Wavelet transform and neural network model for streamflow forecasting
Analysis and fast streamflow forecasting are essential. Reliable predicting for river flow, as per the major source of usable water, which can be a crucial factor in the drought analysis and construction of waterrelated infrastructures. Data-driven and hybrid methods are increasingly being used to a...
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| Format: | Article |
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Little Lion Scientific
2022
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| author | Malekpour Heydari, Salimeh Mohd Aris, Teh Noranis Yaakob, Razali Hamdan, Hazlina |
| author_facet | Malekpour Heydari, Salimeh Mohd Aris, Teh Noranis Yaakob, Razali Hamdan, Hazlina |
| author_sort | Malekpour Heydari, Salimeh |
| collection | UPM |
| description | Analysis and fast streamflow forecasting are essential. Reliable predicting for river flow, as per the major source of usable water, which can be a crucial factor in the drought analysis and construction of waterrelated infrastructures. Data-driven and hybrid methods are increasingly being used to address the nonlinear and variable components of hydraulic processes. In this paper, a streamflow forecasting model is built utilizing Neural Network (NN) and Wavelet Transform (WT) at Western Australia for Ellen Brook River with the application of Railway Parade station. Initially, the sequences of signals are applying to the wavelet to be evaluated at several levels and extract a sequence of different features from the chosen output in the wavelet. Then, the obtained output is presented to the neural network for tuning to get the best intermittent streamflow forecasting. The existing input and structures are designed for streamflow forecasting. The proposed model has a better performance compared to the previous models. The proposed model is beneficial for application of forecasts to examine the relation between the characteristics of river flow, optimal decomposition degree, data duration, and the precise wavelet transform form. |
| first_indexed | 2024-03-06T11:17:43Z |
| format | Article |
| id | upm.eprints-102616 |
| institution | Universiti Putra Malaysia |
| last_indexed | 2024-03-06T11:17:43Z |
| publishDate | 2022 |
| publisher | Little Lion Scientific |
| record_format | dspace |
| spelling | upm.eprints-1026162023-10-24T02:52:01Z http://psasir.upm.edu.my/id/eprint/102616/ Wavelet transform and neural network model for streamflow forecasting Malekpour Heydari, Salimeh Mohd Aris, Teh Noranis Yaakob, Razali Hamdan, Hazlina Analysis and fast streamflow forecasting are essential. Reliable predicting for river flow, as per the major source of usable water, which can be a crucial factor in the drought analysis and construction of waterrelated infrastructures. Data-driven and hybrid methods are increasingly being used to address the nonlinear and variable components of hydraulic processes. In this paper, a streamflow forecasting model is built utilizing Neural Network (NN) and Wavelet Transform (WT) at Western Australia for Ellen Brook River with the application of Railway Parade station. Initially, the sequences of signals are applying to the wavelet to be evaluated at several levels and extract a sequence of different features from the chosen output in the wavelet. Then, the obtained output is presented to the neural network for tuning to get the best intermittent streamflow forecasting. The existing input and structures are designed for streamflow forecasting. The proposed model has a better performance compared to the previous models. The proposed model is beneficial for application of forecasts to examine the relation between the characteristics of river flow, optimal decomposition degree, data duration, and the precise wavelet transform form. Little Lion Scientific 2022-10-15 Article PeerReviewed Malekpour Heydari, Salimeh and Mohd Aris, Teh Noranis and Yaakob, Razali and Hamdan, Hazlina (2022) Wavelet transform and neural network model for streamflow forecasting. Journal of Theoretical and Applied Information Technology, 100 (19). 5419 - 5428. ISSN 1992-8645; ESSN: 1817-3195 www.jatit.org |
| spellingShingle | Malekpour Heydari, Salimeh Mohd Aris, Teh Noranis Yaakob, Razali Hamdan, Hazlina Wavelet transform and neural network model for streamflow forecasting |
| title | Wavelet transform and neural network model for streamflow forecasting |
| title_full | Wavelet transform and neural network model for streamflow forecasting |
| title_fullStr | Wavelet transform and neural network model for streamflow forecasting |
| title_full_unstemmed | Wavelet transform and neural network model for streamflow forecasting |
| title_short | Wavelet transform and neural network model for streamflow forecasting |
| title_sort | wavelet transform and neural network model for streamflow forecasting |
| work_keys_str_mv | AT malekpourheydarisalimeh wavelettransformandneuralnetworkmodelforstreamflowforecasting AT mohdaristehnoranis wavelettransformandneuralnetworkmodelforstreamflowforecasting AT yaakobrazali wavelettransformandneuralnetworkmodelforstreamflowforecasting AT hamdanhazlina wavelettransformandneuralnetworkmodelforstreamflowforecasting |