Discharge coefficient prediction of canal radial gate using neurocomputing models: an investigation of free and submerged flow scenarios

Author:

Tao Hai123,Jamei Mehdi4ORCID,Ahmadianfar Iman5,Khedher Khaled Mohamed67,Farooque Aitazaz Ahsan89,Yaseen Zaher Mundher101112

Affiliation:

1. School of Electronics and Information Engineering, Ankang University, Ankang, People’s Republic of China

2. School of Computer Sciences, Baoji University of Arts and Sciences, Baoji, People’s Republic of China

3. Institute for Big Data Analytics and Artificial Intelligence (IBDAAI), Universiti Teknologi MARA, Shah Alam, Malaysia

4. Faculty of Engineering, Shohadaye Hoveizeh Campus of Technology, Shahid Chamran University of Ahvaz, Dashte Azadegan, Iran

5. Department of Civil Engineering, Behbahan Khatam Alanbia University of Technology, Behbahan, Iran

6. Department of Civil Engineering, College of Engineering, King Khalid University, Abha, Saudi Arabia

7. Department of Civil Engineering, High Institute of Technological Studies, Mrezgua University Campus, Nabeul, Tunisia

8. Faculty of Sustainable Design Engineering, University of Prince Edward Island, Charlottetown, Canada

9. School of Climate Change and Adaptation, University of of Prince Edward Island, Charlottetown, Canada

10. Department of Urban Planning, Engineering Networks and Systems, Institute of Architecture and Construction, South Ural State University, Chelyabinsk, Russia

11. New Era and Development in Civil Engineering Research Group, Scientific Research Center, Al-Ayen University, Thi-Qar, Iraq

12. College of Creative Design, Asia University, Taichung, Taiwan

Publisher

Informa UK Limited

Subject

Modeling and Simulation,General Computer Science

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