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to support the decision-making of traffic control effectively, an association rules algorithm based on data cube was proposed in the paper. First, data cube from database was set up. Then frequent item-set which satisfied the minimum support on data cube was mined out. Furthermore, association rules of frequent item-set were obtained. Finally, redundant association rules were wiped off through the relative method. The algorithm had two advantages, the first was that the executing time of the algorithm was short while searching for the frequent item- set; the second was that the rules' interest degree was high. The algorithm was also used intelligence traffic system and a few effective patterns were obtained. The results manifested that the algorithm was effective in decision- making support of traffic control.
to support the decision-making of traffic control effectively, an association rules algorithm based on data cube was proposed in the paper. First, data cube from database was set up. Then frequent item-set which satisfied the minimum support on data cube was mined out. Furthermore, association rules of frequent item-set were obtained. Finally, redundant association rules were wiped off through the relative method. The algorithm had two advantages, the first was that the executing time of the algorithm was short while searching for the frequent item- set; the second was that the rules' interest degree was high. The algorithm was also used intelligence traffic system and a few effective patterns were obtained. The results manifested that the algorithm was effective in decision- making support of traffic control.
Research on Application of Association Rule Algorithm in Intelligence Transportation System
01.06.2006
4126845 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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