Application of artificial neural networks in construction management: Current status and future directions

Shicheng Liu, Ruidong Chang, Jian Zuo, Ronald J. Webber, Feng Xiong, Na Dong*

*Corresponding author for this work

Research output: Contribution to journalReview articleResearchpeer-review

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Abstract

Artificial neural networks (ANN) exhibit excellent performance in complex problems and have been increasingly applied in the research field of construction management (CM) over the last few decades. However, few papers draw up a systematic review to evaluate the state-of-the-art research on ANN in CM. In this paper, content analysis is performed to comprehensively analyze 112 related bibliographic records retrieved from seven selected top journals published between 2000 and 2020. The results indicate that the applications of ANN of interest in CM research have been significantly increasing since 2015. Back-propagation was the most widely used algorithm in training ANN. Integrated ANN with fuzzy logic/genetic algorithm was the most commonly employed way of addressing the CM problem. In addition, 11 application fields and 31 research topics were identified, with the primary research interests focusing on cost, performance, and safety. Lastly, challenges and future directions for ANN in CM were put forward from four main areas of input data, modeling, application fields, and emerging technologies. This paper provides a comprehensive understanding of the application of ANN in CM research and useful reference for the future.

Original languageEnglish
Article number9616
JournalApplied Sciences (Switzerland)
Volume11
Issue number20
DOIs
Publication statusPublished - 1 Oct 2021
Externally publishedYes

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