Application of Machine Learning and Optimization Methods in Engineering Mathematics
Materialtyp:
ArtikelUtgivningsinformation: CH MDPI - Multidisciplinary Digital Publishing Institute 2025Beskrivning: 1 electronic resource (196 p.)Innehållstyp: - text
- computer
- online resource
- 978-3-7258-4745-7
- BEM
- Cox–Ingersoll–Ross model
- HARA utility
- Heston model
- Interval Valued Pythagorean Fuzzy Analytic Hierarchy Process
- Open Data Barcelona
- PMSM drives
- Pythagorean Fuzzy Analytic Hierarchy Process
- Smart City
- artificial intelligence
- artificial neural network
- big data mining
- buildings
- capped L1-norm
- complex analysis
- crumb rubber
- data standardization
- deep learning
- electric vehicles
- estimations
- fisher regularization
- fly ash
- fuzzy PID control
- join operation
- lagged cross-correlations
- mechanical characteristics
- nano silica
- neural network
- optical filter
- potential theory
- remora optimization algorithm
- robustness
- semantic data enrichment
- smartness
- spatial data distribution
- time series data
- twin extreme learning machine
- variance premium principle
- within-class scatter
- yield rate
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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.
Creative Commons Licence cc by cc https://creativecommons.org/licenses/by/4.0/
eng
Freely available e-book