Technical Study on Demand Forecast for CBR Emergency Resources Based on Information Entropy and Standard Deviation

Zai Peng Duan; Xin Ming Qian; Ying Quan Duo; Zong Zhi Wu

doi:10.4028/www.scientific.net/AMR.955-959.1877

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 955-959Technical Study on Demand Forecast for CBR...

Technical Study on Demand Forecast for CBR Emergency Resources Based on Information Entropy and Standard Deviation

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.

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Periodical:

Advanced Materials Research (Volumes 955-959)

Pages:

1877-1880

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.955-959.1877

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Online since:

June 2014

Authors:

Zai Peng Duan, Xin Ming Qian*, Ying Quan Duo, Zong Zhi Wu

Keywords:

Case Inference, Demand Forecast, Emergency Resources, Information Entropy, Standard Deviation

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* - Corresponding Author

References

[1] Shi Z, Zhou H, Wang J: Artificial Intelligence in Engineering. Vol. 11(2) (1997), p.167.

Google Scholar

[2] Bose A, Gini M, Riley D: Artificial Intelligence in Engineering. Vol. 11(2) (1997), p.107.

Google Scholar

[3] Jun Wang: Journal of Tsinghua University Vol. 46(S1) (2006), p.900 In Chinese.

Google Scholar

[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.

Google Scholar

[5] Jungang Luo: Journal of Hydraulic Engineering. Vol. 39(9) (2008), p.1092 In Chinese.

Google Scholar