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Titlebook: Evolutionary Machine Learning Techniques; Algorithms and Appli Seyedali Mirjalili,Hossam Faris,Ibrahim Aljarah Book 2020 Springer Nature Si

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發(fā)表于 2025-3-21 17:39:45 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Evolutionary Machine Learning Techniques
副標(biāo)題Algorithms and Appli
編輯Seyedali Mirjalili,Hossam Faris,Ibrahim Aljarah
視頻videohttp://file.papertrans.cn/318/317971/317971.mp4
概述Provides an in-depth analysis of the current evolutionary machine learning techniques.Includes training algorithms for machine learning techniques.Covers the application of improved artificial neural
叢書名稱Algorithms for Intelligent Systems
圖書封面Titlebook: Evolutionary Machine Learning Techniques; Algorithms and Appli Seyedali Mirjalili,Hossam Faris,Ibrahim Aljarah Book 2020 Springer Nature Si
描述.This book provides an in-depth analysis of the current evolutionary machine learning techniques. Discussing the most highly regarded methods for classification, clustering, regression, and prediction, it includes techniques such as support vector machines, extreme learning machines, evolutionary feature selection, artificial neural networks including feed-forward neural networks, multi-layer perceptron, probabilistic neural networks, self-optimizing neural networks, radial basis function networks, recurrent neural networks, spiking neural networks, neuro-fuzzy networks, modular neural networks, physical neural networks, and deep neural networks..?..The book provides essential definitions, literature reviews, and the training algorithms for machine learning using classical and modern nature-inspired techniques. It also investigates the pros and cons of classical training algorithms. It features a range of proven and recent nature-inspired algorithms used to train different types of artificial neural networks, including genetic algorithm, ant colony optimization, particle swarm optimization, grey wolf optimizer, whale optimization algorithm, ant lion optimizer, moth flame algorithm,
出版日期Book 2020
關(guān)鍵詞Artificial Neural Network; Probabilistic Neural Network; Self-Optimizing Neural Network; Feedforward Ne
版次1
doihttps://doi.org/10.1007/978-981-32-9990-0
isbn_softcover978-981-32-9992-4
isbn_ebook978-981-32-9990-0Series ISSN 2524-7565 Series E-ISSN 2524-7573
issn_series 2524-7565
copyrightSpringer Nature Singapore Pte Ltd. 2020
The information of publication is updating

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