Название: Artificial Intelligence Techniques in Mathematical Modeling and Optimization
Автор: Mukesh Kumar Awasthi, Sanoj Kumar, Deepika Saini
Издательство: CRC Press
Серия: Intelligent Data-Driven Systems and Artificial Intelligence
Год: 2026
Страниц: 346
Язык: английский
Формат: pdf (true), epub
Размер: 28.7 MB
Artificial Intelligence Techniques in Mathematical Modeling and Optimization offers a dynamic and comprehensive examination of the intersection between AI and mathematical modeling. This edited volume brings together innovative research exploring how AI-driven methods revolutionize traditional approaches to complex optimization problems, enabling enhanced performance, interpretability, and real-world applicability across diverse domains. Covering foundational and advanced topics, the book introduces readers to Machine Learning, Deep Learning, and Reinforcement Learning as critical tools for modeling high-dimensional, nonlinear, and stochastic systems. Chapters delve into essential aspects like data pre-processing, feature engineering, neural network architectures, Swarm Intelligence, quantum optimization, and multi-objective decision-making. This volume is an essential resource for graduate students, researchers, and practitioners in applied mathematics, Computer Science, engineering, and data-driven optimization, offering the theoretical depth and application-driven clarity needed to tackle modern scientific and engineering challenges through AI-powered modeling and decision systems.