Multifractal detrended fluctuation analysis based on fractal fitting: The long-range correlation detection method for highway volume data

Meifeng Dai, Jie Hou and Dandan Ye

Physica A: Statistical Mechanics and its Applications, 2016, vol. 444, issue C, 722-731

Abstract: In this paper, we investigate the traffic time series for volume data observed on the Guangshen highway. We introduce a multifractal detrended fluctuation analysis based on fractal fitting (MFDFA-FF), which is one of the most effective methods to detect long-range correlations of time series. Through effective detecting of long-range correlations, highway volume can be predicted more accurately. In order to get a better detrend effect, we use fractal fitting to replace polynomial fitting in detrend process, the result shows that fractal fitting can get a better detrend effect than polynomial fitting and the MFDFA-FF method can achieve a more accurate research result. Then we introduce the Legendre spectrum to detect the multifractal property characterized by the long-range correlation and multifractality of Guangshen highway volume data.

Keywords: Fractal interpolation; Fractal fitting; MFDFA-FF; Legendre spectrum; Long-range correlation (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:444:y:2016:i:c:p:722-731

DOI: 10.1016/j.physa.2015.10.073

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