Abstract
The floods have undermined the sustainable construction of cities because of their sudden and destruction. To reduce the losses caused by floods, it is necessary to make a reasonable evaluation for historical floods and provide scientific guidance for future precaution. Previous research mainly used subjective/objective weights or barely made static analysis without considering the uncertainty and ambiguity of floods. Therefore, this study proposed a variable fuzzy recognition model, based on combined weights, to evaluate floods, including the determination of index weights and the choice of evaluation model. To make the index weights reflect both subjective experience and objective data, the combined weights were proposed and calculated based on the principle of minimum identification information. Then, the relative membership degree matrix and evaluation results can be worked out by the variable fuzzy recognition model. Conclusions indicated that the combined weights were more convincing than simply subjective or objective weights. Moreover, the variable fuzzy recognition model, by changing model parameters, got stable evaluation results of the sample data. Therefore, the model can improve the credibility of evaluation and the conclusions can provide reasonable suggestions for management departments.
Highlights
The floods have destroyed the sustainable construction of cities, such as damaging buildings and breaking the city lifeline system, when they suddenly happened with great power [1]
In order to validate the influence of individual preference on the subjective weights, combined weights and the evaluation results, we choose two groups of experts to fill in the judgment matrix for Analytic Hierarchy Process (AHP) and the binary comparison method separately
This paper had the comprehensive evaluation results calculated by the multi-index evaluation model of variable fuzzy recognition, based on the combined weights according to a case
Summary
The floods have destroyed the sustainable construction of cities, such as damaging buildings and breaking the city lifeline system, when they suddenly happened with great power [1]. Since the 1980s, the research on disaster sociology and disaster economics emerged rapidly, with the development of the disaster reduction activities worldwide [17] They proposed a number of quantitative evaluation methods about the disaster losses, one after another, including the fuzzy comprehensive evaluation method [18,19,20], grey clustering analysis method [21,22], intelligent model based on artificial neural network and genetic algorithm [23,24], projection pursuit method [25], and the matter element analysis method [26], etc. The goal of this study is to make a scientific and reasonable evaluation for floods by a variable fuzzy recognition model based on combined weights, and to provide supports for government authorities on flood precaution and mitigation. The floods evaluation by variable fuzzy recognition model, based on combined weights, can provide supports for disaster precaution and relief decision-making. The model proposed by this study can be applicable to the multi-index evaluation in other fields—with a good promotion
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