Azman, Azid and Mohd Khairul Amri, Kamarudin and Mohd Ekhwan, Toriman (2015) Flood Risk Pattern Recognition Using Integrated Chemometric Method and Artificial Neural Network: A Case Study in the Johor River Basin. Jurnal Teknologi, 74 (1). pp. 165-170. ISSN 2180–3722
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Abstract
Flood is a major problem in Johor river basin, which normally happened during monsoon season. However, in this study, it shows that rainfall did not have a strong relationship for the changes of water level compared to suspended solid and stream flow, where both variables have p-values of <0.0001 and these variables also became the main factors in contributing to the flood occurrence based on Factor Analysis result. Time Series Analysis was being carried out and based on Statistical Process Control, the limitation has been set up for mitigation in controlling flood. All data beyond the Upper Control Limit was predicted to have High Risk to face flood and Emergency Response Plan should be implemented to prevent complication and destruction because of flood. The prediction for the risk level was carried out using the application of Artificial Neural Network (ANN), where the accuracy of prediction was very high, with the result of 96% for the level of accuracy in the prediction of risk class.
Item Type: | Article |
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Uncontrolled Keywords: | Flood; monsoon; factor analysis; time series analysis; statistical process control; artificial neural network |
Subjects: | T Technology > TA Engineering (General). Civil engineering (General) |
Depositing User: | Syahmi Manaf |
Date Deposited: | 13 Sep 2022 04:53 |
Last Modified: | 13 Sep 2022 04:53 |
URI: | http://eprints.unisza.edu.my/id/eprint/6033 |
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