Affiliation:
1. Beijing Institute of Technology
2. China Academy of Safety Sciences and Technology
Abstract
This thesis intends to study the technology that the information entropy and the standard deviation are used to forecast the CBR demand. Firstly the standard deviation is used to calculate the weight of each index; secondly, the rescue database with plenty of information and the information entropy are used to calculate the weight of each index level, then the model is built where standard deviation weight and entropy weight are integrated; the cases are verified by the model at the end.
Publisher
Trans Tech Publications, Ltd.
Reference5 articles.
1. Shi Z, Zhou H, Wang J: Artificial Intelligence in Engineering. Vol. 11(2) (1997), p.167.
2. Bose A, Gini M, Riley D: Artificial Intelligence in Engineering. Vol. 11(2) (1997), p.107.
3. Jun Wang: Journal of Tsinghua University Vol. 46(S1) (2006), p.900 In Chinese.
4. Mu Liu: Oil and gas pipelines emergency resource demand forecasting and transporting methods research (Ph.D. Dissertation Beijing Institute of Technology, Beijing 2010) In Chinese.
5. Jungang Luo: Journal of Hydraulic Engineering. Vol. 39(9) (2008), p.1092 In Chinese.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献