Flood and Flash Flood Hazard Mapping Using the Frequency Ratio, Multilayer Perceptron and Their Hybrid Ensemble
The importance of identifying the areas vulnerable for both floods and flash-floods is an important component of risk management. The assessment of vulnerable areas is a major challenge in the scientific world. Adaptation and mitigation have generally been treated as two separate issues, both in public politics and in practice, in which mitigation is seen as the attenuation of the cause, and studies of adaption look into dealing with the consequences of climate change. Studies on the impact of climate change on flood risk are mostly conducted at the river basin or regional scale. Remote sensing and GIS technologies, together with the latest modelling techniques, can contribute to our ability to predict and manage floods. Various methods are commonly used to map flood sensitivity. Recent methods such as multicriteria evaluation, decision tree analysis (DT), fuzzy theory, weight of samples (WoE), artificial neural networks (ANN), frequency ratio (FR) and logistic regression (LR) approaches have been widely used by many researchers.
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Flood and Flash Flood Hazard Mapping Using the Frequency Ratio, Multilayer Perceptron and Their Hybrid Ensemble
Semantic Scholar · Environmental Science · 2019
Abstract
The importance of identifying the areas vulnerable for both floods and flash-floods is an important component of risk management. The assessment of vulnerable areas is a major challenge in the scientific world. Adaptation and mitigation have generally been treated as two separate issues, both in public politics and in practice, in which mitigation is seen as the attenuation of the cause, and studies of adaption look into dealing with the consequences of climate change. Studies on the impact of climate change on flood risk are mostly conducted at the river basin or regional scale. Remote sensing and GIS technologies, together with the latest modelling techniques, can contribute to our ability to predict and manage floods. Various methods are commonly used to map flood sensitivity. Recent methods such as multicriteria evaluation, decision tree analysis (DT), fuzzy theory, weight of samples (WoE), artificial neural networks (ANN), frequency ratio (FR) and logistic regression (LR) approaches have been widely used by many researchers.
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