文章基本信息

标题：An Artificial neural networks (ANN) model for evaluating construction project performance based on coordination factors
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作者：Wesam Salah Alaloul ; Mohd Shahir Liew ; Noor Amila Wan Zawawi 等
期刊名称：Cogent Engineering
电子版ISSN：2331-1916
出版年度：2018
卷号：5
期号：1
页码：1-18
DOI：10.1080/23311916.2018.1507657
出版社：Taylor and Francis Ltd
摘要：Construction projects are delivered in a multidisciplinary environment, which need continues coordination. The aim of this paper is to develop an ANN model to evaluate the influence of coordination factors on construction projects performance. For this purpose, the most effective 16 coordination factors impacting the construction projects performance have been identified. After that, through a questionnaire survey, the extent of coordination factors application and the corresponding project’s performance were collected. Three multilayer feed-forward networks with Back-Propagation and Elman-Propagation algorithms were adopted to train, validate, and test the cost, time and quality, as performance evaluation indicators. Consequently, the training process continues unit it reaches the pre-defined error or up to 1000 epochs. The results of Mean Square Error (MSE) confirmed the accuracy of the networks with an average value of 0.0231. Furthermore, the determination coefficient (R2) for the three networks of cost, time, and quality were obtained to be 0.77, 0.76 and 0.75, respectively..
关键词：artificial neural networks; performance evaluation; construction projects