项目名称: 多源信息集结条件下灰色异构数据序列预测建模方法及其应用研究
项目编号: No.71271226
项目类型: 面上项目
立项/批准年度: 2013
项目学科: 管理科学
项目作者: 曾波
作者单位: 重庆工商大学
项目金额: 51万元
中文摘要: 统计对象的复杂性是导致统计数据不确定性的主要因素,多源信息集结尽管对提高复杂环境下统计数据的可信度具有重要作用,但该方法中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。本项目拟应用灰色系统建模技术对灰色异构数据序列预测建模方法展开研究。首先,研究复杂条件下的多源信息集结方法,探究灰色异构数据"核和灰度"的计算方法,建立灰色异构数据的代数运算与矩阵计算规则;然后,研究灰色异构数据预测模型建模机理与参数优化算法,在此基础上对灰色异构波动序列预测模型,以及多变量灰色异构数据预测模型进行拓展研究;最后,将上述理论成果应用于自然灾害应急救援人员和物资需求的预测,并开发需求预测软件,以实现救援人员需求类型和人数、应急物资需求种类和数量的快速预测,为救援机构实施应急资源调度提供理论依据。本项目研究成果对丰富与发展灰色预测理论,提高自然灾害应急救援效率具有积极意义。
中文关键词: 灰色理论;灰色异构时序数据;灰色预测模型;灾害应急物资需求预测;灰色预测建模软件
英文摘要: The complexity of statistical objects is an important factor that leads to the uncertainty of statistical data. Although the multiple-source information aggregation plays an important role in improving the reliability of statistical data under a complex environment,the information channel of multi-sources of its can easily cause the inconformity and incompatible types of the aggregation information data and produce a isomerism data sequence. This project is aimed at studying grey isomerism data sequence forecast modeling method through the grey system modeling technology. Firstly,study the methods of multiple-source information aggregation under a complex environment,and research the "kernel degree of greyness" modeling method as well as build the rules of algebraic operation and matrix calculation. Then,on the basis of studying the modeling mechanism of grey isomerism data and parameter optimization, do expand research on single variable grey isomerism fluctuation sequence prediction model and multivariable grey isomerism data sequence forecast model. Finally,by adopting the use of the achievements of above study ,forecast the demand of natural disaster emergency rescue workers and goods and materials ,and develop demanding forecasting software ,to realize fast forecast of the demanding types and numbers of th
英文关键词: Grey theory;Time sequence data of grey isomerism;Grey prediction model;Demand forecasting for Disaster emergency supplies;Grey forecasting modeling software