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Springer Modular Neural Networks and Type-2 Fuzzy Systems 389

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Description

Expand your knowledge of hybrid intelligent systems with this technical volume from Springer. Part of the Studies in Computational Intelligence series (Volume 389), this book provides a detailed look at how type-2 fuzzy logic and modular neural networks work together for pattern recognition applications. Readers will find a comprehensive guide covering basic theory and the practical use of type-2 fuzzy models. The text also addresses the optimization of type-2 fuzzy systems and modular neural networks, making it a valuable resource for those studying advanced computing paradigms. By combining fuzzy logic, neural networks, and bio-inspired optimization algorithms, this work explores how different intelligent computing methods can be integrated to solve complex problems. This book is designed for researchers and students interested in the intersection of machine learning and fuzzy logic systems.

Key Features

Covers hybrid intelligent systems that combine fuzzy logic, neural networks, and bio-inspired optimization algorithms.

Provides foundational theory and practical applications for using type-2 fuzzy models in pattern recognition.

Explores optimization techniques for both type-2 fuzzy systems and modular neural networks.

Part of the Studies in Computational Intelligence series, volume 389, for specialized academic study.

Focuses on the integration of multiple intelligent computing paradigms for advanced pattern recognition.

Product Specifications

Format
paperback
Domain
Amazon UK
Publication Date
30 November 2013
Listed Since
01 November 2013

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