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Groundwater level prediction using machine learning models: A comprehensive review., , , , , , , , , and 14 other author(s). Neurocomputing, (2022)Log-Kumaraswamy distribution: its features and applications., , , , , , , , and . Frontiers Appl. Math. Stat., (2023)Earth skin temperature long-term prediction using novel extended Kalman filter integrated with Artificial Intelligence models and information gain feature selection., , , , , , and . Sustain. Comput. Informatics Syst., (2022)New formulation for predicting total dissolved gas supersaturation in dam reservoir: application of hybrid artificial intelligence models based on multiple signal decomposition., , , , , , , , , and . Artif. Intell. Rev., 57 (4): 85 (2024)Inverse groundwater salinization modeling in a sandstone's aquifer using stand-alone models with an improved non-linear ensemble machine learning technique., , , and . J. King Saud Univ. Comput. Inf. Sci., 34 (10 Part A): 8162-8175 (2022)Digital elevation model for flood hazards analysis in complex terrain: Case study from Jeddah, Saudi Arabia., , , , , , , and . Int. J. Appl. Earth Obs. Geoinformation, (May 2023)Non-Linear Input Variable Selection Approach Integrated With Non-Tuned Data Intelligence Model for Streamflow Pattern Simulation., , , , , and . IEEE Access, (2019)Flash-Flood Susceptibility Assessment Using Multi-Criteria Decision Making and Machine Learning Supported by Remote Sensing and GIS Techniques., , , , , , , , and . Remote. Sens., 12 (1): 106 (2020)A comparative study between dynamic and soft computing models for sediment forecasting., , , , , and . Soft Comput., 25 (16): 11005-11017 (2021)Integrating feature extraction approaches with hybrid emotional neural networks for water quality index modeling., , , , , , , and . Appl. Soft Comput., (2022)