Optimization Algorithms in Machine Learning : A Meta-heuristics Perspective (Engineering Optimization: Methods and Applications)

Das, Debashish/ Sadiq, Ali Safaa/ Mirjalili, Seyedali

Springer Nature Switzerland AG（2025/05発売）

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製本 Hardcover:ハードカバー版／ページ数 172 p.
言語 ENG
商品コード 9789819638482

Full Description

This book explores the development of several new learning algorithms that utilize recent optimization techniques and meta-heuristics. It addresses well-known models such as particle swarm optimization, genetic algorithm, ant colony optimization, evolutionary strategy, population-based incremental learning, and grey wolf optimizer for training neural networks. Additionally, the book examines the challenges associated with these processes in detail. This volume will serve as a valuable reference for individuals in both academia and industry.

Challenges and opportunities in Machine Learning using optimization techniques.- Optimization methods: traditional versus stochastic.- Heuristic and meta-heuristic optimization algorithms.- A comprehensive review of evolutionary algorithms and swarm intelligence methods.- Artificial Neural Networks: structure and learning.- A survey of Neural Networks trained by optimization algorithms and meta-heuristics.