Description: Evolutionary Machine Learning Techniques Please note: this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days). Algorithms and Applications Author(s): Seyedali Mirjalili, Hossam Faris, Ibrahim Aljarah Format: Hardback Publisher: Springer Verlag, Singapore, Singapore Imprint: Springer Verlag, Singapore ISBN-13: 9789813299894, 978-9813299894 Synopsis 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, dragonfly algorithm, salp swarm algorithm, multi-verse optimizer, and sine cosine algorithm. The book also covers applications of the improved artificial neural networks to solve classification, clustering, prediction and regression problems in diverse fields.
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Location: Aldershot
End Time: 2024-08-27T10:59:26.000Z
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Book Title: Evolutionary Machine Learning Techniques
Item Height: 235 mm
Item Width: 155 mm
Series: Algorithms for Intelligent Systems
Author: Ibrahim Aljarah, Hossam Faris, Seyedali Mirjalili
Publication Name: Evolutionary Machine Learning Techniques: Algorithms and Applications
Format: Hardcover
Language: English
Publisher: Springer Verlag, Singapore
Subject: Computer Science, Mathematics
Publication Year: 2019
Type: Textbook
Item Weight: 612 g
Number of Pages: 286 Pages