Neural fuzzy forecasting of the China Yuan to US dollar exchange rate - A swarm intelligence approach

研究成果: 書貢獻/報告類型會議論文篇章同行評審

5 引文 斯高帕斯(Scopus)

摘要

Exchange rate fluctuation has a significant effect on the risk of marketing business, economic development and financial stability. Accurate prediction for exchange rate may reduce commercial and economic risk arisen by exchange rate fluctuation. In this study, we propose an intelligent approach to the forecasting problem of the CNY-USD exchange rate, where a neuro-fuzzy self-organizing system is used as the intelligent predictor. For learning purpose, a novel hybrid learning method is devised for the intelligent predictor, where the well-known particle swarm optimization (PSO) algorithm and the recursive least squares estimator (RLSE) algorithm are involved. The proposed learning method is called the PSO-RLSE-PSO method. Experiments for time series forecasting of the CNY-USD exchange rate are conducted. For performance, the intelligent predictor is trained by several different methods. The experimental results show that the proposed approach has excellent forecasting performance.

原文???core.languages.en_GB???
主出版物標題Advances in Swarm Intelligence - Second International Conference, ICSI 2011, Proceedings
頁面616-625
頁數10
版本PART 1
DOIs
出版狀態已出版 - 2011
事件2nd International Conference on Swarm Intelligence, ICSI 2011 - Chongqing, China
持續時間: 12 6月 201115 6月 2011

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
號碼PART 1
6728 LNCS
ISSN(列印)0302-9743
ISSN(電子)1611-3349

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???event.eventtypes.event.conference???2nd International Conference on Swarm Intelligence, ICSI 2011
國家/地區China
城市Chongqing
期間12/06/1115/06/11

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