Training and Testing Data Division Influence on Hybrid Machine Learning Model Process: Application of River Flow Forecasting
The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environment...
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Main Authors: | Hai Tao, Ali Omran Al-Sulttani, Ameen Mohammed Salih Ameen, Zainab Hasan Ali, Nadhir Al-Ansari, Sinan Q. Salih, Reham R. Mostafa |
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Format: | Article |
Language: | English |
Published: |
Wiley
2020-01-01
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Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2020/8844367 |
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