Generative ai in the construction industry: Opportunities & challenges
In the last decade, despite rapid advancements in artificial intelligence (AI) transforming
many industry practices, construction largely lags in adoption. Recently, the emergence and …
many industry practices, construction largely lags in adoption. Recently, the emergence and …
Predicting mine water inrush accidents based on water level anomalies of borehole groups using long short-term memory and isolation forest
H Yin, Q Wu, S Yin, S Dong, Z Dai, MR Soltanian - Journal of hydrology, 2023 - Elsevier
Water level variation of explorational boreholes in mining sites is one of the most direct
representations of water inrush risk. Despite recent efforts on mine water inrush accident …
representations of water inrush risk. Despite recent efforts on mine water inrush accident …
Comparison of neural network, Gaussian regression, support vector machine, long short-term memory, multi-gene genetic programming, and M5 Trees methods for …
In this study, it was investigated that how machine learning (ML) methods show performance
in different problems having different characteristics. Six ML approaches including Artificial …
in different problems having different characteristics. Six ML approaches including Artificial …
Opportunities and challenges of generative ai in construction industry: Focusing on adoption of text-based models
In the last decade, despite rapid advancements in artificial intelligence (AI) transforming
many industry practices, construction largely lags in adoption. Recently, the emergence and …
many industry practices, construction largely lags in adoption. Recently, the emergence and …
Random forest algorithm and support vector machine for nondestructive assessment of mass moisture content of brick walls in historic buildings
A Hoła, S Czarnecki - Automation in Construction, 2023 - Elsevier
The article presents the results of experimental research and numerical analyses, and also
shows the usefulness of the random forest algorithm and the support vector machine for the …
shows the usefulness of the random forest algorithm and the support vector machine for the …
A generative adversarial learning strategy for spatial inspection of compaction quality
Reliable prediction methods play a crucial role in enhancing the compaction quality and
implementing the intelligent compaction (IC). The predictive performance of contemporary …
implementing the intelligent compaction (IC). The predictive performance of contemporary …
Transfer-learning and texture features for recognition of the conditions of construction materials with small data sets
Construction materials undergo appearance and textural changes during the construction
process. Accurate recognition of these changes is critical for effectively understanding the …
process. Accurate recognition of these changes is critical for effectively understanding the …
Using machine learning to improve cost and duration prediction accuracy in green building projects
A Darko, I Glushakova, EB Boateng… - Journal of Construction …, 2023 - ascelibrary.org
A major source of risk in green building projects (GBPs) is inaccurate human prediction of
the final project cost and duration, which in turn results in cost and schedule overruns (ie …
the final project cost and duration, which in turn results in cost and schedule overruns (ie …
Process-oriented guidelines for systematic improvement of supervised learning research in construction engineering
A limited assessment of the development process and various stages of machine learning
(ML) based solutions for construction engineering (CE) problems are available in the …
(ML) based solutions for construction engineering (CE) problems are available in the …
Forecasting failure load of Sandstone under different Freezing-Thawing cycles using Gaussian process regression method and grey wolf optimization algorithm
The stability analysis of rock is an important basis to ensure the safe exploitation of
underground resources and the reliable operation of space engineering. Failure load is one …
underground resources and the reliable operation of space engineering. Failure load is one …