基于主成分分析的仿真模型选择方法

doi:10.16182/j.issn1004731x.joss.201611005

系统仿真学报 ›› 2016, Vol. 28 ›› Issue (11): 2677-2683.doi: 10.16182/j.issn1004731x.joss.201611005

基于主成分分析的仿真模型选择方法

焦松, 毛少杰, 居真奇, 楚威

中国电科28所信息系统工程重点实验室,南京 210007

收稿日期:2014-07-15 修回日期:2014-08-11 出版日期:2016-11-08 发布日期:2020-08-13
作者简介:焦松(1985-),男,湖北大冶,博士,工程师,研究方向为系统仿真、效能评估;毛少杰(1963-),男,江苏,本科,研究员,研究方向为综合电子信息系统建模与仿真;楚威(1979-),男,江苏,硕士,高工,研究方向为综合电子信息系统建模与仿真。

Selection of Simulation Model Based on Principal Component Analysis

Jiao Song, Mao Shaojie, Ju Zhenqi, Chu Wei

Science and Technology on Information Systems Engineering Laboratory, The 28th Research Institute of China Electronics Technology Group Corporation, Nanjing 210007, China

Received:2014-07-15 Revised:2014-08-11 Online:2016-11-08 Published:2020-08-13

摘要/Abstract

摘要： 为了减少在参考输出完备时仿真模型选择的主观性,提出了基于主成分分析和灰色综合评判的仿真模型选择方法。依据数据特征将仿真输出分为静态、缓变和速变三类数据,并分别从多个方面充分刻画了各类数据之间的差异;基于主成分分析从多个相关的数据差异中提取出少数几个独立的主成分;利用灰色综合评判对主成分进行综合分析,进而得到仿真模型的选择结果。通过实例应用,表明了方法的有效性。

关键词: 仿真模型选择, 仿真模型可信性, 主成分分析, 灰色综合评判

Abstract: To reduce the subjectivity of result for selecting the simulation model when the reference output is complete, the selection method of simulation model based on principal component analysis and grey comprehensive evaluation was proposed. The simulation outputs were divided into three kinds of static data, gradual data and fast data according to the data feature, and the measure models of differences for each kind data were given. The correlation among the feature differences was eliminated via principal component analysis, and several independent principal components were gained. The independent principal components were integrated based on grey comprehensive evaluation, and the selection result of simulation model was gained. In the application, the validity of the method is showed.

Key words: selection of simulation model, credibility of simulation model, principal component analysis, grey comprehensive evaluation

中图分类号:

TP391.9

焦松, 毛少杰, 居真奇, 楚威. 基于主成分分析的仿真模型选择方法[J]. 系统仿真学报, 2016, 28(11): 2677-2683.

Jiao Song, Mao Shaojie, Ju Zhenqi, Chu Wei. Selection of Simulation Model Based on Principal Component Analysis[J]. Journal of System Simulation, 2016, 28(11): 2677-2683.

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基于主成分分析的仿真模型选择方法

Selection of Simulation Model Based on Principal Component Analysis

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