Titlebook: Metaheuristics in Machine Learning: Theory and Applications; Diego Oliva,Essam H. Houssein,Salvador Hinojosa Book 2021 The Editor(s) (if a

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Drug Design and Discovery: Theory, Applications, Open Issues and Challenges,ploitation processes of MA’s are convenient for selecting the significant features as preprocessing to ML step for accomplishing high classification accuracy to the active chemical compound. In consequence, the results of the drug designed aim an optimal compound and enhanced the chemical descriptor.

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Artificial Neural Networks for Stock Market Prediction: A Comprehensive Review,iques. Moreover, the studies are evaluated based on databases used, performance assessment indicators, and prediction targets. The collective evidence suggests that stock market prediction involves numerous factors that need to be efficiently and precisely addressed.

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Image Classification with Convolutional Neural Networks,sification, this chapter focuses on the study of Convolutional Neural Networks (CNN), and the development of tests that facilitate the understanding of the effects of their basic parameters. The classification objects used are images, and only the multiple class classification model is considered.

Antimicrobial

Book 2021stgraduate students of Science, Engineering, and Computational Mathematics and is useful in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the book is useful for research from the evolutionary computation, artificial intelligence, and image processing communities. .

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Feature Engineering for Machine Learning and Deep Learning Assisted Wireless Communication, chapter presents the need for feature engineering and its application to machine learning and deep learning in wireless communication. The chapter also gives the details of the feature engineering assisted machine-learning algorithm for automatic modulation classi cation and path-loss prediction in wireless communication.

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Genetic Operators and Their Impact on the Training of Deep Neural Networks,ion in the maze and reach the goal. Each variation of the genetic algorithm presents changes in its operators, so the advantages or disadvantages of certain operators can be analyzed. The aim of this chapter is to analyze how the operators of the genetic algorithm impact the training and the results of the DNN model.

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Implementation of Metaheuristics with Extreme Learning Machines, of each algorithm can be observed. The data employed in this work consist of information about Australian credit, diabetes detection and hearth disease. The investigation result show that GWO obtained better results in the first dataset and PSO are better in the second and third datasets.

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ly (e.g. as channels, palaeosols, clay seamsor salts), others may be diagenetic in origin (e.g. carbonate orsilica cemented zones, authigenic clays, karstic surfaces). Theseverity with which diagenesis affects rock systems results from theinterplay between the diagenetic process itself and the times