State-of-the-art on research and applications of machine learning in the building life cycle

T Hong, Z Wang, X Luo, W Zhang - Energy and Buildings, 2020 - Elsevier
Fueled by big data, powerful and affordable computing resources, and advanced algorithms,
machine learning has been explored and applied to buildings research for the past decades …

Artificial intelligence in civil engineering

P Lu, S Chen, Y Zheng - Mathematical Problems in …, 2012 - Wiley Online Library
Artificial intelligence is a branch of computer science, involved in the research, design, and
application of intelligent computer. Traditional methods for modeling and optimizing complex …

Application of machine learning to construction injury prediction

AJP Tixier, MR Hallowell, B Rajagopalan… - Automation in …, 2016 - Elsevier
The needs to ground construction safety-related decisions under uncertainty on knowledge
extracted from objective, empirical data are pressing. Although construction research has …

A deep learning approach in predicting products' sentiment ratings: a comparative analysis

V Balakrishnan, Z Shi, CL Law, R Lim, LL Teh… - The Journal of …, 2022 - Springer
We present a benchmark comparison of several deep learning models including
Convolutional Neural Networks, Recurrent Neural Network and Bi-directional Long Short …

Assessing the accuracy of ChatGPT use for risk management in construction projects

H Aladağ - Sustainability, 2023 - mdpi.com
Artificial Intelligence (AI) is considered promising digital technology that has important
opportunities for enhancing project oversight and delivering improved decision-making in …

AI-based prediction of independent construction safety outcomes from universal attributes

H Baker, MR Hallowell, AJP Tixier - Automation in Construction, 2020 - Elsevier
This paper significantly improves on, and finishes to validate, an approach proposed in
previous research in which safety outcomes were predicted from attributes with machine …

Project cost risk analysis: A Bayesian networks approach for modeling dependencies between cost items

V Khodakarami, A Abdi - International Journal of Project Management, 2014 - Elsevier
Uncertainty of cost items is an important aspect of complex projects. Cost uncertainty
analysis aims to help decision makers to understand and model different factors affecting …

Support vector machine regression for project control forecasting

M Wauters, M Vanhoucke - Automation in Construction, 2014 - Elsevier
Abstract Support Vector Machines are methods that stem from Artificial Intelligence and
attempt to learn the relation between data inputs and one or multiple output values …

A comparative study of Artificial Intelligence methods for project duration forecasting

M Wauters, M Vanhoucke - Expert systems with applications, 2016 - Elsevier
This paper presents five Artificial Intelligence (AI) methods to predict the final duration of a
project. A methodology that involves Monte Carlo simulation, Principal Component Analysis …

High-performance concrete compressive strength prediction using time-weighted evolutionary fuzzy support vector machines inference model

MY Cheng, JS Chou, AFV Roy, YW Wu - Automation in Construction, 2012 - Elsevier
The major different between High Performance Concrete (HPC) and conventional concrete
is essentially the use of mineral and chemical admixture. These two admixtures made HPC …