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  • 标题:A COMPARISON BETWEEN THREE PREDICTIVE MODELS OF COMPUTATIONAL INTELLIGENCE
  • 本地全文:下载
  • 作者:DUMITRU CIOBANU ; BAR MARY VIOLETA
  • 期刊名称:Analele Universităţii Constantin Brâncuşi din Târgu Jiu : Seria Economie
  • 印刷版ISSN:1844-7007
  • 出版年度:2013
  • 期号:6
  • 页码:62-74
  • 语种:English
  • 出版社:Academica Brâncuşi
  • 摘要:Time series prediction is an open problem and many researchers are trying to find new predictive methods and improvements for the existing ones.Lately methods based on neural networks are used extensively for time series prediction.Also,support vector machines have solved some of the problems faced by neural networks and they began to be widely used for time series prediction.The main drawback of those two methods is that they are global models and in the case of a chaotic time series it is unlikely to find such model.In this paper it is presented a comparison between three predictive from computational intelligence field one based on neural networks one based on support vector machine and another based on chaos theory.We show that the model based on chaos theory is an alternative to the other two methods.
  • 关键词:time series prediction;neural networks;support vector machines;chaos theory;exchange rate.
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