2011•Kongzhi yu jueceRequires access

Research of modeling of multi-variable non-equidistant MGM(1,m) model

Pingping Xiong, Yaoguo Dang, Zhu Hui

Open publisher page 11 citations

Abstract

Based on the problem of simulation and prediction of the non-equidistant raw data series for the multi-variable with interaction, the multi-variable MGM(1,�� ) model in the case of non-equidistance is modeled and the non-equidistance MGM(1,�� ) model is constructed in order to improve the accuracy of simulation and prediction. The simulation and prediction accuracy is proved to be higher in multi-variable non-equidistant MGM(1,�� ) model than in single-variable non- equidistant GM(1,1) models according to an application. The proposed model is suitable in non-equidistant modeling and equidistant modeling, thus, non-equidistant model has broad applying value.

About this research paper

What this paper is about

Based on the problem of simulation and prediction of the non-equidistant raw data series for the multi-variable with interaction, the multi-variable MGM(1,�� ) model in the case of non-equidistance is modeled and the non-equidistance MGM(1,�� ) model is constructed in order to improve the accuracy of simulation and prediction. The simulation and prediction accuracy is proved to be higher in multi-variable non-equidistant MGM(1,�� ) model than in single-variable non- equidistant GM(1,1) models according to an application. The proposed model is suitable in non-equidistant modeling and equidistant modeling, thus, non-equidistant model has broad applying value.

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OpenAlex reports 11 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Based on the problem of simulation and prediction of the non-equidistant raw data series for the multi-variable with interaction, the multi-variable MGM(1,�� ) model in the case of non-equidistance is modeled and the non-equidistance MGM(1,�� ) model is constructed in order to improve the accuracy of simulation and prediction. The simulation and prediction accuracy is proved to be higher in multi-variable non-equidistant MGM(1,�� ) model than in single-variable non- equidistant GM(1,1) models according to an application. The proposed model is suitable in non-equidistant modeling and equidistant modeling, thus, non-equidistant model has broad applying value.

Key concepts: Equidistant, Variable (mathematics), Mathematics, Algorithm, Applied mathematics, Geometry, Mathematical analysis

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