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Springer Fuzzy Logic & Neural Algorithms - Studies in Comp Intel

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Description

Explore advanced computational intelligence in this Springer publication, Fuzzy Logic Augmentation of Neural and Optimization Algorithms. This volume, part of the Studies in Computational Intelligence series (749), provides a deep look into fuzzy logic, neural networks, and nature-inspired optimization meta-heuristics. The book covers diverse applications including intelligent control, robotics, pattern recognition, and medical diagnosis. It also addresses time series prediction and the optimization of complex problems. Organized into seven main parts, the text presents new concepts such as type-2 fuzzy logic for dynamic parameter adaptation in meta-heuristics and explores network theory and its practical applications. This is an essential resource for professionals and researchers working in AI, machine learning, and complex system optimization.

Key Features

This Springer book covers diverse aspects of fuzzy logic, neural networks, and nature-inspired optimization meta-heuristics.

The content includes applications in intelligent control, robotics, pattern recognition, and medical diagnosis.

Learn about time series prediction and the optimization of complex problems through various research papers.

The text presents new concepts and algorithms based on type-2 fuzzy logic for dynamic parameter adaptation.

The volume is organized into seven main parts covering subjects like network theory and its applications.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
06 June 2019
Listed Since
24 December 2018

Barcode

No barcode data available

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