ESTIMATING WATER LEVEL IN THE URMIA LAKE USING SATELLITE DATA: A MACHINE LEARNING APPROACH

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5. Urmia lake water depth modeling using extreme learning machine-improved grey wolf optimizer hybrid algorithm A. Sales et al. 10.1007/s00704-021-03771-1
6. Comparative assessment of advanced machine learning techniques for simulation of lake water level fluctuations based on different dimensionality reduction methods M. Riazi et al. 10.1007/s12145-023-00951-7