Application of Artificial Neural Networks in Construction Management: A Scientometric Review
Author(s): |
Hongyu Xu
Ruidong Chang Min Pan Huan Li Shicheng Liu Ronald J. Webber Jian Zuo Na Dong |
---|---|
Medium: | journal article |
Language(s): | English |
Published in: | Buildings, 5 July 2022, n. 7, v. 12 |
Page(s): | 952 |
DOI: | 10.3390/buildings12070952 |
Abstract: |
As a powerful artificial intelligence tool, the Artificial Neural Network (ANN) has been increasingly applied in the field of construction management (CM) during the last few decades. However, few papers have attempted to draw up a systematic commentary to appraise the state-of-the-art research on ANNs in CM except the one published in 2000. In the present study, a scientometric analysis was conducted to comprehensively analyze 112 related articles retrieved from seven selected authoritative journals published between 2000 and 2020. The analysis identified co-authorship networks, collaboration networks of countries/regions, co-occurrence networks of keywords, and timeline visualization of keywords, together with the strongest citation burst, the active research authors, countries/regions, and main research interests, as well as their evolution trends and collaborative relationships in the past 20 years. This paper finds that there is still a lack of systematic research and sufficient attention to the application of ANNs in CM. Furthermore, ANN applications still face many challenges such as data collection, cleaning and storage, the collaboration of different stakeholders, researchers and countries/regions, as well as the systematic design for the needed platforms. The findings are valuable to both the researchers and industry practitioners who are committed to ANNs in CM. |
Copyright: | © 2022 by the authors; licensee MDPI, Basel, Switzerland. |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
4.38 MB
- About this
data sheet - Reference-ID
10688566 - Published on:
13/08/2022 - Last updated on:
10/11/2022