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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 6
1744-1747,1758

Min-Min algorithm for optimizing moving average prediction model

Xu Qili
School of Economics, Jiangxi University of Finance & Economics, Nanchang 330013, China
DOI: 10.19734/j.issn.1001-3695.2020.06.0163

Abstract

After improvement of one-time moving average model, this paper designed a Min-Min algorithm to optimize the moving average prediction model based on the principle of the least summation of the local residual squares for making the application of moving average prediction technology change from specialization to popularization, from artificial to intelligent. Firstly, it respectively selected the optimal number of moving items of the one-time moving average model and the double-time moving average model. Then, it selected the optimal number of moving times between the optimal one-time moving average model and the optimal two-time moving average model. Finally, based on the optimized moving average model it carried out the point prediction and interval prediction for the future first period. Compared with the existing algorithms, the progress of this moving average method was mainly reflected in: a) Replaced expert practice, which first selected the number of moving items and then the number of moving times, by program algorithm, which first selected the number of moving times and then the number of moving items, so as to improve the implementation of moving average method from semi-automatic artificial prediction to full-automatic intelligent prediction. b) Improved the current one-time moving average model, so as to greatly improve the prediction ability of one-time moving average method. c) Further put forward interval prediction model based on the point prediction model, so as to improve and enrich the prediction report of moving average prediction method.

Foundation Support

北京市社科基金重点项目(18GLA003)
北京市教委科研项目(SM201910038003)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.06.0163
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 6
Section: Algorithm Research & Explore
Pages: 1744-1747,1758
Serial Number: 1001-3695(2021)06-026-1744-04

Publish History

[2021-06-05] Printed Article

Cite This Article

徐齐利. 一种优选移动平均预测模型的Min-Min算法 [J]. 计算机应用研究, 2021, 38 (6): 1744-1747,1758. (Xu Qili. Min-Min algorithm for optimizing moving average prediction model [J]. Application Research of Computers, 2021, 38 (6): 1744-1747,1758. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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