Buch, Englisch, Band 771, 279 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 1310 g
Reihe: The Springer International Series in Engineering and Computer Science
Structures, Learning and Performance Evaluation
Buch, Englisch, Band 771, 279 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 1310 g
Reihe: The Springer International Series in Engineering and Computer Science
ISBN: 978-1-4020-8042-5
Verlag: Springer US
Flexible Neuro-Fuzzy Systems is the only book that proposes a flexible approach to fuzzy modeling and fills the gap in existing literature. This book introduces new fuzzy systems which outperform previous approaches to system modeling and classification, and has the following features:
-Provides a framework for unification, construction and development of neuro-fuzzy systems;
-Presents complete algorithms in a systematic and structured fashion, facilitating understanding and implementation,
-Covers not only advanced topics but also fundamentals of fuzzy sets,
-Includes problems and exercises following each chapter,
-Illustrates the results on a wide variety of simulations,
-Provides tools for possible applications in business and economics, medicine and bioengineering, automatic control, robotics and civil engineering.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik Mathematik Mathematische Analysis Variationsrechnung
- Mathematik | Informatik Mathematik Mathematik Allgemein Grundlagen der Mathematik
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
- Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
Weitere Infos & Material
Elements of the Theory of Fuzzy Sets.- Fuzzy Inference Systems.- Flexibility in Fuzzy Systems.- Flexible Or-Type Neuro-Fuzzy Systems.- Flexible Compromise and-Type Neuro-Fuzzy Systems.- Flexible Mamdani-Type Neuro-Fuzzy Systems.- Flexible Logical-Type Neuro-Fuzzy Systems.- Performance Comparison of Neuro-Fuzzy Systems.