The application of machine learning and deep learning on demand forecasting across time-critical industries: A systematic review

A market-rule-informed neural network for efficient imbalance electricity price forecasting

Runyao Yu, Julia Lin, Derek W. Bunn, Jochen Stiasny, Wentao Wang, Yuehua Chen, et al.

Accurate and efficient imbalance electricity price forecasting is critical for industrial energy trading in balancing markets. Battery assets and automated trading systems require forecasts with limited computational resources and near-real-time speed. The imbalance price is form…Read more

Physics-informed data augmentation and explainable machine learning for parametric design of stainless steel columns

Wenkang Zuo, Yuner Huang, Man-Tai Chen, Ben Young

Mixed reality and machine learning-guided cable robot framework (MMCR) for real-time prefabricated construction automation

Qi Wang, Maowei Jiang, Ting Yu, Yusong Hu, Zhiyong Dong, Hongfei Ai, et al.

Porosity prediction in laser beam welding with a multimodal physics-informed machine learning framework

Xiangmeng Meng, Marcel Bachmann, Fan Yang, Michael Rethmeier

Also available via: Advanced Engineering Informatics

Multimodal machine learning in the AEC industry: a lifecycle-aligned review of strategies, challenges, and informatics frameworks

Abdulkadir Hassan Ahmed, Osama Mohsen

Also available via: Advanced Engineering Informatics

AutoSurrogate: An LLM-driven multi-agent framework for autonomous construction of deep learning surrogate models in subsurface flow

Jiale Liu, Nanzhe Wang