Reservoir water level forecasting model using neural network

Reservoir is one of the structural defense mechanism for flood. During heavy rainfall, reservoir hold excessive amount of water to reduce flood risk at downstream area. During less rainfall, reservoir maintains the water supply for major uses such as domestic and commercial usage. In both situ...

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Main Authors: Wan Ishak, Wan Hussain, Ku-Mahamud, Ku Ruhana, Md. Norwawi, Norita
Format: Article
Language:English
Published: Research India Publications 2010
Subjects:
Online Access:https://repo.uum.edu.my/id/eprint/3994/1/ijcirvol6no4.pdf
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author Wan Ishak, Wan Hussain
Ku-Mahamud, Ku Ruhana
Md. Norwawi, Norita
author_facet Wan Ishak, Wan Hussain
Ku-Mahamud, Ku Ruhana
Md. Norwawi, Norita
author_sort Wan Ishak, Wan Hussain
collection UUM
description Reservoir is one of the structural defense mechanism for flood. During heavy rainfall, reservoir hold excessive amount of water to reduce flood risk at downstream area. During less rainfall, reservoir maintains the water supply for major uses such as domestic and commercial usage. In both situations, the water release decision is very critical. The decision is typically influence by the reservoir storage capacity that is the reservoir water level. Early decision regarding the water release can be made if the future water level can be forecasted. In this paper, the potential of neural network model for forecasting the reservoir water level is experimented. The time delay of upstream flow to increase the water level is also experimented. Sliding windows have been used to segment the data into a various range. The findings show that 8 days for delay has significantly affected the reservoir water level. The best neural network model obtain from the experiment is 24-15-3.
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spelling uum-39942013-01-16T04:22:10Z https://repo.uum.edu.my/id/eprint/3994/ Reservoir water level forecasting model using neural network Wan Ishak, Wan Hussain Ku-Mahamud, Ku Ruhana Md. Norwawi, Norita QA75 Electronic computers. Computer science Reservoir is one of the structural defense mechanism for flood. During heavy rainfall, reservoir hold excessive amount of water to reduce flood risk at downstream area. During less rainfall, reservoir maintains the water supply for major uses such as domestic and commercial usage. In both situations, the water release decision is very critical. The decision is typically influence by the reservoir storage capacity that is the reservoir water level. Early decision regarding the water release can be made if the future water level can be forecasted. In this paper, the potential of neural network model for forecasting the reservoir water level is experimented. The time delay of upstream flow to increase the water level is also experimented. Sliding windows have been used to segment the data into a various range. The findings show that 8 days for delay has significantly affected the reservoir water level. The best neural network model obtain from the experiment is 24-15-3. Research India Publications 2010 Article PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/3994/1/ijcirvol6no4.pdf Wan Ishak, Wan Hussain and Ku-Mahamud, Ku Ruhana and Md. Norwawi, Norita (2010) Reservoir water level forecasting model using neural network. International Journal of Computational Intellegence, 6 (4). pp. 947-952. ISSN 0973-1873 http://www.ripublication.corn/ijcir.htm
spellingShingle QA75 Electronic computers. Computer science
Wan Ishak, Wan Hussain
Ku-Mahamud, Ku Ruhana
Md. Norwawi, Norita
Reservoir water level forecasting model using neural network
title Reservoir water level forecasting model using neural network
title_full Reservoir water level forecasting model using neural network
title_fullStr Reservoir water level forecasting model using neural network
title_full_unstemmed Reservoir water level forecasting model using neural network
title_short Reservoir water level forecasting model using neural network
title_sort reservoir water level forecasting model using neural network
topic QA75 Electronic computers. Computer science
url https://repo.uum.edu.my/id/eprint/3994/1/ijcirvol6no4.pdf
work_keys_str_mv AT wanishakwanhussain reservoirwaterlevelforecastingmodelusingneuralnetwork
AT kumahamudkuruhana reservoirwaterlevelforecastingmodelusingneuralnetwork
AT mdnorwawinorita reservoirwaterlevelforecastingmodelusingneuralnetwork