Industrial Output Prediction Research Based on Combination Forecasting Model

Computer & Telecommunication

2015, Vol. 1

Issue (3): 62-64 DOI:

Current Issue | Archive | Adv Search

Industrial Output Prediction Research Based on Combination Forecasting Model

Li Zhipeng¹，LiWei²，Liu Zhijie¹,³

(1. Key Laboratory of Information and Computing Science of Guizhou Province, Guizhou Normal University, Guiyang 550001 2.Guizhou Province Development and Reform Commission 3. Network and Information Center of Guizhou Normal University

Download:

PDF(0KB)
Export: BibTeX | EndNote (RIS)

Abstract For predicting complex economic data, selecting suitable prediction model is the key to improve the prediction accuracy. This paper uses the combination of grey model and regression model to predict the high technology industry output in Guizhou. Taking the advantages of this combination model can improve the linear regression model by considering the exponential growth and improve the grey model by considering the linear factor, so as to achieve the goal of improving the prediction accuracy. And the computer numerical simulation results show the effectiveness of the combination forecasting model.

Published: 08 November 2017

ZTFLH:

TP39

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Li Zhipeng
	LiWei
	Liu Zhijie

Cite this article:

Li Zhipeng, LiWei, Liu Zhijie. Industrial Output Prediction Research Based on Combination Forecasting Model. Computer & Telecommunication, 2015, 1(3): 62-64.

URL:

http://www.computertelecom.com.cn/EN/ OR http://www.computertelecom.com.cn/EN/Y2015/V1/I3/62

[1]	ZHANG Gang , CHEN Jia-lian, SONG Jian, GUO Jun-qi, ZHOU Chen-rui. Chinese Landscape Painting Automated Generation Model Based on Generative Adversarial Networks[J]. 电脑与电信, 0, (): 1-.
[2]	ZHANG Gang , CHEN Jia-lian, SONG Jian, GUO Jun-qi, ZHOU Chen-rui. Chinese Landscape Painting Automated Generation Model Based on Generative Adversarial Networks[J]. 电脑与电信, 2020, 1(3): 1-.
[3]	LI Jia-Qi SU Li-na. Research on Science and Technology Information Service platform of Comprehensive Sci-tech Journals based on Mobile Interconnection and its Architecture[J]. 电脑与电信, 2019, 1(6): 42-46.
[4]	LI Bo. Application of Grubbs Criterion in Project Evaluation System[J]. 电脑与电信, 2019, 1(6): 61-63.
[5]	ZHANG Hui-fang ZONG Cai-le ZHANG Xiao-lin. Chinese Text Feature Classification Based on Distributed Framework[J]. 电脑与电信, 2019, 1(5): 1-7.
[6]	WU Hai-jun. Research on Personal Information Security on Internet[J]. 电脑与电信, 2019, 1(5): 37-39.
[7]	GAO Pan LIN Li. Discussion on the Omni-directional Defense for Virus Defense[J]. 电脑与电信, 2019, 1(5): 45-47.
[8]	LIU Xiao-qiang. Design and Implementation of Vehicle Search Engine in Insurance System Based on ElasticSearch[J]. 电脑与电信, 2019, 1(5): 51-55.
[9]	DAI Xiao-fang. A Moving Target Detection Technology Based on Compressed Sensing[J]. 电脑与电信, 2019, 1(5): 64-67.
[10]	HUANG Xiao-hua. Analysis on the Head of the Web[J]. 电脑与电信, 2019, 1(5): 75-77.
[11]	YI Li-zhi. Research and Application of Image Clarity Processing in Haze Environment[J]. 电脑与电信, 2019, 1(4): 1-4.
[12]	XIN Yan-shuang CHEN Si HAN Xiu-yuan. A Tele-collaboration Implementation Scheme Based on ICE[J]. 电脑与电信, 2019, 1(4): 61-65.
[13]	CHEN Rong-zheng. Research on College Information Service Platform Based on Web Crawler and Wechat[J]. 电脑与电信, 2019, 1(3): 13-16.
[14]	FANG Yong. Research on the IPv6 Remote Network Monitoring and Communication System[J]. 电脑与电信, 2019, 1(3): 62-65.
[15]	GOU Ting-ting YAN Jin HUANG Ling-xiao LIU Li-bo. Image Defogging Technology Based on Dark Channel Prior[J]. 电脑与电信, 2019, 1(1-2): 5-8.

Viewed

Full text

Abstract

Cited

Shared

Discussed