Flood prediction using NARX neural network and EKF prediction technique: A comparative study
Accurate and reliable flood water level prediction is very difficult to achieve as it is often characterized as chaotic in nature. Prediction using conventional neural network techniques with back propagation algorithm which was widely used does not provide reliable prediction results. Flood water l...
| 发表在: | Proceedings - 2013 IEEE 3rd International Conference on System Engineering and Technology, ICSET 2013 |
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| 格式: | Conference paper |
| 语言: | English |
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2013
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| 在线阅读: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84891096883&doi=10.1109%2fICSEngT.2013.6650171&partnerID=40&md5=63ba98e30991dcadcd39f9aa8d68a634 |
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Ruslan F.A.; Samad A.M.; Zain Z.M.; Adnan R. |
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Ruslan F.A.; Samad A.M.; Zain Z.M.; Adnan R. 2-s2.0-84891096883 Flood prediction using NARX neural network and EKF prediction technique: A comparative study 2013 Proceedings - 2013 IEEE 3rd International Conference on System Engineering and Technology, ICSET 2013 10.1109/ICSEngT.2013.6650171 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84891096883&doi=10.1109%2fICSEngT.2013.6650171&partnerID=40&md5=63ba98e30991dcadcd39f9aa8d68a634 Accurate and reliable flood water level prediction is very difficult to achieve as it is often characterized as chaotic in nature. Prediction using conventional neural network techniques with back propagation algorithm which was widely used does not provide reliable prediction results. Flood water level is characterizing as a dynamic nonlinear properties that cannot be represented by static neural network such as back propagation algorithm. Therefore, NARX NN is propose as the identification model because it could reflect the dynamic characteristics of the flood water level, as NARX structure includes the feedback of the network output. This paper compares the prediction performances of NARX model and EKF prediction technique in flood water level prediction. EKF is well known as the best nonlinear state estimator. Results showed that NARX model performed better than EKF prediction technique. © 2013 IEEE. English Conference paper |
| author |
2-s2.0-84891096883 |
| spellingShingle |
2-s2.0-84891096883 Flood prediction using NARX neural network and EKF prediction technique: A comparative study |
| author_facet |
2-s2.0-84891096883 |
| author_sort |
2-s2.0-84891096883 |
| title |
Flood prediction using NARX neural network and EKF prediction technique: A comparative study |
| title_short |
Flood prediction using NARX neural network and EKF prediction technique: A comparative study |
| title_full |
Flood prediction using NARX neural network and EKF prediction technique: A comparative study |
| title_fullStr |
Flood prediction using NARX neural network and EKF prediction technique: A comparative study |
| title_full_unstemmed |
Flood prediction using NARX neural network and EKF prediction technique: A comparative study |
| title_sort |
Flood prediction using NARX neural network and EKF prediction technique: A comparative study |
| publishDate |
2013 |
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Proceedings - 2013 IEEE 3rd International Conference on System Engineering and Technology, ICSET 2013 |
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| container_issue |
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| doi_str_mv |
10.1109/ICSEngT.2013.6650171 |
| url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84891096883&doi=10.1109%2fICSEngT.2013.6650171&partnerID=40&md5=63ba98e30991dcadcd39f9aa8d68a634 |
| description |
Accurate and reliable flood water level prediction is very difficult to achieve as it is often characterized as chaotic in nature. Prediction using conventional neural network techniques with back propagation algorithm which was widely used does not provide reliable prediction results. Flood water level is characterizing as a dynamic nonlinear properties that cannot be represented by static neural network such as back propagation algorithm. Therefore, NARX NN is propose as the identification model because it could reflect the dynamic characteristics of the flood water level, as NARX structure includes the feedback of the network output. This paper compares the prediction performances of NARX model and EKF prediction technique in flood water level prediction. EKF is well known as the best nonlinear state estimator. Results showed that NARX model performed better than EKF prediction technique. © 2013 IEEE. |
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English |
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Conference paper |
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scopus |
| collection |
Scopus |
| _version_ |
1828987883112890368 |