetic fuzzy systems$b[electronic resource] $eevolutionary tuning and learning of fuzzy knowledge bases /$fOscar Cordo?n ... [et al.]
210   $aSingapore ;$aRiver Edge, NJ $cWorld Scientific$dc2001
215   $a1 online resource (489 p.)
225 1 $aAdvances in fuzzy systems ;$vv. 19
300   $aDescription based upon print version of record.
311   $a981-02-4017-1 
311   $a981-02-4016-3 
320   $aIncludes bibliographical references (p. 425-456) and index.
327   $aForeword; Preface; Contents; Chapter 1 Fuzzy Rule-Based Systems; 1.1 Framework: Fuzzy Logic and Fuzzy Systems; 1.2 Mamdani Fuzzy Rule-Based Systems; 1.3 Takagi-Sugeno-Kang Fuzzy Rule-Based Systems; 1.4 Generation of the Fuzzy Rule Set; 1.5 Applying Fuzzy Rule-Based Systems; Chapter 2 Evolutionary Computation; 2.1 Conceptual Foundations of Evolutionary Computation; 2.2 Genetic Algorithms; 2.3 Other Evolutionary Algorithms; Chapter 3 Introduction to Genetic Fuzzy Systems; 3.1 Soft Computing; 3.2 Hybridisation in Soft Computing; 3.3 Integration of Evolutionary Algorithms and Fuzzy Logic
327   $a3.4 Genetic Fuzzy SystemsChapter 4 Genetic Tuning Processes; 4.1 Tuning of Fuzzy Rule-Based Systems; 4.2 Genetic Tuning of Scaling Functions; 4.3 Genetic Tuning of Membership Functions of Mamdani Fuzzy Rule-Based Systems; 4.4 Genetic Tuning of TSK Fuzzy Rule Sets; Chapter 5 Learning with Genetic Algorithms; 5.1 Genetic Learning Processes. Introduction; 5.2 The Michigan Approach. Classifier Systems; 5.3 The Pittsburgh Approach; 5.4 The Iterative Rule Learning Approach; Chapter 6 Genetic Fuzzy Rule-Based Systems Based on the Michigan Approach; 6.1 Basic Features of Fuzzy Classifier Systems
327   $a6.2 Fuzzy Classifier Systems for Learning Rule Bases6.3 Fuzzy Classifier Systems for Learning Fuzzy Rule Bases; Chapter 7 Genetic Fuzzy Rule-Based Systems Based on the Pittsburgh Approach; 7.1 Coding Rule Bases as Chromosomes; 7.2 Multi-chromosome Genomes (Coding Knowledge Bases); 7.3 Examples; Chapter 8 Genetic Fuzzy Rule-Based Systems Based on the Iterative Rule Learning Approach; 8.1 Coding the Fuzzy Rules; 8.2 Learning Fuzzy Rules under Competition; 8.3 Post-Processing: Refining Rule Bases under Cooperation; 8.4 Inducing Cooperation in the Fuzzy Rule Generation Stage; 8.5 Examples
327   $aChapter 9 Other Genetic Fuzzy Rule-Based System Paradigms9.1 Designing Fuzzy Rule-Based Systems with Genetic Progamming; 9.2 Genetic Selection of Fuzzy Rule Sets; 9.3 Learning the Knowledge Base via the Genetic Derivation of the Data Base; 9.4 Other Genetic-Based Machine Learning Approaches; Chapter 10 Other Kinds of Evolutionary Fuzzy Systems; 10.1 Genetic Fuzzy Neural Networks; 10.2 Genetic Fuzzy Clustering; 10.3 Genetic Fuzzy Decision Trees; Chapter 11 Applications; 11.1 Classification; 11.2 System Modelling; 11.3 Control Systems; 11.4 Robotics; Bibliography; Acronyms; Index
330   $aIn recent years, a great number of publications have explored the use of genetic algorithms as a tool for designing fuzzy systems. Genetic Fuzzy Systems explores and discusses this symbiosis of evolutionary computation and fuzzy logic. The book summarizes and analyzes the novel field of genetic fuzzy systems, paying special attention to genetic algorithms that adapt and learn the knowledge base of a fuzzy-rule-based system. It introduces the general concepts, foundations and design principles of genetic fuzzy systems and covers the topic of genetic tuning of fuzzy systems. It also introduces t
410  0$aAdvances in fuzzy systems ;$vv. 19.
606   $aFuzzy systems
606   $aGenetics$xMathematical models
608   $aElectronic books.
615  0$aFuzzy systems.
615  0$aGenetics$xMathematical models.
676   $a006.31
701   $aCordo?n$b Oscar$0501266
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910453555403321
996   $aGenetic fuzzy systems$91446750
997   $aUNINA