Application of Machine Learning and Optimization Methods in Engineering Mathematics
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 v...
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| Autors principals: | , |
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| Format: | Online |
| Idioma: | anglès |
| Publicat: |
MDPI - Multidisciplinary Digital Publishing Institute
2026
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| Matèries: | |
| Accés en línia: | https://directory.doabooks.org/handle/20.500.12854/170584 |
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| Sumari: | 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. |
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