Eliminating the Correlation of Multi-Attribute Evaluation Based on Equivalence Class Partition

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Eliminating the Correlation of Multi-Attribute Evaluation Based on Equivalence Class Partition

更新时间：2025-07-09

- Eliminating the Correlation of Multi-Attribute Evaluation Based on Equivalence Class Partition
- Vol. 43, Issue 4, Pages: 26-29(2009)
- 作者机构：
  
  西安交通大学计算机系统结构与网络研究所,西安,710049
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP393
- Online First：10 April 2009，
  
  Published：2009
- 稿件说明：
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Eliminating the Correlation of Multi-Attribute Evaluation Based on Equivalence Class Partition[J]. 2009, 43(4): 26-29.
DOI：

Eliminating the Correlation of Multi-Attribute Evaluation Based on Equivalence Class Partition[J]. 2009, 43(4): 26-29. DOI：

摘要

针对多属性评价中消除评价指标之间相关性的问题

从指标的组成出发

将评价指标分为元指标和合成指标

并分别给出了线性合成指标和非线性合成指标的相关度计算方法.借鉴Dijkstra算法

提出了基于指标等价类的合成指标动态约简算法

即通过等价类划分来缩小参与约简的指标范围

并充分利用前一次约简以求得最终指标约简的结果.仿真实验表明

随着指标数目的增多

所提算法比直接使用改进Dijkstra算法进行指标约简的运行时间要少

可提高大规模指标约简的执行效率.

Abstract

To eliminate the correlation among evaluation indexes

the evaluation indexes are divided into element indexes and synthetic indexes. Then the methods of calculating the correlation degree of linear synthetic indexes and nonlinear synthetic indexes are given. An algorithm of eliminating the correlation of synthetic indexes based on index equivalence class is proposed in terms of Dijkstra algorithm. The reduction ranges of evaluation indexes can be reduced

and the anterior reduction results are used to increase the efficiency. Comparisons with the modified Dijkstra index reduction algorithm show that the proposed algorithm based on equivalence class spends less running time. The more indexes there exist

the more efficient the proposed algorithm is.

关键词

Keywords

references

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