面向灾害应急物资需求的灰色异构数据预测建模方法

doi:10.16381/j.cnki.issn1003-207x.2015.08.010

中国管理科学 ›› 2015, Vol. 23 ›› Issue (8): 84-91.doi: 10.16381/j.cnki.issn1003-207x.2015.08.010

面向灾害应急物资需求的灰色异构数据预测建模方法

曾波^1,2, 孟伟¹, 刘思峰³, 李川⁴, 崔杰³

1. 重庆工商大学商务策划学院, 重庆 400067;
2. 电子科技大学经济与管理学院, 四川成都 611731;
3. 南京航空航天大学经济与管理学院, 江苏南京 210016;
4. 重庆工商大学装备系统服役健康保障国际联合研究中心, 重庆 400067

收稿日期:2013-07-12 修回日期:2014-03-04 出版日期:2015-08-20 发布日期:2015-08-19
作者简介:曾波(1975-),男(汉族),四川威远人,重庆工商大学商务策划学院教授,工学博士,管理学博士后,研究方向:系统预测、决策与评价.
基金资助:
国家自然科学基金资助项目(71271226,71301060);中国博士后科学基金资助项目(2014M560712);中国博士后科学基金特别资助项目(2015T80975);重庆市基础与前沿研究计划项目(cstc2014jcyjA00024);教育部人文社会科学研究一般项目(14YJAZH033);重庆高校创新团队计划(KJTD201313);重庆市高等学校教学改革研究项目(1202010);重庆市教委科学技术研究项目资助(KJ120706)

Prediction Modeling Method of Grey Isomerism Data for Calamity Emergency Material Demand

ZENG Bo^1,2, MENG Wei¹, LIU Si-feng³, LI Chuan⁴, CUI Jie³

1. School of Business Planning, Chongqing Technology and Business University, Chongqing 400067, China;
2. School of Management and Economics, University of Electrcnic Science and Tehnology, Chengdu 611731, China;
3. College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;
4. Research Center of Sustem Health Maintenance, Chongqing Technology and University, Chongqing 400067, China

Received:2013-07-12 Revised:2014-03-04 Online:2015-08-20 Published:2015-08-19

摘要/Abstract

摘要： 多源信息集结对提高自然灾害环境下统计数据可信度具有重要作用,但信息渠道的多源性极易导致集结信息数据类型不一致、不兼容,形成灰色异构数据序列。本文应用灰色系统建模技术对灰色异构数据预测建模方法展开研究,首先,基于"核"和"灰度"对灰色异构数据进行规范化处理;然后,建立灰色异构数据"核"序列的DGM(1,1)模型,并以"核"为基础,根据灰度不减公理,以灰色异构数据序列中最大灰度值所对应的信息域作为预测结果之信息域,推导并构建了灰色异构数据预测模型;最后,将该模型应用于某地震帐篷需求量的预测。本文研究成果将传统灰色模拟及预测模型建模对象从"同质数据"拓展至"异构数据",对丰富与完善灰色模拟及预测模型理论体系,提高自然灾害救援效率具有积极意义。

关键词: 灰色理论, 预测模型, 灰色异构数据, 应急物资需求

Abstract: Multiple-source information aggregation is a significant way to improve the reliability of the statistical data in the environment of natural disasters. However, the diversity of information sources often cause the inconformity and incompatible types of the aggregation information data which thereby produce isomerism data sequences that belong to different types of data. The modeling technology of grey system is applied to study the modeling method for grey isomerism data. First, the grey heterogeneous data is normalized based on the "Kernel" and "degree of greyness"; then a (1,1) DGM model of grey heterogeneous data "Kernel" sequence is established. According to the "Kernel" and the axiom of grey degree not-reducing, a grey prediction model of heterogeneous data is built by using the information field to which the maximum degree of greyness in the grey heterogeneous data sequence corresponding as the information field of the prediction results, Finally, the model is applied to forecast the demand volume of tent in the ya'an earthquake. The research results of the project will expand the traditional modeling objects of gray forecasting model from homogeneous data to heterogeneous data and has a vital significance for enriching and perfecting the grey prediction model theory system, and improving the efficiency of natural disasters and rescue.

Key words: grey theory, prediction model, grey isomerism data, emergency material demand

中图分类号:

N941.5

曾波, 孟伟, 刘思峰, 李川, 崔杰. 面向灾害应急物资需求的灰色异构数据预测建模方法[J]. 中国管理科学, 2015, 23(8): 84-91.

ZENG Bo, MENG Wei, LIU Si-feng, LI Chuan, CUI Jie. Prediction Modeling Method of Grey Isomerism Data for Calamity Emergency Material Demand[J]. Chinese Journal of Management Science, 2015, 23(8): 84-91.

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面向灾害应急物资需求的灰色异构数据预测建模方法

Prediction Modeling Method of Grey Isomerism Data for Calamity Emergency Material Demand

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