crossrefComputer-Aided Civil and Infrastructure EngineeringCited by 0

Real-time multi-step prediction of tunnel boring machine parameters using a decomposition-enhanced dual-stream deep learning model

Houle Zhang, Yongxin Wu, Mao Ye, Hanzhi Yang, Yue Hou

Related papers

crossrefComputer-Aided Civil and Infrastructure Engineering2026-07-01Cited by 1

A maintenance-aware machine learning framework for network-level highway pavement condition prediction

Jin Hwan Kim, Guk Gon Song, Youngguk Seo

crossrefComputer-Aided Civil and Infrastructure Engineering2026-07-01

An explainable framework integrating machine learning and life cycle assessment for balancing performance, carbon emissions, and costs in asphalt mixtures

Meng Guo, Mengmeng Zhou, Xiuli Du, Johannes Mirwald

crossrefComputer-Aided Civil and Infrastructure Engineering2026-07-01

Iterative Image Annotation for Deep Learning-based Concrete Damage Segmentation through Human-AI Collaboration

Vahidreza Gharehbaghi, Zhao Hang, Remy Lequesne, Caroline Bennett, Jian Li

semantic_scholarComputer-Aided Civil and Infrastructure Engineering2026-08-01

Corrigendum to “Parameterized quantum circuit-enhanced graph neural networks for seismic damage prediction: Advantages under data-scarce and noisy conditions” [Computer-Aided Civil and Infrastructure Engineering 49 (2026) 100101]

Donwoo Lee, Seungjae Lee

View free PDFSource page

crossrefComputer-Aided Civil and Infrastructure Engineering2026-08-01

Transfer learning-powered physics-informed neural network for forecasting and inversion analysis of rainfall-induced landslides

Shian Cao, Lin Li, Weibing Gong