Construction and application of optimized GM(1, 1) power model incorporating self-memory principle

被引：1

作者：

Guo, Xiao-Jun ^{[1
,2
]}

Liu, Si-Feng ^{[2
]}

Fang, Zhi-Geng ^{[2
]}

Wu, Li-Feng ^{[2
]}

机构：

[1] School of Science, Nantong University, Nantong

[2] College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing

来源：

Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2015年 / 37卷 / 01期

关键词：

Enrolment rate; GM(1; 1) power model; Grey system; Self-memory principle;

D O I：

10.3969/j.issn.1001-506X.2015.01.19

中图分类号：

学科分类号：

摘要：

As for the fluctuating sequences characterized by saturated condition or single-peak, whose development and variation are subject to multi-faceted factors, the coupling prediction model combining the self-memory principle and the optimized GM(1, 1) power model has been constructed based on the grey GM(1, 1) power model in order to improve prediction accuracy. The traditional grey model's weakness as being sensitive to the initial value can been overcomed by the self-memory principle of dynamic system. The results indicate that the newly-established model can take full advantage of the systematic multi-time historical data. It extends the grey model's application span, which possesses higher accuracy of simulation and forecast than the traditional optimized GM(1, 1) power model. Finally, the superiority and effectiveness of this proposed model have been proved by the case of Chinese senior high school students' enrolment rate into higher education institutions. ©, 2015, Chinese Institute of Electronics. All right reserved.

引用

页码：117 / 122

页数：5

共 18 条

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