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Springer Fuzzy Logic Hybrid Extensions of Neural and Optimization

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Description

Expand your technical knowledge with Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications. Published by Springer as part of the Studies in Computational Intelligence series (Volume 940), this academic text provides a deep look into the integration of fuzzy logic with neural networks and optimization methods. This book serves as a specialized resource for researchers and professionals working within the fields of artificial intelligence and machine learning. By exploring the theory and applications of hybrid systems, readers can better understand how to combine different computational approaches to solve complex problems. Whether you are studying computer science or working in advanced computing, this volume offers a structured way to examine modern algorithmic developments. This edition is part of a recognized series dedicated to computational intelligence, making it a valuable addition to any professional or academic library focused on the latest advancements in AI technology.

Key Features

Part of the Studies in Computational Intelligence series, specifically volume 940.

Published by Springer, a leading name in academic and scientific literature.

Focuses on the theoretical and practical applications of hybrid neural and optimization algorithms.

Designed for readers interested in computer science, AI, and machine learning topics.

Provides a comprehensive look at fuzzy logic extensions within computational intelligence.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
29 March 2022
Listed Since
27 February 2022

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