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Springer Nature-Inspired Hybrid Intelligent Systems Book 667

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Description

Explore recent advances in hybrid intelligent systems with this Springer publication from the Studies in Computational Intelligence series. This technical text covers design methods based on nature-inspired optimization and their practical use in robotics, intelligent control, and pattern recognition. The book is organized into seven main parts to guide readers through complex topics. The first section addresses theoretical aspects and new algorithms using type-2 and intuitionistic fuzzy logic systems. The second part focuses on neural network theory and explores how these networks function in diverse areas such as time series prediction and the optimization of complex problems. This resource provides a deep look into the intersection of computational intelligence and real-world application.

Key Features

This Springer book covers recent advances in hybrid intelligent systems based on nature-inspired optimization.

The text explores applications in robotics, intelligent control, pattern recognition, and time series prediction.

Part one of the book addresses theoretical concepts and algorithms for type-2 and intuitionistic fuzzy logic systems.

The second part focuses on neural network theory and its use in various diverse application areas.

This volume is part of the Studies in Computational Intelligence series, specifically number 667.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
05 July 2018
Listed Since
05 July 2018

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