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2014 | Buch

Fuzzy Sets Kapitel lesen Erstes Kapitel lesen

Type-2 Fuzzy Neural Networks and Their Applications

verfasst von: Rafik Aziz Aliev, Babek Ghalib Guirimov

Verlag: Springer International Publishing

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

This book deals with the theory, design principles, and application of hybrid intelligent systems using type-2 fuzzy sets in combination with other paradigms of Soft Computing technology such as Neuro-Computing and Evolutionary Computing. It provides a self-contained exposition of the foundation of type-2 fuzzy neural networks and presents a vast compendium of its applications to control, forecasting, decision making, system identification and other real problems. Type-2 Fuzzy Neural Networks and Their Applications is helpful for teachers and students of universities and colleges, for scientists and practitioners from various fields such as control, decision analysis, pattern recognition and similar fields.

Inhaltsverzeichnis

Frontmatter
Chapter 1. Fuzzy Sets
Abstract
This chapter is a succinct exposition of the basics of fuzzy logic, with emphasis on those parts of fuzzy logic which are of prime relevance to neuro-fuzzy approach. Here foundations of fuzzy sets theory, including basic concepts and properties of type-1 and type-2 fuzzy sets, elements of fuzzy mathematics, and fuzzy relations are given. This chapter also contains elements of fuzzy logic (in narrow sense of L.Zadeh), which is viewed as a generalization of the various multi-valued logics. This chapter includes compositional rules of inference, choice of fuzzy implications, formalization of fuzzy conditional inference using the fuzzy implications suggested by the authors.
Rafik Aziz Aliev, Babek Ghalib Guirimov
Chapter 2. Evolutionary Computing and Type-2 Fuzzy Neural Networks
Abstract
This chapter deals with comparative analysis of methods of evolutionary computing and its merging with type-2 fuzzy neural networks. The models of neural networks and, especially, fuzzy and high-order fuzzy networks can be described by complex nonlinear, non-convex, and non-differentiable functions. As evolutionary optimization methods do not require any restrictive properties for the functions or the computational models to work with, they can be effectively used for training of parameters of fuzzy type-2 neural networks. The chapter includes main characteristics of genetic algorithms, particle swarm optimization (PSO), differential evolution (DE) methods. An emphasis is put on the DE method and its application to the training of all types of neural networks.
Rafik Aziz Aliev, Babek Ghalib Guirimov
Chapter 3. Type-1 and Type-2 Fuzzy Neural Networks
Abstract
The subject of this chapter is Type-1 and type-2 fuzzy neural networks. This chapter is source of information on neuro-fuzzy computing, basic architectures and operations of fuzzy feed-forward and recurrent neural networks, several types of fuzzy logical neuron models, logic-oriented neural networks, general and interval type-2 fuzzy neural network’s features and their training algorithms.
Rafik Aziz Aliev, Babek Ghalib Guirimov
Chapter 4. Type-2 Fuzzy Clustering
Abstract
Clustering can be part of training strategy for such neural networks as RBF and logical and ordinary fuzzy neural networks in case of presence of large sets of crisp and noisy training data. This chapter contains elements of general and interval type-2 FCM clustering methods, interval type-2 fuzzy clustering using DE, and design of type-2 neural networks with clustering.
Rafik Aziz Aliev, Babek Ghalib Guirimov
Chapter 5. Application of Type-2 Fuzzy Neural Networks
Abstract
This chapter describes application of type-2 neural networks to real-word problems in decision making, forecasting, control, identification and other areas. The chapter also discuss on Computing with Words (CWW) paradigm and possible ways of its modeling with type-2 neural networks.
Rafik Aziz Aliev, Babek Ghalib Guirimov
Backmatter
Metadaten
Titel
Type-2 Fuzzy Neural Networks and Their Applications
verfasst von
Rafik Aziz Aliev
Babek Ghalib Guirimov
Copyright-Jahr
2014
Electronic ISBN
978-3-319-09072-6
Print ISBN
978-3-319-09071-9
DOI
https://doi.org/10.1007/978-3-319-09072-6