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DC Field | Value | Language |
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dc.contributor.author | Jain, Sharad K. | - |
dc.contributor.author | Chalisgaonkar, Deepa | - |
dc.date.accessioned | 2022-04-27T16:44:38Z | - |
dc.date.available | 2022-04-27T16:44:38Z | - |
dc.date.issued | 2001 | - |
dc.identifier.uri | http://117.252.14.250:8080/jspui/handle/123456789/6754 | - |
dc.description.abstract | The design, analysis and management of the water resources systems, involves modelling and prediction of the behavior of complex systems. The Artificial Neural Network (ANN) can be used in a large variety of problems, e.g. mapping, dynamic process modelling, optimisation, image processing, data analysis, forecasting, simulation, function approximation etc. Due to the distributed nature of ANNs, destruction of a few nodes or presence of some inconsistent data does not adversely affect the performance of ANNs. An ANN model was applied to rainfall-runoff simulation of an Indian catchment. Hourly rainfall, discharge and potential evaporation data were used The results show acceptable match between the observed and computed discharges. | en_US |
dc.language.iso | en | en_US |
dc.publisher | National Institute of Hydrology | en_US |
dc.subject | Emerging Techniques in Water Resources | en_US |
dc.subject | Artificial Neural Networks | en_US |
dc.subject | Rainfall-Runoff Modelling | en_US |
dc.title | 3-Application of Artificial Neural Networks in Rainfall-Runoff Modelling. | en_US |
dc.type | Technical Report | en_US |
Appears in Collections: | 21-Jal Vigyan Sameeksha Vol.-16(1-2)-2001 |
Files in This Item:
File | Description | Size | Format | |
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3-Application of Artificial Neural Networks in Rainfall-Runoff Modelling..pdf | 12.41 MB | Adobe PDF | View/Open |
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