| 书目名称 | Metaheuristics in Machine Learning: Theory and Applications | | 编辑 | Diego Oliva,Essam H. Houssein,Salvador Hinojosa | | 视频video | | | 概述 | Provides representative tools used for machine learning and metaheuristic algorithms.Focuses on the theory and application of metaheuristic algorithms in machine learning, including hybridization and | | 丛书名称 | Studies in Computational Intelligence | | 图书封面 |  | | 描述 | This book is a collection of the most recent approaches that combine metaheuristics and machine learning. Some of the methods considered in this book are evolutionary, swarm, machine learning, and deep learning. The chapters were classified based on the content; then, the sections are thematic. Different applications and implementations are included; in this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms..The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and is useful in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the book is useful for research from the evolutionary computation, artificial intelligence, and image processing communities. . | | 出版日期 | Book 2021 | | 关键词 | Metaheuristics; Machine Learning; Clustering; Fuzzy Systems; Image processing | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-70542-8 | | isbn_softcover | 978-3-030-70544-2 | | isbn_ebook | 978-3-030-70542-8Series ISSN 1860-949X Series E-ISSN 1860-9503 | | issn_series | 1860-949X | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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发表于 2025-3-21 17:36:03
