Prediction of China's urban residents consumption level based on Grey GM (1, 1)-BP neural network

Dongjuan Guo; Yan Zou

doi:10.2495/SSSIT20130261

Prediction of China's urban residents consumption level based on Grey GM (1, 1)-BP neural network

Dongjuan Guo
, Yan Zou

经济管理学院

Northwestern Polytechnical University Xian

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

1 引用（Scopus）

摘要

Household consumption expenditure is not only the important power to drive economic growth but also the sign to measure the level of the residents' lives. It has very important practical significance to predict consumer spending effectively. By means of contrast, this paper found that both GM (1, 1) and BP neural network models have a large error when they are used separately. Thus, China's urban consumption level from 2011 to 2014 forecasts by integrating Grey model with BP neural network, and the prediction results show that per capita of urban consumption level will reach 2487.61 Yuan in 2014.

源语言	英语
主期刊名	Advances in Services Science and Services Information Technology
出版商	WITPress
页	193-199
页数	7
ISBN（印刷版）	9781845648671
DOI	https://doi.org/10.2495/SSSIT20130261
出版状态	已出版 - 2014
活动	2013 International Conference on Services Science and Services Information Technology, SSSIT 2013 - Wuhan, 中国期限: 7 11月 2013 → 8 11月 2013

出版系列

姓名	WIT Transactions on Information and Communication Technologies
卷	52
ISSN（印刷版）	1743-3517

会议

会议	2013 International Conference on Services Science and Services Information Technology, SSSIT 2013
国家/地区	中国
市	Wuhan
时期	7/11/13 → 8/11/13

联合国可持续发展目标

此成果有助于实现下列可持续发展目标：

可持续发展目标 8 体面工作和经济增长

访问文件

10.2495/SSSIT20130261

其它文件与链接

链接到 Scopus 的出版物

引用此

@inproceedings{26b9eb1600d944f1ba8215f6a206170a,

title = "Prediction of China's urban residents consumption level based on Grey GM (1, 1)-BP neural network",

abstract = "Household consumption expenditure is not only the important power to drive economic growth but also the sign to measure the level of the residents' lives. It has very important practical significance to predict consumer spending effectively. By means of contrast, this paper found that both GM (1, 1) and BP neural network models have a large error when they are used separately. Thus, China's urban consumption level from 2011 to 2014 forecasts by integrating Grey model with BP neural network, and the prediction results show that per capita of urban consumption level will reach 2487.61 Yuan in 2014.",

keywords = "BP neural network, Grey model, Household consumption expenditure, Residual modification",

author = "Dongjuan Guo and Yan Zou",

year = "2014",

doi = "10.2495/SSSIT20130261",

language = "英语",

isbn = "9781845648671",

series = "WIT Transactions on Information and Communication Technologies",

publisher = "WITPress",

pages = "193--199",

booktitle = "Advances in Services Science and Services Information Technology",

address = "英国",

note = "2013 International Conference on Services Science and Services Information Technology, SSSIT 2013 ; Conference date: 07-11-2013 Through 08-11-2013",

}

Guo, D & Zou, Y 2014, Prediction of China's urban residents consumption level based on Grey GM (1, 1)-BP neural network. 在 Advances in Services Science and Services Information Technology. WIT Transactions on Information and Communication Technologies, 卷 52, WITPress, 页码 193-199, 2013 International Conference on Services Science and Services Information Technology, SSSIT 2013, Wuhan, 中国, 7/11/13. https://doi.org/10.2495/SSSIT20130261

Prediction of China's urban residents consumption level based on Grey GM (1, 1)-BP neural network. / Guo, Dongjuan; Zou, Yan.
Advances in Services Science and Services Information Technology. WITPress, 2014. 页码 193-199 (WIT Transactions on Information and Communication Technologies; 卷 52).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Prediction of China's urban residents consumption level based on Grey GM (1, 1)-BP neural network

AU - Guo, Dongjuan

AU - Zou, Yan

PY - 2014

Y1 - 2014

N2 - Household consumption expenditure is not only the important power to drive economic growth but also the sign to measure the level of the residents' lives. It has very important practical significance to predict consumer spending effectively. By means of contrast, this paper found that both GM (1, 1) and BP neural network models have a large error when they are used separately. Thus, China's urban consumption level from 2011 to 2014 forecasts by integrating Grey model with BP neural network, and the prediction results show that per capita of urban consumption level will reach 2487.61 Yuan in 2014.

AB - Household consumption expenditure is not only the important power to drive economic growth but also the sign to measure the level of the residents' lives. It has very important practical significance to predict consumer spending effectively. By means of contrast, this paper found that both GM (1, 1) and BP neural network models have a large error when they are used separately. Thus, China's urban consumption level from 2011 to 2014 forecasts by integrating Grey model with BP neural network, and the prediction results show that per capita of urban consumption level will reach 2487.61 Yuan in 2014.

KW - BP neural network

KW - Grey model

KW - Household consumption expenditure

KW - Residual modification

UR - https://www.scopus.com/pages/publications/84896053456

U2 - 10.2495/SSSIT20130261

DO - 10.2495/SSSIT20130261

M3 - 会议稿件

AN - SCOPUS:84896053456

SN - 9781845648671

T3 - WIT Transactions on Information and Communication Technologies

SP - 193

EP - 199

BT - Advances in Services Science and Services Information Technology

PB - WITPress

T2 - 2013 International Conference on Services Science and Services Information Technology, SSSIT 2013

Y2 - 7 November 2013 through 8 November 2013

ER -

Prediction of China's urban residents consumption level based on Grey GM (1, 1)-BP neural network

摘要

出版系列

会议

联合国可持续发展目标

访问文件

其它文件与链接

指纹

引用此