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: Malekpour Heydari, Salimeh, Mohd Aris, Teh Noranis, Yaakob, Razali, Hamdan, Hazlina
格式: Article
出版: Multidisciplinary Digital Publishing Institute 2021
在线阅读:http://psasir.upm.edu.my/id/eprint/96598/
https://www.mdpi.com/2071-1050/13/20/11537
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