Data-driven forecasting and modeling of runoff flow to reduce flood risk using a novel hybrid wavelet-neural network based on feature extraction
The reliable forecasting of river flow plays a key role in reducing the risk of floods. Regarding nonlinear and variable characteristics of hydraulic processes, the use of data-driven and hybrid methods has become more noticeable. Thus, this paper proposes a novel hybrid wavelet-neural network (WNN)...
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| Main Authors: | , , , |
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| Format: | Article |
| Published: |
Multidisciplinary Digital Publishing Institute
2021
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| Online Access: | http://psasir.upm.edu.my/id/eprint/96598/ https://www.mdpi.com/2071-1050/13/20/11537 |
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