基于多维关联抽样的区间数灰靶决策模型及其应用

传统区间数灰靶决策模型忽略了指标区间分布及指标间相关性对于方案优劣评价的重要影响,且赋权过程中存在一定的模糊误差.针对上述不足,本文提出了基于多维关联抽样的区间数灰靶决策模型,通过全面考虑指标空间边界及空间内部的多维联合概率密度分布情况,弱化了指标极值对于决策结果的影响;并引入模糊集值统计方法确定指标权重,将灰靶决策模型权重由实数序列拓展到区间数序列,减小了专家判定过程中的模糊误差.以潘口水库汛期运行水位抬升方案决策为研究案例,将改进模型与传统模型进行比较,结果表明,改进后的模型能够更有效地考虑区间内部数据特点及指标间的关联程度,区间数权重的设定也更合理客观.

Interval number grey target decision-making model based on multi-dimensional association sampling and its application

The existing interval number grey target decision-making model ignores the important influence of interval distribution and the correlation between the indicators in scheme evaluation. And there are some fuzzy errors when setting the weight of indicators. In order to solve the above problems, this paper proposes an interval number grey target decision-making model based on multi-dimensional association sampling, taking into account the multi-dimensional joint probability density distribution of index space and its boundary, and weakens the impact of extreme index value on the decision-making results. In addition, this paper determines the weight of index by using set-valued statistical method, expanding the weight of grey target model from the real number sequence to the interval number sequence, and reducing the fuzzy error in the experts' judgment process. This improved model is applied to Pankou reservoir for the decision-making of water level operating in flood season. Compared with traditional models, the improved model fully considers the characteristics of interval data and the correlation between the indicators. Meanwhile, the setting of interval number weight is more scientific and reasonable.