基于关联度的遗传-粗糙集约简算法  

Genetic-Rough Set Reduction Algorithm Based on Model Correlation

作　　者：何新华[1] 陆皖麟 陈庚申 

机构地区：[1]装甲兵工程学院信息工程系,北京100072

出　　处：《四川兵工学报》2015年第10期90-94,共5页Journal of Sichuan Ordnance

摘　　要：仿真模型的优化是仿真模型构建工作的重要组成部分。通过引入模型单元关联度的概念对传统模型约简算法进行改进,提出了一种基于模型单元关联度的遗传-粗糙集理论的仿真模型优化算法,很好地改善了聚合仿真模型的计算复杂度问题,并通过实例验证了算法的实用性。Optimization of the simulation model is an important part of the aggregation simulation model building. The concept of the model element correlation was introduced and the reduction algorithm for the model based on the genetic-rough set algorithm was designed, as well as to improve the computational com- plexity problem of aggregation simulation model. The algorithm design and implementation process were described in this paper, then the correctness of the algorithm was described. At last, applicability of this algorithm was proved by an example.

关 键 词：聚合仿真模型 模型优化 约简算法 遗传-粗糙集理论 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]