Comparing natural language processing (NLP) applications in construction and computer science using preferred reporting items for systematic reviews (PRISMA)
Despite the increasing use of natural language processing (NLP) in the construction
domain, no systematic comparison has been conducted between NLP applications in …
domain, no systematic comparison has been conducted between NLP applications in …
A comprehensive review of bio-inspired optimization algorithms including applications in microelectronics and nanophotonics
The application of artificial intelligence in everyday life is becoming all-pervasive and
unavoidable. Within that vast field, a special place belongs to biomimetic/bio-inspired …
unavoidable. Within that vast field, a special place belongs to biomimetic/bio-inspired …
BIM-supported automatic energy performance analysis for green building design using explainable machine learning and multi-objective optimization
Y Shen, Y Pan - Applied Energy, 2023 - Elsevier
Supported by the combination of the advanced BIM technique with intelligent algorithms, this
paper develops a systematic framework using explainable machine learning and multi …
paper develops a systematic framework using explainable machine learning and multi …
Data-driven multi-step prediction and analysis of monthly rainfall using explainable deep learning
Monthly rainfall prediction is a crucial topic for the management of water resources and
prevention of hydrological disasters. To make a multi-step monthly rainfall prediction and …
prevention of hydrological disasters. To make a multi-step monthly rainfall prediction and …
Multi-objective robust optimization for enhanced safety in large-diameter tunnel construction with interactive and explainable AI
Robust optimization is an ideal solution for enhancing safety in tunnel construction in the
presence of unpredictable soil conditions, especially in large-diameter tunnel construction …
presence of unpredictable soil conditions, especially in large-diameter tunnel construction …
Time series prediction of tunnel boring machine (TBM) performance during excavation using causal explainable artificial intelligence (CX-AI)
K Wang, L Zhang, X Fu - Automation In Construction, 2023 - Elsevier
Since early warning is significant to ensure high-quality tunneling boring machine (TBM)
construction, a real-time prediction method based on TBM data is proposed. To solve the …
construction, a real-time prediction method based on TBM data is proposed. To solve the …
A causal-temporal graphic convolutional network (CT-GCN) approach for TBM load prediction in tunnel excavation
This research proposes a novel deep learning approach named causal-temporal graphic
convolutional network (CT-GCN) which aims to provide accurate predictions on tunnel …
convolutional network (CT-GCN) which aims to provide accurate predictions on tunnel …
Data-driven multi-step robust prediction of TBM attitude using a hybrid deep learning approach
K Wang, X Wu, L Zhang, X Song - Advanced Engineering Informatics, 2023 - Elsevier
A robust multi-step TBM attitude prediction approach named convolutional gated-recurrent-
unit neural network (C-GRU) is proposed in this research and the random balance design …
unit neural network (C-GRU) is proposed in this research and the random balance design …
[HTML][HTML] Artificial Intelligence and Sustainable Development Goals: Systematic Literature Review of the Construction Industry
While acknowledging the widespread recognition of artificial intelligence's (AI) potential in
achieving sustainable development, there remains a notable deficiency and thorough …
achieving sustainable development, there remains a notable deficiency and thorough …
Flood risk assessment and mitigation for metro stations: An evidential-reasoning-based optimality approach considering uncertainty of subjective parameters
This study presents an optimality approach based on evidential reasoning for flood risk
assessment and mitigation of metro stations. To address the uncertainty of subjective …
assessment and mitigation of metro stations. To address the uncertainty of subjective …