ARIMA model estimated by particle swarm optimization algorithm for consumer price index forecasting

Hongjie Wang, Weigang Zhao*

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

26 引用 (Scopus)

摘要

This paper presents an ARIMA model which uses particle swarm optimization algorithm (PSO) for model estimation. Because the traditional estimation method is complex and may obtain very bad results, PSO which can be implemented with ease and has a powerful optimizing performance is employed to optimize the coefficients of ARIMA. In recent years, inflation and deflation plague the world moreover the consumer price index (CPI) which is a measure of the average price of consumer goods and services purchased by households is usually observed as an important indicator of the level of inflation, so the forecast of CPI has been focused on by both scientific community and relevant authorities. Furthermore, taking the forecast of CPI as a case, we illustrate the improvement of accuracy and efficiency of the new method and the result shows it is predominant in forecasting.

源语言英语
主期刊名Artificial Intelligence and Computational Intelligence - International Conference, AICI 2009, Proceedings
48-58
页数11
DOI
出版状态已出版 - 2009
已对外发布
活动International Conference on Artificial Intelligence and Computational Intelligence, AICI 2009 - Shanghai, 中国
期限: 7 11月 20098 11月 2009

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
5855 LNAI
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议International Conference on Artificial Intelligence and Computational Intelligence, AICI 2009
国家/地区中国
Shanghai
时期7/11/098/11/09

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