Selection of Simulation Model Based on Principal Component Analysis

doi:10.16182/j.issn1004731x.joss.201611005

Abstract

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

CLC Number:

TP391.9

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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