COMPARATIVE ANALYSIS OF BIFURCATION TIME SERIES(<Special Issue>Contribution to 21 Century Intelligent Technologies and Bioinformatics)

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概要

• 論文の詳細を見る

• The time series analysis (ARIMA models) is a good approach for identification of time series. But, if we have structural break in the time series, we cannot create only one model of time series. Further more, if we don't have enough data between two structural breaks, it's impossible to create valid time series models for identification of the time series. This paper explores the possibility of identification of the inflation process dynamics via of the system-theoretic, by means of both Box-Jenkins ARIMA methodologies and artificial neural networks. The structural break problem can be overcomed by using NN for system identification of unknown order with finite number of breaks.

• バイオメディカル・ファジィ・システム学会の論文

著者

• Vasant Pandian

  Faculty Of Tourism Hospitality

• Andreeski Cvetko

  Faculty of Tourism Hospitality

関連論文

• COMPARATIVE ANALYSIS OF BIFURCATION TIME SERIES(Contribution to 21 Century Intelligent Technologies and Bioinformatics)

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