Assessment of Shear Stress Distribution in Meandering Compound Channels with Differential Roughness Through Various Artificial Intelligence Approach
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DOI: 10.1007/s11269-021-02966-5
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References listed on IDEAS
- Abinash Mohanta & K. C. Patra & Arpan Pradhan, 2020. "Enhanced Channel Division Method for Estimation of Discharge in Meandering Compound Channel," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(3), pages 1047-1073, February.
- Amirhosein Mosavi & Farzaneh Sajedi Hosseini & Bahram Choubin & Massoud Goodarzi & Adrienn A. Dineva & Elham Rafiei Sardooi, 2021. "Ensemble Boosting and Bagging Based Machine Learning Models for Groundwater Potential Prediction," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(1), pages 23-37, January.
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- Seyed Morteza Seyedian & Ozgur Kisi & Abbas Parsaie & Mojtaba Kashani, 2024. "Improving the Reliability of Compound Channel Discharge Prediction Using Machine Learning Techniques and Resampling Methods," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(12), pages 4685-4709, September.
- Icen Yoosefdoost & Abbas Khashei-Siuki & Hossein Tabari & Omolbani Mohammadrezapour, 2022. "Runoff Simulation Under Future Climate Change Conditions: Performance Comparison of Data-Mining Algorithms and Conceptual Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(4), pages 1191-1215, March.
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Keywords
Artificial intelligence techniques; channel division; Meandering compound channel; Relative roughness; shear force distribution;All these keywords.
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