Arbain, Siti Hajar and Wibowo, Antoni (2012) Time series methods for water level forecasting of Dungun River in Terengganu Malaysia. International Journal of Engineering Science and Technology, 4 (4). pp. 1803-1811. ISSN 0975-5462
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Official URL: http://www.ijest.info/docs/IJEST12-04-04-280.pdf
Abstract
Due to climate change and global warming, the possibility of floods may increase to occur in Malaysia. Water level forecasting is an important for the water catchment management in particular for flood warning systems. The aim of this study is to predict water level with input variables monthly rainfall and rate of evaporation taken from the same catchment at Dungun River, Terengganu-Malaysia, using ARIMA and Artificial Neural Network (ANN). The process of pre-processing data has been made to the original rainfall data since they contain imperfect characteristics data. Our experiments show that the ANN with cleansing rainfall data gives better performance than ARIMA and ANN without cleansing data.
Item Type: | Article |
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Uncontrolled Keywords: | time series, ARIMA, SARIMA, neural network, Dungun River, Terengganu, water level, rainfall, flooding |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Computer Science and Information System |
ID Code: | 30461 |
Deposited By: | Yanti Mohd Shah |
Deposited On: | 23 Apr 2013 02:21 |
Last Modified: | 23 Jul 2019 09:01 |
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