Pre-assessment for ice disaster in Ning-Meng reaches of the Yellow river based on improved TOPSIS under three-parameter interval grey number

Abstract

The occurrence of ice disasters in Ning-Meng Reaches of the Yellow River in China is affected by a variety of factors. The interaction between the factors has a certain degree of uncertainty. It is a complex multi-factor interaction process. So pre-disaster assessment to improve the effectiveness of prevention and mitigation is essential. To address such a challenging problem, three critical contributions are provided in this paper. First, according to the value characteristics of the three-parameter interval grey number, aiming at the grey characteristics of ice disasters, the concept of compatibility degree of the three-parameter interval grey number is defined. Second, according to the “new information priority principle” of grey system theory, an optimized model based on variable coefficient and time degree is built to determine the weight of the time point. Finally, the shortcomings of the classical Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method are analyzed. Combined with the compatibility degree of the three-parameter interval grey number, the weighted relative compatibility degree of the scheme is defined; the scheme is sorted according to the weighted relative compatibility degree. To verify the efficacy and practicality of this proposed model, data sets from the ice disaster data (2014–2020) are employed in the experiments. The experimental results show that the decision results of the improved TOPSIS method are more consistent with the actual situation than the results of the classical TOPSIS method. Moreover, the improved TOPSIS method can be applied to the case where the decision information is a three-parameter interval grey number and to the case where the decision information is a real number. It shows that the modified TOPSIS method has a wider application range than the classical TOPSIS method. The rationality of the results is analyzed based on the evaluation results, which provides a better reference for improving the prevention and management of ice disasters.