A neural model for predicting the time performance of traditional general contract (TGC) project
Several studies had shown that many project managers are facing difficulties in predicting the time performance of Traditional General Contract (TGC) projects because there are many factors that affect TGC project success. This study presents the development of a model that can be used to predict th...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Faculty of Civil Engineering, Universiti Teknologi Malaysia
2008
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| Online Access: | http://eprints.utm.my/8188/ http://eprints.utm.my/8188/1/RosliMohamadZin2008-ANeuralNetworkModelforPredicting.pdf |
| _version_ | 1848891636064452608 |
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| author | Mohamad Zin, Rosli Tan, Caren Cai Loon |
| author_facet | Mohamad Zin, Rosli Tan, Caren Cai Loon |
| author_sort | Mohamad Zin, Rosli |
| building | UTeM Institutional Repository |
| collection | Online Access |
| description | Several studies had shown that many project managers are facing difficulties in predicting the time performance of Traditional General Contract (TGC) projects because there are many factors that affect TGC project success. This study presents the development of a model that can be used to predict the time performance of TGC project. Through literature research, fortyfour success factors affecting TGC project have been established. The degree of importance for these factors was determined through questionnaire survey. The outcome of the survey formed a basis for the development of the time performance prediction model using Artificial Neural Network technique. The best model was found to be a multi-layer back-propagation neural network consists of eight input nodes, five hidden nodes and three output nodes. The model was tested by using data from nine new projects. The results show that the mean error for this prediction model is relatively low. The developed model enables all parties involved in TGC projects to predict and ensure that their project is on time |
| first_indexed | 2025-11-15T21:01:07Z |
| format | Article |
| id | utm-8188 |
| institution | Universiti Teknologi Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T21:01:07Z |
| publishDate | 2008 |
| publisher | Faculty of Civil Engineering, Universiti Teknologi Malaysia |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utm-81882014-04-16T04:35:20Z http://eprints.utm.my/8188/ A neural model for predicting the time performance of traditional general contract (TGC) project Mohamad Zin, Rosli Tan, Caren Cai Loon TA Engineering (General). Civil engineering (General) Several studies had shown that many project managers are facing difficulties in predicting the time performance of Traditional General Contract (TGC) projects because there are many factors that affect TGC project success. This study presents the development of a model that can be used to predict the time performance of TGC project. Through literature research, fortyfour success factors affecting TGC project have been established. The degree of importance for these factors was determined through questionnaire survey. The outcome of the survey formed a basis for the development of the time performance prediction model using Artificial Neural Network technique. The best model was found to be a multi-layer back-propagation neural network consists of eight input nodes, five hidden nodes and three output nodes. The model was tested by using data from nine new projects. The results show that the mean error for this prediction model is relatively low. The developed model enables all parties involved in TGC projects to predict and ensure that their project is on time Faculty of Civil Engineering, Universiti Teknologi Malaysia 2008 Article PeerReviewed application/pdf en http://eprints.utm.my/8188/1/RosliMohamadZin2008-ANeuralNetworkModelforPredicting.pdf Mohamad Zin, Rosli and Tan, Caren Cai Loon (2008) A neural model for predicting the time performance of traditional general contract (TGC) project. Malaysian Journal of Civil Engineering, 20 (1). pp. 26-37. ISSN 1823-7843 |
| spellingShingle | TA Engineering (General). Civil engineering (General) Mohamad Zin, Rosli Tan, Caren Cai Loon A neural model for predicting the time performance of traditional general contract (TGC) project |
| title | A neural model for predicting the time performance of traditional general contract (TGC) project
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| title_full | A neural model for predicting the time performance of traditional general contract (TGC) project
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| title_fullStr | A neural model for predicting the time performance of traditional general contract (TGC) project
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| title_full_unstemmed | A neural model for predicting the time performance of traditional general contract (TGC) project
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| title_short | A neural model for predicting the time performance of traditional general contract (TGC) project
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| title_sort | neural model for predicting the time performance of traditional general contract (tgc) project |
| topic | TA Engineering (General). Civil engineering (General) |
| url | http://eprints.utm.my/8188/ http://eprints.utm.my/8188/1/RosliMohamadZin2008-ANeuralNetworkModelforPredicting.pdf |