Description: Evolutionary Machine Learning Techniques : Algorithms and Applications, Paperback by Mirjalili, Seyedali (EDT); Faris, Hossam (EDT); Aljarah, Ibrahim (EDT), ISBN 9813299924, ISBN-13 9789813299924, Brand New, Free shipping in the US 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. Th 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. Th also covers applications of the improved artificial neural networks to solve classification, clustering, prediction and regression problems in diverse fields.
Price: 218.06 USD
Location: Jessup, Maryland
End Time: 2024-11-23T22:55:14.000Z
Shipping Cost: 0 USD
Product Images
Item Specifics
Restocking Fee: No
Return shipping will be paid by: Buyer
All returns accepted: Returns Accepted
Item must be returned within: 14 Days
Refund will be given as: Money Back
Book Title: Evolutionary Machine Learning Techniques : Algorithms and Applica
Number of Pages: X, 286 Pages
Publication Name: Evolutionary Machine Learning Techniques : Algorithms and Applications
Language: English
Publisher: Springer
Publication Year: 2020
Subject: Engineering (General), Intelligence (Ai) & Semantics, Applied
Type: Textbook
Item Weight: 16.1 Oz
Item Length: 9.3 in
Author: Hossam Faris
Subject Area: Mathematics, Computers, Technology & Engineering
Item Width: 6.1 in
Series: Algorithms for Intelligent Systems Ser.
Format: Trade Paperback
