Risk assessment and validation of flood disaster based on fuzzy mathematics

By Weiguo Jiang, L. Deng, Luyao Chen, Jianjun Wu, Jing Li. 2009

128 citations recorded by the source corpus.

Abstract Floods often take place around rivers and plains, which indicates a higher risk of flooding in these areas. This paper adopts fuzzy comprehensive assessment (FCA), simple fuzzy classification (SFC), and the fuzzy similarity method (FSM) to assess flood disaster risk in Kelantan, Malaysia. Validation data, such as the flooded area, paddy area, urban area, residential area, and refuges, were overlaid to validate and analyze the accuracy of flood disaster risk. The results show that (1) 70–75% of flooded areas lie within the higher and highest risk zones, which shows an effective assessment accuracy; (2) paddy, built-up, and residential areas concentrated in the higher and highest risk zones are more likely to be destroyed by flood disasters; (3) 200–225 refuges in the higher and highest risk zones account for around 50% of all refuges, which means that more refuges should be built in the higher and highest risk zones to meet the accommodation requirement; (4) three methods proved to be feasible and effective in evaluating flood disaster risk, among which FCA is more suitable for the study area than the two other methods.

Subfields: Artificial Intelligence, Environmental Engineering, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/2a93d895b6eec65c9780c2994eae005b2db9d7e1

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Citations in the corpus

Flood hazard risk assessment model based on random forest (2015, methodology): “After considering the actual conditions of floods and relevant characteristics in the study area and reviewing recommendations provided by previous research (Jiang et al., 2009; Zou et al., 2013; Yang et al., 2013), three indices of disaster-inducing factors and eight indices of hazard-inducing”
Assessment of Geohazards and Preventative Countermeasures Using AHP Incorporated with GIS in Lanzhou, China (2018, methodology): “(2009) [32] and Kazakis (2015) [33] Figure 1.”
Survey of computational intelligence as basis to big flood management: challenges, research directions and future work (2018, methodology): “Several effective fuzzy-based models have been proposed and employed in flood prediction (Jiang et al., 2009) ranging from formal concept analysis (FCA) to simple fuzzy classifier (SFC) problems.”
Optimization models in emergency logistics: A literature review (2012, methodology): “Research addresses those challenges through the use of statistical and probabilistic models [16,69], queuing theory [3], simulation [33,55], decision theory [17,62], fuzzy methods [21,37], and most commonly, optimization methods (will be discussed in this paper).”
Comprehensive flood risk assessment based on set pair analysis-variable fuzzy sets model and fuzzy AHP (2013, background): “…evacuation, disaster warning, disaster evaluation, flood influence evaluation, improving the public’s flood risk awareness and understanding of flood disasters; meanwhile, it is also an important scientific basis for flood risk management and decision-making (Jiang et al. 2009; Wang et al. 2011).”