Cloud Model Method in Disaster Loss Assessment
Tao Wu, Qin Kun · 2009
Various disasters have happened continually, and lead to massive loss to the people, loss assessment has become a critical role in alleviating disaster and defending disaster. But uncertainty is often found in disaster loss assessment, due to reasons such as imprecise measurement, outdated sources, or sampling errors. And a nationally consistent approach is absent in disaster loss assessment. In order to handle the uncertainty effectively, considering nature language as the cut-in point in the study of uncertainty, this paper proposed a novel method based on the Cloud model, described evaluation factors using Cloud based soft segmentation, discussed the uncertainty of disaster loss assessment, proposed an algorithm to assess disaster loss, which is more reasonable and more compatible with human think, and finally presented the drought of Zhejiang province in China as an example to illustrate the effectiveness and feasibility of this algorithm.