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Forecasting Daily Flood Water Level Using Hybrid Advanced Machine Learning Based Time-Varying Filtered Empirical Mode Decomposition Approach |
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| Authors: | Jamei Mehdi Ali Mumtaz Malik Anurag Prasad Ramendra Abdulla Shahab Yaseen Zaher Mundher |
| Affiliation: | 1.Faculty of Engineering, Shohadaye Hoveizeh Campus of Technology, Shahid Chamran University of Ahvaz, Dashte Azadegan, Iran ;2.School of Information Technology, Deakin University, Burwood, VIC, 3125, Australia ;3.Punjab Agricultural University, Regional Research Station, Punjab, Bathinda, 151001, India ;4.Department of Science, School of Science and Technology, The University of Fiji, Lautoka, Fiji ;5.USQ College, University of Southern Queensland, Toowoomba, Australia ;6.Department of Earth Sciences and Environment, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia ;7.New Era and Development in Civil Engineering Research Group, Scientific Research Center, Al-Ayen University, Thi-Qar, 64001, Iraq ;8.Adjunct Research Fellow, USQ’s Advanced Data Analytics Research Group, School of Mathematics, Physics and Computing, University of Southern Queensland, Toowoomba, QLD, 4350, Australia ; |
| Abstract: | Water Resources Management - Accurate water level forecasting is important to understand and provide an early warning of flood risk and discharge. It is also crucial for many plants and animal... |
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