Buch, Englisch, Band 7, 394 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 1680 g
Paradigms and Practice
Buch, Englisch, Band 7, 394 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 1680 g
Reihe: International Series in Intelligent Technologies
ISBN: 978-0-7923-9703-8
Verlag: Springer Us
The objective of this book is to provide researchers and practitioners involved in the development of models for complex systems with an understanding of fuzzy modelling, and an appreciation of what makes these models unique. The chapters are organized into three major parts covering relational models, fuzzy neural networks and rule-based models. The material on relational models includes theory along with a large number of implemented case studies, including some on speech recognition, prediction, and ecological systems. The part on fuzzy neural networks covers some fundamentals, such as neurocomputing, fuzzy neurocomputing, etc., identifies the nature of the relationship that exists between fuzzy systems and neural networks, and includes extensive coverage of their architectures. The last part addresses the main design principles governing the development of rule-based models.
provides a wealth of specific fuzzy modelling paradigms, algorithms and tools used in systems modelling. Also included is a panoply of case studies from various computer, engineering and science disciplines. This should be a primary reference work for researchers and practitioners developing models of complex systems.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik Mathematik Mathematische Analysis Variationsrechnung
- Mathematik | Informatik Mathematik Mathematik Allgemein Grundlagen der Mathematik
- Mathematik | Informatik Mathematik Mathematik Allgemein Mathematische Logik
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
- Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Mikroprozessoren
Weitere Infos & Material
1: Modelling with Fuzzy Sets.- 1.1. Fuzzy Models: Methodology, Design, Applications, and Challenges.- 2: Relational Models.- 2.1. Fundamentals of Fuzzy Relational Calculus.- 2.2. Max-Min Relational Networks.- 2.3. Relational Calculus in Designing Fuzzy Petri Networks.- 2.4. Prediction in Relational Models.- 2.5 Implementing A Fuzzy Relational Network For Phonetic Automatic Speech Recognition.- 2.6 Fuzzy Ecological Models.- 3: Fuzzy Neural Networks.- 3.1. Fuzzy Neural Networks: Capabilities.- 3.2. Development of Fuzzy Neural Networks.- 3.3. Designing Fuzzy Neural Networks Through Backpropagation.- 4: Rule-Based Modelling.- 4.1. Foundations of Rule-Based Computations in Fuzzy Models.- 4.2. Evolutionary Learning of Rules Competition and Cooperation.- 4.3 Logical Optimization of Rule-Based Models.- 4.4 Interpretation and Completion of Fuzzy Rules.- 4.5 Hyperellipsoidal Clustering.- 4.6. Fuzzy Rule-Based Models in Computer Vision.- 4.7. Forecasting in Rule-Based Systems.