A Systematic Literature Review on Classification Machine Learning for Urban Flood Hazard Mapping

This publication has 141 references indexed in Scilit:

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  Stochastic Environmental Research and Risk Assessment, 2022
• Flood-prone area mapping using machine learning techniques: a case study of Quang Binh province, Vietnam
  Natural Hazards, 2021
• Urban flood hazard mapping using machine learning models: GARP, RF, MaxEnt and NB
  Natural Hazards, 2021
• Flood susceptibility prediction using four machine learning techniques and comparison of their performance at Wadi Qena Basin, Egypt
  Natural Hazards, 2020
• Flood susceptibility modeling in Teesta River basin, Bangladesh using novel ensembles of bagging algorithms
  Stochastic Environmental Research and Risk Assessment, 2020
• Comparative assessment of bivariate, multivariate and machine learning models for mapping flood proneness
  Natural Hazards, 2019
• Exploring the application of topographic indices in urban areas as indicators of pluvial flooding locations
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• Hyperparameters and tuning strategies for random forest
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• Flood hazard assessment for extreme flood events
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• Future changes to the intensity and frequency of short-duration extreme rainfall
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