A New Data Transformation Method and Its Empirical Research Based on Inverted Cycloidal Kinetic Model | Zendy

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A New Data Transformation Method and Its Empirical Research Based on Inverted Cycloidal Kinetic Model

Author(s) -

Zhang Mao

Publication year - 2015

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2015.07.020

Subject(s) - computer science , transformation (genetics) , cycloid , nonlinear system , series (stratigraphy) , algorithm , field (mathematics) , time series , autoregressive integrated moving average , mathematics , mathematical optimization , machine learning , physics , geology , paleontology , biochemistry , chemistry , reducer , quantum mechanics , pure mathematics , gene , thermodynamics

This paper represented a reasonable method of data transformation in economic field based on inverted cycloidal kinetic model. We first apply the inverted cycloidal kinetic model to the data transformation in time series and then linearize the nonlinear data. This method fully considers the most deceleration characteristics and the isochronism of inverted cycloid and the equivalent substitution mechanism of transiting the non-linear curve into a linear one, which is a useful innovation compared with the traditional data transformation method. Finally, the ARIMA-GARCH model is established using the linearized data. The method shows that the time series analysis results are more accurate based on this kind of data processing in comparison with the traditional one

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