Information Technology and Applications, International Forum on
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Abstract

Railway passenger traffic volume forecasting is an important responsibity of the railway transportation management departments, railway passenger traffic volumes are influenced by multiple factors, and the action mechanisms of these factors are usually unable to be described by accurate mathematical linguistic forms, so the theory and method of railway passenger traffic forecasting remain a focus in research all the time. The paper analyzes data using rough set theory. Combining rough set theory and the characteristics of railway passenger traffic volume data, we bring forward a forecasting model of railway passenger traffic volume using rough set theory. Through setting up, hybrid clustering method of discretization and reduction decision table, a rule Set concerning forecasting of railway passenger traffic volumes is achieved——rough set forecasting model.
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