Citation
Hafizan Juahir, . and Sharifuddin M. Zain, . and Zainal Ahmad, . and M. Nazari Jaafar, . (2004) An application of second order neural network back propagation method in modeling river discharge at Sungai Langat Malaysia. [Proceedings Paper]
Abstract
River discharge influences many important processes in aquatic ecosystem. In this work artificial neural network ANN is applied as a model to estimate the daily discharge of the Langat River. The actual values of discharge are compared to the values predicted by classical multiple layer perceptron MLP ANN namely the Levenberg-Marquardt Backpropagation Neural Network LMBPNN model via statistical tests. It is seen that the ANN simulates the actual values of water discharge time series.
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Abstract
River discharge influences many important processes in aquatic ecosystem. In this work artificial neural network ANN is applied as a model to estimate the daily discharge of the Langat River. The actual values of discharge are compared to the values predicted by classical multiple layer perceptron MLP ANN namely the Levenberg-Marquardt Backpropagation Neural Network LMBPNN model via statistical tests. It is seen that the ANN simulates the actual values of water discharge time series.
Additional Metadata
| Item Type: | Proceedings Paper |
|---|---|
| Additional Information: | Summary En |
| AGROVOC Term: | RIVERS |
| AGROVOC Term: | WATER QUALITY |
| AGROVOC Term: | GEOGRAPHICAL INFORMATION SYSTEMS |
| AGROVOC Term: | LAND USE |
| AGROVOC Term: | SPATIAL DISTRIBUTION |
| AGROVOC Term: | WATER RESOURCES |
| AGROVOC Term: | WATER MANAGEMENT |
| AGROVOC Term: | MALAYSIA |
| Geographical Term: | MALAYSIA |
| Depositing User: | Ms. Norfaezah Khomsan |
| Last Modified: | 24 Apr 2025 05:27 |
| URI: | http://webagris.upm.edu.my/id/eprint/16082 |
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