Railway freight demand are predicted and analyzed by using multidimensional association rule based on Apriori algorithm. At the same time, Three correlation models—goods-weight-transport distance, goods-weight-arrival railroad, goods-weight-arrival province are established by using data mining software Clementine to analysis some railway freight invoice of a railway bureau. Finally, some association rules which are helpful for railway freight demand analysis are obtained. It proved that using multidimensional association rules to analyze the railway freight demand is rational and feasible.
Railway Freight Demand Analysis Based on Multidimensional Association Rules Mining
Fifth International Conference on Transportation Engineering ; 2015 ; Dailan, China
ICTE 2015 ; 2075-2081
2015-09-25
Conference paper
Electronic Resource
English
Association Rules Mining for Railway Accident Causes Based on Improved HFACS
Springer Verlag | 2023
|Engineering Index Backfile | 1903
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