Reprint

Application of Machine Learning and Optimization Methods in Engineering Mathematics

Edited by
August 2025
196 pages
  • ISBN 978-3-7258-4745-7 (Hardback)
  • ISBN 978-3-7258-4746-4 (PDF)
https://doi.org/10.3390/books978-3-7258-4746-4 (registering)

Print copies available soon

This is a Reprint of the Special Issue Application of Machine Learning and Optimization Methods in Engineering Mathematics that was published in

Computer Science & Mathematics
Engineering
Summary

The articles published in this Special Issue collectively demonstrate the significant impact of mathematical modeling, machine learning, and optimization techniques in solving complex engineering problems. They cover a broad spectrum of applications, from manufacturing process control and electric vehicle motor temperature prediction to the financial optimization and structural analysis of dams.

The integration of advanced algorithms, such as fuzzy control, deep learning, and stochastic modeling, with classical analytical methods highlights the evolving landscape of engineering mathematics. These studies not only improve predictive accuracy and operational efficiency but also contribute to sustainable and intelligent engineering solutions.

Overall, this Special Issue showcases the critical role of interdisciplinary mathematical approaches in advancing engineering research and practice.

Related Books

May 2024

Applied Mathematics and Machine Learning

Computer Science & Mathematics
April 2022

Applications of Mathematical Models in Engineering

Computer Science & Mathematics
...
October 2020

Mathematics and Engineering

Engineering

The recommendations have been generated using an AI system.