Modeling reservoir water release decision using adaptive neuro fuzzy inference system
Reservoir water release decision is one of the critical actions in determining the quantity of water to be retained or released from the reservoir.Typically, the decision is influenced by the reservoir inflow that can be estimated based on the rainfall recorded at the reservoir’s upstream areas.Sinc...
保存先:
主要な著者: | , , |
---|---|
フォーマット: | 論文 |
言語: | English |
出版事項: |
Universiti Utara Malaysia
2016
|
主題: | |
オンライン・アクセス: | http://repo.uum.edu.my/20879/1/JICT%2015%202%202016%20141%20152.pdf http://repo.uum.edu.my/20879/ http://jict.uum.edu.my/images/pdf3/vol15no2/7jictno22016.pdf |
タグ: |
タグ追加
タグなし, このレコードへの初めてのタグを付けませんか!
|
id |
my.uum.repo.20879 |
---|---|
record_format |
eprints |
spelling |
my.uum.repo.208792017-02-08T01:23:10Z http://repo.uum.edu.my/20879/ Modeling reservoir water release decision using adaptive neuro fuzzy inference system Abdul Mokhtar, Suriyati Wan Ishak, Wan Hussain Md Norwawi, Norita QA75 Electronic computers. Computer science Reservoir water release decision is one of the critical actions in determining the quantity of water to be retained or released from the reservoir.Typically, the decision is influenced by the reservoir inflow that can be estimated based on the rainfall recorded at the reservoir’s upstream areas.Since the rainfall is recorded at several different locations, the use of temporal pattern alone may not be appropriate.Hence, in this study a spatial temporal pattern was used to retain the spatial information of the rainfall’s location.In addition, rainfall recorded at different locations may cause fuzziness in the data representation.Therefore, a hybrid computational intelligence approach, namely the Adaptive Neuro Fuzzy Inference System (ANFIS), was used to develop a reservoir water release decision model.ANFIS integrates both the neural network and fuzzy logic principles in order to deal with the fuzziness and complexity of the spatial temporal pattern of rainfall.In this study, the Timah Tasoh reservoir and rainfall from five upstream gauging stations were used as a case study.Two ANFIS models were developed and their performances were compared based on the lowest square error achieved from the simulation conducted.Both models utilized the spatial temporal pattern of the rainfall as input.The first model considered the current reservoir water level as an additional input, while the second model retained the existing input.The result indicated that the application of ANFIS could be used successfully for modeling reservoir water release decision. The first model with the additional input showed better performance with the lowest square error compared to the second model. Universiti Utara Malaysia 2016-12 Article PeerReviewed application/pdf en http://repo.uum.edu.my/20879/1/JICT%2015%202%202016%20141%20152.pdf Abdul Mokhtar, Suriyati and Wan Ishak, Wan Hussain and Md Norwawi, Norita (2016) Modeling reservoir water release decision using adaptive neuro fuzzy inference system. Journal of ICT, 15 (2). pp. 141-152. ISSN 1675-414X http://jict.uum.edu.my/images/pdf3/vol15no2/7jictno22016.pdf |
institution |
Universiti Utara Malaysia |
building |
UUM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Utara Malaysia |
content_source |
UUM Institutionali Repository |
url_provider |
http://repo.uum.edu.my/ |
language |
English |
topic |
QA75 Electronic computers. Computer science |
spellingShingle |
QA75 Electronic computers. Computer science Abdul Mokhtar, Suriyati Wan Ishak, Wan Hussain Md Norwawi, Norita Modeling reservoir water release decision using adaptive neuro fuzzy inference system |
description |
Reservoir water release decision is one of the critical actions in determining the quantity of water to be retained or released from the reservoir.Typically, the decision is influenced by the reservoir inflow that can be estimated based on the rainfall recorded at the reservoir’s upstream areas.Since the rainfall is recorded at
several different locations, the use of temporal pattern alone may not be appropriate.Hence, in this study a spatial temporal pattern was used to retain the spatial information of the rainfall’s
location.In addition, rainfall recorded at different locations may cause fuzziness in the data representation.Therefore, a hybrid
computational intelligence approach, namely the Adaptive Neuro Fuzzy Inference System (ANFIS), was used to develop a reservoir water release decision model.ANFIS integrates both the neural network and fuzzy logic principles in order to deal with the fuzziness and complexity of the spatial temporal pattern of rainfall.In this study, the Timah Tasoh reservoir and rainfall from five upstream gauging stations were used as a case study.Two ANFIS models were developed and their performances were
compared based on the lowest square error achieved from the simulation conducted.Both models utilized the spatial temporal pattern of the rainfall as input.The first model considered the
current reservoir water level as an additional input, while the second model retained the existing input.The result indicated that the application of ANFIS could be used successfully for modeling reservoir water release decision. The first model with the additional input showed better performance with the lowest square error compared to the second model. |
format |
Article |
author |
Abdul Mokhtar, Suriyati Wan Ishak, Wan Hussain Md Norwawi, Norita |
author_facet |
Abdul Mokhtar, Suriyati Wan Ishak, Wan Hussain Md Norwawi, Norita |
author_sort |
Abdul Mokhtar, Suriyati |
title |
Modeling reservoir water release decision using adaptive neuro fuzzy inference system |
title_short |
Modeling reservoir water release decision using adaptive neuro fuzzy inference system |
title_full |
Modeling reservoir water release decision using adaptive neuro fuzzy inference system |
title_fullStr |
Modeling reservoir water release decision using adaptive neuro fuzzy inference system |
title_full_unstemmed |
Modeling reservoir water release decision using adaptive neuro fuzzy inference system |
title_sort |
modeling reservoir water release decision using adaptive neuro fuzzy inference system |
publisher |
Universiti Utara Malaysia |
publishDate |
2016 |
url |
http://repo.uum.edu.my/20879/1/JICT%2015%202%202016%20141%20152.pdf http://repo.uum.edu.my/20879/ http://jict.uum.edu.my/images/pdf3/vol15no2/7jictno22016.pdf |
_version_ |
1644283083854184448 |
score |
13.149126 |