摘要
为了克服基本粗糙集理论确定权重的不足,提出一种新的基于粗糙集和粒子群优化算法的权重确定方法.该方法先利用粗糙集和粒子群优化算法对决策表进行属性约简,对约简后的决策表再用粗糙集方法计算属性权重.运用该算法对教师职业倦怠与压力数据进行分析,得到影响教师职业倦怠的各种压力因子的权重.研究结果表明,基于粗糙集和粒子群优化算法可以对决策表的权重进行有效的分析.
In order to overcome the shortcomings of the existing methods of determing weights based on the basic rough set theory,a new method based on rough set theory and particle swarm optimization algorithms is proposed. The rough set theory and particle swarm optimization algorithms is used for calculating the minimum attribute reduction of the decision table. Then the rough set theory is used for determing the weights for the reducted decision table. The algorithm is applied to got the weights of the stress factors that influence job burnout among teachers. Experiments show the proposed algorithm is an effective method of analyzing weights of the decision table.
出处
《闽江学院学报》
2010年第5期74-78,135,共6页
Journal of Minjiang University
关键词
权重
粗糙集
粒子群优化算法
属性约简
weight
rough set
particle swarm optimization
attribute reduction
