Dharma, IGB. Sila and Putera, IGA. Adnyana and Ardana, Putu Doddy Heka (2011) ARTIFICIAL NEURAL NETWORKS UNTUK PEMODELAN CURAH HUJAN-LIMPASAN PADA DAERAH ALIRAN SUNGAI (DAS) DI PULAU BALI. Jurnal Bumi Lestari, 11 (1). pp. 9-22.
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Abstract
Rainfall-runoff transformation of a watershed is one of the most complex hydrology phenomena, non- linier process, time-varying and spatial distribution. Rainfall-runoff relationships play an important role in water resource management planning and therefore, different types of models with various degrees of complexity have been developed for this purpose. The application of Artificial Neural Networks (ANNs) on rainfall-runoff modelling has studied more extensively in order to appreciate and fulfil the potential of this modelling approach. Back propagation method has used in this study for modelling monthly rainfall for small size catchments areas. ANN model developed in this study successfully predicts relationship for rainfall-runoff with 90.14% accuracy on learning process and 72.41% accuracy on testing process. These results show that ANN provides a systematic approach for runoff estimation and represents improvement in prediction accuracy. Key words: artificial neural networks, rainfall-runoff modelling, back propagation method
Item Type: | Article |
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Subjects: | T Technology > TA Engineering (General). Civil engineering (General) |
Divisions: | Fakultas Sains dan Teknologi > Prodi Teknik Sipil |
Depositing User: | ms vionita pertiwi |
Date Deposited: | 06 Apr 2021 12:26 |
Last Modified: | 06 Apr 2021 12:26 |
URI: | http://repo.unr.ac.id/id/eprint/589 |
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