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: | , , , |
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| Format: | Article |
| Published: |
Springer
2022
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| Subjects: | |
| Online Access: | http://eprints.um.edu.my/40971/ |
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