Recent Advances in Machine Learning and Computational Intelligence

doi:10.3390/books978-3-0365-7483-7

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Recent Advances in Machine Learning and Computational Intelligence

Edited by

May 2023

216 pages

ISBN978-3-0365-7482-0 (Hardback)
ISBN978-3-0365-7483-7 (PDF)

https://doi.org/10.3390/books978-3-0365-7483-7

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This book is a reprint of the Special Issue Recent Advances in Machine Learning and Computational Intelligence that was published in

Biology & Life Sciences

Chemistry & Materials Science

Computer Science & Mathematics

Engineering

Environmental & Earth Sciences

Physical Sciences

Summary

Machine learning and computational intelligence have been applied to various areas and witnessed many successes. The research in this publication explorse many intelligent algorithms which are characterized by computational adaptability, robustness, and high performance. These algorithms facilitate intelligent behavior in complex and dynamic environments and the development of technology that enables machines to think, behave, or act in a more humanesque fashion. This reprint aims to present and discuss the most recent innovations, trends, concerns, challenges, solutions, and application fields in the areas of machine learning and computational intelligence.

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Keywords

left ventricle segmentation; UNet 3+; encoder–decoder; transformer; magnetic resonance imaging; beta function; crow search algorithm; dynamic multi-objective optimization problems; evolutionary algorithm; many-objective optimization problems; naive Bayesian classifier; attribute independence assumption; mixed-attribute classification; conditional probability; Bayesian network; attribute transformation; subsection proximal policy optimization; weighted importance sampling; TORCS; vehicle-following; autonomous driving; credit scoring; machine learning; deep learning; transformer; model predictive control; reinforcement learning; parameter adaptive; quadruped robot; facial skin problem; mask R-CNN; super resolution; Generative Adversarial Network (GAN); tactics for high performance; R5DOS intersection matrix; RJA-star algorithm; jump point search algorithm; path planning; sentiment analysis; machine learning; cross-validation; vectorization; feature importance; differential evolution strategy; global search optimization; optimization algorithm; search accuracy; weighted mean of vectors; n/a