The purpose of this paper is to assess the natural disaster damage of Sichuan province and provide suggestions to prevent or decrease the loss owing to the natural disaster.
The disaster loss system of Sichuan is regarded as a grey system. Five evaluation indicators are selected such as the number of deaths, total affected area, collapsed houses, damaged houses, and the direct economic losses. Grey fixed-weight clustering approach is applied in the cluster analysis. In order to reduce the impact of human factors, grey correlation analysis method is applied to calculate the weights of grey fixed-weight clustering.
The results of this paper indicate that the frequency of occurrence of major natural disaster in Sichuan increased since 2008. The major natural disasters occurred in 2008, 2010, 2011, and 2013. In contrast, there was almost no major disaster during 2000-2007. Minor natural disaster occurred in 2002 and 2003.
Sichuan province is one of the provinces most affected by natural disasters in China. Natural disasters have occurred frequently in Sichuan province since 2008 and pose serious threats to life and property safety. They have become an important restricting factor for economic and social development. In order to prevent or decrease the effects of natural disasters, effective measures should be taken to protect the environment.
This paper first normalizes the raw sequence, calculates the weight, and then establishes the grey cluster model. A new method is applied to determine the weight when evaluating natural disaster damage.
This paper was supported by National Natural Science Foundation of China (71171116), Natural Science Foundation of Higher Education of Jiangsu Province of China (16KJB120003), and Philosophical and Social Science Foundation of Higher Education of Jiangsu Province of China (2016SJB630023).
Yao, T., Cheng, W. and Gao, H. (2016), "The natural disaster damage assessment of Sichuan province based on grey fixed-weight cluster", Grey Systems: Theory and Application, Vol. 6 No. 3, pp. 415-425. https://doi.org/10.1108/GS-08-2016-0019Download as .RIS
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