TY  - JOUR
AV  - none
SP  - 580
TI  - Delay and cost overrun of palm oil refinery construction projects: Artificial neural network (ann) model
N1  - cited By 2; Conference of 6th International Conference on Civil, Offshore and Environmental Engineering, ICCOEE 2020 ; Conference Date: 13 July 2021 Through 15 July 2021; Conference Code:253689
SN  - 23662557
PB  - Springer Science and Business Media Deutschland GmbH
EP  - 589
KW  - Construction industry; Costs; Developing countries; Forecasting; Offshore oil well production; Optimization; Palm oil; Petroleum refineries; Predictive analytics; Surveys
KW  -  Artificial bee colony algorithms (ABC); Artificial neural network models; Causes of delays; Construction projects; Construction technologies; Oil refinery construction projects; Prediction model; Questionnaire surveys
KW  -  Neural networks
ID  - scholars15906
N2  - 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.
Y1  - 2021///
VL  - 132
UR  - 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
JF  - Lecture Notes in Civil Engineering
A1  - Abdullah, M.S.
A1  - Alaloul, W.S.
A1  - Liew, M.S.
A1  - Musarat, M.A.
ER  -