Description: Integrating Meta-heuristics and Machine Learning for Real-world Optimization Problems, Hardcover by Houssein, Essam H. (EDT); Elaziz, Mohamed Abd (EDT); Oliva, Diego (EDT); Abualigah, Laith (EDT), ISBN 3030990788, ISBN-13 9783030990787, Brand New, Free shipping in the US This book collects different methodologies that permit metaheuristics and machine learning to solve real-world problems. This book has exciting chapters that employ evolutionary and swarm optimization tools combined with machine learning techniques. The fields of applications are from distribution systems until medical diagnosis, and they are also included different surveys and literature reviews that will enrich the reader. Besides, cutting-edge methods such as neuroevolutionary and IoT implementations are presented in some chapters. In this sense, th provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, th is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and can be used in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the material can be helpful for research from the evolutionary computation, artificial intelligence communities.
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Book Title: Integrating Meta-heuristics and Machine Learning for Real-world O
Number of Pages: IX, 497 Pages
Language: English
Publication Name: Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems
Publisher: Springer International Publishing A&G
Subject: Engineering (General), Probability & Statistics / General, Intelligence (Ai) & Semantics, General
Publication Year: 2022
Item Weight: 32.7 Oz
Type: Textbook
Item Length: 9.3 in
Subject Area: Mathematics, Computers, Technology & Engineering
Author: Mohamed Abd Elaziz
Item Width: 6.1 in
Series: Studies in Computational Intelligence Ser.
Format: Hardcover
