| 书目名称 | Multidimensional Particle Swarm Optimization for Machine Learning and Pattern Recognition | | 编辑 | Serkan Kiranyaz,Turker Ince,Moncef Gabbouj | | 视频video | | | 概述 | Presents a new optimization technique.Characterized by an emphasis on solving real-world problems.Supported by source code and datasets.Includes supplementary material: | | 丛书名称 | Adaptation, Learning, and Optimization | | 图书封面 |  | | 描述 | .For many engineering problems we require optimization processes with dynamic adaptation as we aim to establish the dimension of the search space where the optimum solution resides and develop robust techniques to avoid the local optima usually associated with multimodal problems. This book explores multidimensional particle swarm optimization, a technique developed by the authors that addresses these requirements in a well-defined algorithmic approach. . .After an introduction to the key optimization techniques, the authors introduce their unified framework and demonstrate its advantages in challenging application domains, focusing on the state of the art of multidimensional extensions such as global convergence in particle swarm optimization, dynamic data clustering, evolutionary neural networks, biomedical applications and personalized ECG classification, content-based image classification and retrieval, and evolutionary feature synthesis. The content is characterizedby strong practical considerations, and the book is supported with fully documented source code for all applications presented, as well as many sample datasets. . .The book will be of benefit to researchers and prac | | 出版日期 | Book 2014 | | 关键词 | Content-based image retrieval; Data clustering; Evolutionary computing; Evolutionary feature synthesis; | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-642-37846-1 | | isbn_softcover | 978-3-642-43762-5 | | isbn_ebook | 978-3-642-37846-1Series ISSN 1867-4534 Series E-ISSN 1867-4542 | | issn_series | 1867-4534 | | copyright | Springer-Verlag Berlin Heidelberg 2014 |
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发表于 2025-3-21 16:04:16
