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Analysis on Fractal Features of Labor Productivity of Manufacturing Industry Time Series

According to the data of manufacturing industry, phase-space of time series was reconstructed based on the phase-space reconstruction theory. The fractal features of labor productivity of manufacturing industry time series were studied by using G-P (Grassberger-Procaccia) arithmetic,correlation dimension of labor…

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According to the data of manufacturing industry, phase-space of time series was reconstructed based on the phase-space reconstruction theory. The fractal features of labor productivity of manufacturing industry time series were studied by using G-P (Grassberger-Procaccia) arithmetic,correlation dimension of labor productivity of manufacturing industry time series and delay time were calculated out. The results indicate that the dynamic system of labor productivity of manufacturing industry has a steady correlation dimension of 0.948 after the embedded dimension comes to 6, which explains that at least one factor is controlling the dynamic changes of accidents time series, and the effective freedom is 6. The research provides much reference value for establishing comparative evaluation models and management system of labor productivity of manufacturing industry time series.
http://www.ivypub.org/msr/paperInfo.aspx?ID=2285

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According to the data of manufacturing industry, phase-space of time series was reconstructed based on the phase-space reconstruction theory. The fractal features of labor productivity of manufacturing industry time series were studied by using G-P (Grassberger-Procaccia) arithmetic,correlation dimension of labor productivity of manufacturing industry time series and delay time were calculated out. The results indicate that the dynamic system of labor productivity of manufacturing industry has a steady correlation dimension of 0.948 after the embedded dimension comes to 6, which explains that at least one factor is controlling the dynamic changes of accidents time series, and the effective freedom is 6. The research provides much reference value for establishing comparative evaluation models and management system of labor productivity of manufacturing industry time series.
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