
Автор: Debashish Das, Ali Safaa Sadiq, Seyedali Mirjalili
Издательство: Springer
Год: 2025
Страниц: 189
Язык: английский
Формат: pdf (true), epub
Размер: 28.9 MB
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. Artificial Intelligence which mostly simulates the human intelligence through machine is one of the most trending technologies around the globe that impacts almost every domain these days. Whereas, optimization relates to the process of finding the optimum solution to a particular problem satisfying some given constraints within AI. We decided to write this book to share our understanding of optimization leveraging meta-heuristic algorithms for solving stock market prediction. The first goal of this book is to demonstrate what a meta-heuristic algorithm is and what its applications are. The second goal of this book is to show how to prepare and employ a meta-heuristic algorithm for a given optimization problem: how to create models, how to test them, and how to use them.