Intelligent Predictive Systems : AI and Machine Learning in Engineering (Emerging Trends in Mechatronics)

Azizi, Aydin (EDT)/ Jahed Armaghani, Danial (EDT)/ Mirrashid, Masoomeh (EDT)

Springer Verlag, Singapore（2026/05発売）

• 製本 Hardcover:ハードカバー版／ページ数 261 p.
• 言語 ENG
• 商品コード 9789819577651

Full Description

The introduction of AI and ML technologies has brought new changes to the engineering profession. This book presents the theory and practical solutions backed with real results. It also explains in detail the uses of Machine Learning methods, Gene Expression Programming, Extreme Gradient Boosting, and Deep Neural Networks in predicting parameters that are critical in understanding soil behavior, foundation settlements, material behavior, resource consumption, and beyond. One focal point is the shift from opaque models to transparent, accountable AI. The integration of AI methods is elucidated to clarify decisions made by predictive models and instill trust in the predictive systems. Additionally, the book addresses the issue of sustainability by demonstrating how AI can refine the utilization of industrial by-products such as fly ash and marble slurry in the construction sector and improve the efficiency of public transportation systems.

Contents

Machine Learning for Sustainable Concrete Predictive Approaches Using Industrial Waste Materials.- Interpretable Machine Learning for Public Bus Service Efficiency A SHAP Driven Framework for Operational Analytics.- Smart Modeling Approaches for Foundation Settlement Forecasting A Comprehensive Review 2015 to 2025.- Computational Intelligence Approaches to Ground Settlement Prediction in Tunneling A Review of Recent Advances.- A Machine Learning Approach to California Bearing Ratio Prediction Evaluation of GEP and Ridge Regression.