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Advanced Fuzzy Systems Design and Applications

Aus der Reihe Studies in Fuzziness and Soft Computing
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96,99 € UVP 109,99 €

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Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

18.11.2002

Abbildungen

X, 272 p. 228 illus.

Verlag

Physica

Seitenzahl

272

Maße (L/B/H)

24,1/16/2,1 cm

Gewicht

600 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-3-7908-1537-5

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

18.11.2002

Abbildungen

X, 272 p. 228 illus.

Verlag

Physica

Seitenzahl

272

Maße (L/B/H)

24,1/16/2,1 cm

Gewicht

600 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-3-7908-1537-5

Herstelleradresse

Physica Verlag
Tiergartenstr. 17
69121 Heidelberg
DE

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  • Produktbild: Advanced Fuzzy Systems Design and Applications
  • Produktbild: Advanced Fuzzy Systems Design and Applications
  • 1. Fuzzy Sets and Fuzzy Systems.- 1.1 Basics of Fuzzy Sets.- 1.2 Fuzzy Rule Systems.- 1.3 Interpretability of Fuzzy Rule System.- 1.4 Knowledge Processing with Fuzzy Logic.- 2. Evolutionary Algorithms.- 2.1 Introduction.- 2.2 Generic Evolutionary Algorithms.- 2.3 Adaptation and Self-Adaptation in Evolutionary Algorithms.- 2.4 Constraints Handling.- 2.5 Multi-objective Evolution.- 2.6 Evolution with Uncertain Fitness Functions.- 2.7 Parallel Implementations.- 2.8 Summary.- 3. Artificial Neural Networks.- 3.1 Introduction.- 3.2 Feedforward Neural Network Models.- 3.3 Learning Algorithms.- 3.4 Improvement of Generalization.- 3.5 Rule Extraction from Neural Networks.- 3.6 Interaction between Evolution and Learning.- 3.7 Summary.- 4. Conventional Data-driven Fuzzy Systems Design.- 4.1 Introduction.- 4.2 Fuzzy Inference Based Method.- 4.3 Wang-Mendel’s Method.- 4.4 A Direct Method.- 4.5 An Adaptive Fuzzy Optimal Controller.- 4.6 Summary.- 5.Neural Network Based Fuzzy Systems Design.- 5.1 Neurofuzzy Systems.- 5.2 The Pi-sigma Neurofuzzy Model.- 5.3 Modeling and Control Using the Neurofuzzy System.- 5.4 Neurofuzzy Control of Nonlinear Systems.- 5.5 Summary.- 6. Evolutionary Design of Fuzzy Systems.- 6.1 Introduction.- 6.2 Evolutionary Design of Flexible Structured Fuzzy Controller..- 6.3 Evolutionary Optimization of Fuzzy Rules.- 6.4 Fuzzy Systems Design for High-Dimensional Systems.- 6.5 Summary.- 7. Knowledge Discovery by Extracting Interpretable Fuzzy Rules.- 7.1 Introduction.- 7.2 Evolutionary Interpretable Fuzzy Rule Generation.- 7.3 Interactive Co-evolution for Fuzzy Rule Extraction.- 7.4 Fuzzy Rule Extraction from RBF Networks.- 7.5 Summary.- 8. Fuzzy Knowledge Incorporation into Neural Networks.- 8.1 Data and A Priori Knowledge.- 8.2 Knowledge Incorporation in NeuralNetworks for Control.- 8.3 Fuzzy Knowledge Incorporation By Regularization.- 8.4 Fuzzy Knowledge as A Related Task in Learning.- 8.5 Simulation Studies.- 8.6 Summary.- 9. Fuzzy Preferences Incorporation into Multi-objective Optimization.- 9.1 Multi-objective Optimization and Preferences Handling.- 9.2 Evolutionary Dynamic Weighted Aggregation.- 9.3 Fuzzy Preferences Incorporation in MOO.- 9.4 Summary.- References.