Delay and cost overrun of palm oil refinery construction projects: Artificial neural network (ann) model
In spite of the development and innovation in the construction technologies, still, delay and cost overrun are the most crucial challenge of the construction industry in both developed and the developing countries. This research aims to develop a prediction model using Artificial Neural Network (ANN...
| Main Authors: | Abdullah, M.S., Alaloul, W.S., Liew, M.S., Musarat, M.A. |
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| Format: | Article |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.30313 / |
| Published: |
Springer Science and Business Media Deutschland GmbH
2021
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| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100735960&doi=10.1007%2f978-981-33-6311-3_67&partnerID=40&md5=1dfa794bfa02c9504bc26e05aac6cfc6 http://eprints.utp.edu.my/30313/ |
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| Summary: |
In spite of the development and innovation in the construction technologies, still, delay and cost overrun are the most crucial challenge of the construction industry in both developed and the developing countries. This research aims to develop a prediction model using Artificial Neural Network (ANN). The prediction model consists of the most impactful causes of delays and costs overruns during the construction of Palm Oil Refinery projects which were ranked based on importance, severity and frequency. A series of 39 questions were developed from the questionnaire survey causing delays and cost overruns during construction of palm oil refinery projects. Artificial Bee Colony (ABC) algorithm was used to develop the prediction model for palm oil construction projects. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021. |
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