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Springer Fuzzy Logic Hybrid Extensions of Neural Algorithms

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Description

Expand your knowledge in computational intelligence 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 focuses on the integration of neural networks and optimization methods. This book serves as a specialized resource for researchers and students working within the fields of Artificial Intelligence and Machine Learning. By exploring the theoretical foundations and practical applications of hybrid systems, readers can gain a deeper understanding of how fuzzy logic can enhance computational models. This volume is an essential addition to any professional library dedicated to computer science and advanced algorithmic development.

Key Features

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

Focuses on the theoretical and practical aspects of neural and optimization algorithm extensions.

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

Highly relevant for professionals and students specializing in AI and Machine Learning.

Provides technical insights into the application of fuzzy logic within computational systems.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
25 March 2021
Listed Since
05 January 2021

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