Titlebook: Evolutionary Algorithms and Neural Networks; Theory and Applicati Seyedali Mirjalili Book 2019 Springer International Publishing AG, part o

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Book 2019 offers a literature review of several well-regarded evolutionary algorithms, including particle swarm and ant colony optimization, genetic algorithms and biogeography-based optimization. It then proposes evolutionary version of several types of neural networks such as feed forward neural networks,

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https://doi.org/10.1007/978-3-319-93025-1Optimization for Real World Problems; Single-objective Optimization Algorithm; Stochastic Optimization

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https://doi.org/10.1007/978-3-8350-5527-8larly to other evolutionary algorithms, BBO has been equipped with crossover and mutations. The main difference between this algorithm and GA is the use of two operators to perform crossover and exploitation. The concepts of mutation is also similar, in which small changes occur in variables of solu

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,Erwerbst?tige Frauen als Problemgruppe,ms are then applied to the datasets for classification. The chapter also considers the comparison and analysis of different evolutionary algorithms for classifying datasets as well. Another contribution is finding the best set of features for the dataset using evolutionary algorithms. The results sh

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