A comparison of artificial intelligence approaches in predicting discharge coefficient of streamlined weirs

In the present research, three different data-driven models (DDMs) are developed to predict the discharge coefficient of streamlined weirs (Cdstw). Some machine-learning methods (MLMs) and intelligent optimization models (IOMs) such as Random Forest (RF), Adaptive Neuro-Fuzzy Inference System (ANFIS...

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書誌詳細

主要な著者:	Amin Gharehbaghi, Redvan Ghasemlounia, Ehsan Afaridegan, AmirHamzeh Haghiabi, Vishwanadham Mandala, Hazi Mohammad Azamathulla, Abbas Parsaie
フォーマット:	Artigo
言語:	Inglês
出版事項:	IWA Publishing 2023-07-01
シリーズ:	Journal of Hydroinformatics
主題:	discharge coefficient intelligent optimization models joukowsky transform machine-learning models open-channel flow streamlined weirs
オンライン･アクセス:	http://jhydro.iwaponline.com/content/25/4/1513
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