Prediction Success of Machine Learning Methods for Flash Flood Susceptibility Mapping in the Tafresh Watershed, Iran
Saeid Janizadeh(Tarbiat Modares University), Saro Lee(Korea Institute of Geoscience and Mineral Resources), Binh Thai Pham(University of Economics Ho Chi Minh City), Indra Prakash(Government of Gujarat), Tran Van Phong(Vietnam Academy of Science and Technology), Abolfazl Jaafari(Agricultural Research & Education Organization), Mohammadtaghi Avand(Tarbiat Modares University), Ebrahim Ahmadisharaf
Cited by 272
Related Papers
Machine learning methods for landslide susceptibility studies: A comparative overview of algorithm performance
|Earth-Science Reviews|2020|1.1k
A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran
|The Science of The Total Environment|2018|760
A comparative assessment of flood susceptibility modeling using Multi-Criteria Decision-Making Analysis and Machine Learning Methods
|Journal of Hydrology|2019|726
A novel hybrid artificial intelligence approach for flood susceptibility assessment
|Environmental Modelling & Software|2017|637