Predicting the performance of design-bid-build projects: a neural-network based approach

Several studies had shown that many project managers are facing difficulties in predicting the performance of Design- bid-build (DBB) projects. This is due to the fact that there are many factors that affect DBB project success. This research is carried out to identify these factors. In addition, a...

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Main Author:	Tan, Caren Cai Loon
Format:	Thesis
Language:	English
Published:	2006
Subjects:	TA Engineering (General) Civil engineering (General)
Online Access:	http://eprints.utm.my/id/eprint/3837/1/TanCaiLoonMFKA2006.pdf
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id	my-utm-ep.3837
record_format	uketd_dc
spelling	my-utm-ep.38372018-01-10T08:31:40Z Predicting the performance of design-bid-build projects: a neural-network based approach 2006-04 Tan, Caren Cai Loon TA Engineering (General). Civil engineering (General) Several studies had shown that many project managers are facing difficulties in predicting the performance of Design- bid-build (DBB) projects. This is due to the fact that there are many factors that affect DBB project success. This research is carried out to identify these factors. In addition, a model to predict the performance of DBB project was developed based on time. Through literature research, a total of forty-four factors that affect DBB project success had been established. The degree of importance for these factors had been determined through questionnaire survey. Eight out of forty-four factors that affecting project performance were found to be the most important factors ITom the viewpoint of project managers and contractors in the Malaysia construction industry. The outcome of the survey formed a basis for the model development. Artificial neural network (ANN) technique is used to construct the models to predict construction project performance based on time. The best performance model was the multiplayer back-propagation neural network model, which consisted of eight input nodes, five hidden nodes and three output nodes. These models were tested by using data ITom nine new projects. The results indicated that the developed model can give a good prediction. In this study, it was concluded that the ANN prediction model can be an efficient tool for predicting the performance ofDBB project from the time aspect. 2006-04 Thesis http://eprints.utm.my/id/eprint/3837/ http://eprints.utm.my/id/eprint/3837/1/TanCaiLoonMFKA2006.pdf application/pdf en public masters Universiti Teknologi Malaysia Faculty of Civil Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TA Engineering (General) Civil engineering (General)
spellingShingle	TA Engineering (General) Civil engineering (General) Tan, Caren Cai Loon Predicting the performance of design-bid-build projects: a neural-network based approach
description	Several studies had shown that many project managers are facing difficulties in predicting the performance of Design- bid-build (DBB) projects. This is due to the fact that there are many factors that affect DBB project success. This research is carried out to identify these factors. In addition, a model to predict the performance of DBB project was developed based on time. Through literature research, a total of forty-four factors that affect DBB project success had been established. The degree of importance for these factors had been determined through questionnaire survey. Eight out of forty-four factors that affecting project performance were found to be the most important factors ITom the viewpoint of project managers and contractors in the Malaysia construction industry. The outcome of the survey formed a basis for the model development. Artificial neural network (ANN) technique is used to construct the models to predict construction project performance based on time. The best performance model was the multiplayer back-propagation neural network model, which consisted of eight input nodes, five hidden nodes and three output nodes. These models were tested by using data ITom nine new projects. The results indicated that the developed model can give a good prediction. In this study, it was concluded that the ANN prediction model can be an efficient tool for predicting the performance ofDBB project from the time aspect.
format	Thesis
qualification_level	Master's degree
author	Tan, Caren Cai Loon
author_facet	Tan, Caren Cai Loon
author_sort	Tan, Caren Cai Loon
title	Predicting the performance of design-bid-build projects: a neural-network based approach
title_short	Predicting the performance of design-bid-build projects: a neural-network based approach
title_full	Predicting the performance of design-bid-build projects: a neural-network based approach
title_fullStr	Predicting the performance of design-bid-build projects: a neural-network based approach
title_full_unstemmed	Predicting the performance of design-bid-build projects: a neural-network based approach
title_sort	predicting the performance of design-bid-build projects: a neural-network based approach
granting_institution	Universiti Teknologi Malaysia
granting_department	Faculty of Civil Engineering
publishDate	2006
url	http://eprints.utm.my/id/eprint/3837/1/TanCaiLoonMFKA2006.pdf
_version_	1747814474890346496

Predicting the performance of design-bid-build projects: a neural-network based approach

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