124 citations as recorded by crossref.

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29. Spatio-temporal cross-validation to predict pluvial flood events in the Metropolitan City of Venice Z. Marco et al. 10.1016/j.jhydrol.2022.128150
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39. Mapping Fire Susceptibility in the Brazilian Amazon Forests Using Multitemporal Remote Sensing and Time-Varying Unsupervised Anomaly Detection A. Luz et al. 10.3390/rs14102429
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42. Comparison of Novel Hybrid and Benchmark Machine Learning Algorithms to Predict Groundwater Potentiality: Case of a Drought-Prone Region of Medjerda Basin, Northern Tunisia F. Trabelsi et al. 10.3390/rs15010152
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52. Application of hybrid model-based machine learning for groundwater potential prediction in the north central of Vietnam H. Nguyen et al. 10.1007/s12145-023-01209-y
53. Assessment of influencing factor method for delineation of groundwater potential zones with geospatial techniques. Case study of Bostanlik district, Uzbekistan B. Alikhanov et al. 10.1016/j.gsd.2021.100548
54. Optimized Conditioning Factors Using Machine Learning Techniques for Groundwater Potential Mapping . Kalantar et al. 10.3390/w11091909
55. Application of Machine Learning Algorithms for Geogenic Radon Potential Mapping in Danyang-Gun, South Korea F. Rezaie et al. 10.3389/fenvs.2021.753028
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58. Landslide susceptibility modeling based on ANFIS with teaching-learning-based optimization and Satin bowerbird optimizer W. Chen et al. 10.1016/j.gsf.2020.07.012
59. Mapping Burned Areas with Multitemporal–Multispectral Data and Probabilistic Unsupervised Learning R. Negri et al. 10.3390/rs14215413
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64. Point and interval forecasting for carbon price based on an improved analysis-forecast system C. Tian & Y. Hao 10.1016/j.apm.2019.10.022
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67. Stochastic Modeling of Groundwater Fluoride Contamination: Introducing Lazy Learners K. Khosravi et al. 10.1111/gwat.12963
68. Application of novel framework approach for prediction of nitrate concentration susceptibility in coastal multi-aquifers, Bangladesh A. Islam et al. 10.1016/j.scitotenv.2021.149811
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