A prediction model of emergency material demand based on case-based reasoning

In order to solve the problem how to determine the quantitative relationship of characteristic factors caused by uncertainties, this paper describes the target case by characteristic factors in case-based reasoning, determines the initial weight according to the characteristic factor matrix, introduces Hebb learning rule to make a weight adjustment and applies the improved Euclidean distance to calculate the similarity between the cases to look for the most similar case. The similarity comparison between CBR based on Grey Correlation and the proposed method proves this model a better performance. At last, the application example of the prediction model after an earthquake can prove the feasibility.