State-of-the-art development of two-waves artificial intelligence modeling techniques for river streamflow forecasting

Streamflow forecasting is the most well studied hydrological science but still portray numerous unknown knowledge. The conventional physical-based model is unable to yield a high accuracy of forecast due to the embedded noises, non-linear and stochastic nature of hydrological data. This paper is to...

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Main Authors: Tan, Woon Yang, Lai, Sai Hin, Teo, Fang Yenn, El-Shafie, Ahmed
格式: Article
出版: Springer 2022
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在線閱讀:http://eprints.um.edu.my/40971/
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