Artificial Neural Network Model For Rainfall-Runoff Relationship
The modelling of hydraulic and hydrological processes is important in view of the many uses of water resources such as hydropower generation, irrigation, water supply, and flood control. There are many previous works using the artificial neural network (ANN) method for modelling various complex non-...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Penerbit UTM Press
2002
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| Online Access: | http://eprints.utm.my/1408/1/JT37B1.pdf |
| _version_ | 1825909065111306240 |
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| author | Harun, Sobri Ahmat Nor, Nor Irwan Mohd. Kassim, Amir Hashim |
| author_facet | Harun, Sobri Ahmat Nor, Nor Irwan Mohd. Kassim, Amir Hashim |
| author_sort | Harun, Sobri |
| collection | ePrints |
| description | The modelling of hydraulic and hydrological processes is important in view of the many uses of water resources such as hydropower generation, irrigation, water supply, and flood control. There are many previous works using the artificial neural network (ANN) method for modelling various complex non-linear relationships of hydrologic processes. The ANN is well known as a flexible mathematical structure and has the ability to generalize patterns in imprecise or noisy and ambiguous input and output data sets. The study area is Sungai Lui catchment (Selangor, Malaysia). This paper presents the proposed ANN model for prediction of daily runoff using the rainfall as input nodes. The method for selection of input nodes by [10] and [5] is applied. Further, the results are compared between ANN and HEC-HMS model. It has been found that the ANN models show a good generalization of rainfall-runoff relationship and is better than HEC-HMS model. |
| first_indexed | 2024-03-05T17:56:35Z |
| format | Article |
| id | utm.eprints-1408 |
| institution | Universiti Teknologi Malaysia - ePrints |
| language | English |
| last_indexed | 2024-03-05T17:56:35Z |
| publishDate | 2002 |
| publisher | Penerbit UTM Press |
| record_format | dspace |
| spelling | utm.eprints-14082017-11-01T04:17:42Z http://eprints.utm.my/1408/ Artificial Neural Network Model For Rainfall-Runoff Relationship Harun, Sobri Ahmat Nor, Nor Irwan Mohd. Kassim, Amir Hashim TA Engineering (General). Civil engineering (General) The modelling of hydraulic and hydrological processes is important in view of the many uses of water resources such as hydropower generation, irrigation, water supply, and flood control. There are many previous works using the artificial neural network (ANN) method for modelling various complex non-linear relationships of hydrologic processes. The ANN is well known as a flexible mathematical structure and has the ability to generalize patterns in imprecise or noisy and ambiguous input and output data sets. The study area is Sungai Lui catchment (Selangor, Malaysia). This paper presents the proposed ANN model for prediction of daily runoff using the rainfall as input nodes. The method for selection of input nodes by [10] and [5] is applied. Further, the results are compared between ANN and HEC-HMS model. It has been found that the ANN models show a good generalization of rainfall-runoff relationship and is better than HEC-HMS model. Penerbit UTM Press 2002-12 Article PeerReviewed application/pdf en http://eprints.utm.my/1408/1/JT37B1.pdf Harun, Sobri and Ahmat Nor, Nor Irwan and Mohd. Kassim, Amir Hashim (2002) Artificial Neural Network Model For Rainfall-Runoff Relationship. Jurnal Teknologi B (37B). pp. 1-12. ISSN 0127-9696 http://www.penerbit.utm.my/onlinejournal/37/B/JT37B1.pdf |
| spellingShingle | TA Engineering (General). Civil engineering (General) Harun, Sobri Ahmat Nor, Nor Irwan Mohd. Kassim, Amir Hashim Artificial Neural Network Model For Rainfall-Runoff Relationship |
| title | Artificial Neural Network Model For Rainfall-Runoff Relationship |
| title_full | Artificial Neural Network Model For Rainfall-Runoff Relationship |
| title_fullStr | Artificial Neural Network Model For Rainfall-Runoff Relationship |
| title_full_unstemmed | Artificial Neural Network Model For Rainfall-Runoff Relationship |
| title_short | Artificial Neural Network Model For Rainfall-Runoff Relationship |
| title_sort | artificial neural network model for rainfall runoff relationship |
| topic | TA Engineering (General). Civil engineering (General) |
| url | http://eprints.utm.my/1408/1/JT37B1.pdf |
| work_keys_str_mv | AT harunsobri artificialneuralnetworkmodelforrainfallrunoffrelationship AT ahmatnornorirwan artificialneuralnetworkmodelforrainfallrunoffrelationship AT mohdkassimamirhashim artificialneuralnetworkmodelforrainfallrunoffrelationship |