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• W1769767526 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." @default.
• W1769767526 created "2016-06-24" @default.
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• W1769767526 date "2016-02-01" @default.
• W1769767526 modified "2023-10-18" @default.
• W1769767526 title "Multifractal detrended fluctuation analysis based on fractal fitting: The long-range correlation detection method for highway volume data" @default.
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• W1769767526 doi "https://doi.org/10.1016/j.physa.2015.10.073" @default.
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