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Fuzzy Logic Augmentation of Nature-Inspired Optimization Metaheuristics: Theory and Applications 2015 ed. [Kõva köide]

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  • Formaat: Hardback, 195 pages, kõrgus x laius: 235x155 mm, kaal: 4321 g, 98 Illustrations, black and white; VIII, 195 p. 98 illus., 1 Hardback
  • Sari: Studies in Computational Intelligence 574
  • Ilmumisaeg: 01-Oct-2014
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3319109596
  • ISBN-13: 9783319109596
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Fuzzy Logic Augmentation of Nature-Inspired Optimization Metaheuristics: Theory and Applications 2015 ed.Suurem pilt
  • Formaat: Hardback, 195 pages, kõrgus x laius: 235x155 mm, kaal: 4321 g, 98 Illustrations, black and white; VIII, 195 p. 98 illus., 1 Hardback
  • Sari: Studies in Computational Intelligence 574
  • Ilmumisaeg: 01-Oct-2014
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3319109596
  • ISBN-13: 9783319109596
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783319109596.html
Märksõnad:

This book describes recent advances on fuzzy logic augmentation of nature-inspired optimization metaheuristics and their application in areas such as intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. The book is organized in two main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of theoretical aspects of fuzzy logic augmentation of nature-inspired optimization metaheuristics, which basically consists of papers that propose new optimization algorithms enhanced using fuzzy systems. The second part contains papers with the main theme of application of optimization algorithms, which are basically papers using nature-inspired techniques to achieve optimization of complex optimization problems in diverse areas of application.

Arvustused

From the book reviews:

This book presents recent developments in a specific area of computational intelligence, namely fuzzy logic augmentation of nature-inspired optimization metaheuristics and their applications. the book is very interesting for those working in the field of computational intelligence. It will be useful for the researchers and practitioners working in this area of research. (Petrica Pop, Computing Reviews, February, 2015)

Part I Theory
Fuzzy Logic for Dynamic Parameter Tuning in ACO and Its Application in Optimal Fuzzy Logic Controller Design
3(26)
Hector Neyoy
Oscar Castillo
Jose Soria
Fuzzy Classification System Design Using PSO with Dynamic Parameter Adaptation Through Fuzzy Logic
29(20)
Frumen Olivas
Fevrier Valdez
Oscar Castillo
Differential Evolution with Dynamic Adaptation of Parameters for the Optimization of Fuzzy Controllers
49(16)
Patricia Ochoa
Oscar Castillo
Jose Soria
A New Bat Algorithm with Fuzzy Logic for Dynamical Parameter Adaptation and Its Applicability to Fuzzy Control Design
65(16)
Jonathan Perez
Fevrier Valdez
Oscar Castillo
Optimization of Benchmark Mathematical Functions Using the Firefly Algorithm with Dynamic Parameters
81(10)
Cinthya Solano-Aragon
Oscar Castillo
Cuckoo Search via Levy Flights and a Comparison with Genetic Algorithms
91(14)
Maribel Guerrero
Oscar Castillo
Mario Garcia
A Harmony Search Algorithm Comparison with Genetic Algorithms
105(22)
Cinthia Peraza
Fevrier Valdez
Oscar Castillo
Part II Applications
A Gravitational Search Algorithm for Optimization of Modular Neural Networks in Pattern Recognition
127(12)
Beatriz Gonzalez
Fevrier Valdez
Patricia Melin
German Prado-Arechiga
Ensemble Neural Network Optimization Using the Particle Swarm Algorithm with Type-1 and Type-2 Fuzzy Integration for Time Series Prediction
139(12)
Martha Pulido
Patricia Melin
Clustering Bin Packing Instances for Generating a Minimal Set of Heuristics by Using Grammatical Evolution
151(12)
Marco Aurelio Sotelo-Figueroa
Hector Jose Puga Soberanes
Juan Martin Carpio
Hector J. Fraire Huacuja
Laura Cruz Reyes
Jorge Alberto Soria Alcaraz
Comparative Study of Particle Swarm Optimization Variants in Complex Mathematics Functions
163(16)
Juan Carlos Vazquez
Fevrier Valdez
Patricia Melin
Optimization of Modular Network Architectures with a New Evolutionary Method Using a Fuzzy Combination of Particle Swarm Optimization and Genetic Algorithms
179
Fevrier Valdez