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Flood Water Level Forecasting with Stable Accuracy using Nonlinear Autoregressive Exogenous Neural Network
| Content Provider | Scilit |
|---|---|
| Author | Faruq, Amrul |
| Copyright Year | 2019 |
| Description | This paper presents an improved lead time flood forecasting using Nonlinear Autoregressive Exogenous Neural Networks (NARXNN) technique. First, the model is trained by open-loop NARX model using four upper-rivers as exogenous input and one output flood water level of Kelantan River at Kuala Krai, Kelantan, Malaysia. Then a closed-loop sometimes called parallel model of NARX employed with reliable taped-delay times and number of hidden neurons to forecast water level in flood forecasting point (FFP). The model has been tested for multi-step-ahead of time water level at flood location. The result verified the high precision level of error prediction of the presented flood forecasting model. |
| DOI | 10.31227/osf.io/c9jhf |
| Language | English |
| Publisher | Center for Open Science |
| Publisher Date | 2019-10-20 |
| Access Restriction | Open |
| Subject Keyword | Hardware and Architecture Industrial Engineering Using Nonlinear Forecast Water Level |
| Content Type | Text |
| Resource Type | Article |
