Computer Science ›› 2012, Vol. 39 ›› Issue (Z6): 331-334.
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Abstract: This study was mainly to predict the risks for R/M integrated supply chain against its characteristics by Apriori algorithm. First it built risks database according to analyze the ingredient characteristics of the supply chain risk, extracting the relevant information from the risk database. Then dealt it with Apriori algorithm, finding the regularity of risks outbreak through the relevance between the risks. Used improving candidates' extraction method to reduce the space complexity of Apriori algorithm to improve its operational efficiency. Extracted the results of Apriori algorithm to explore the association rules between the risk events and the risk results. I}hen analyzed the results to complete the R/M integrated supply chain risk prediction. And the method could be proved to be feasible through simulation experiment.
Key words: Apriori algorithm, Improve, R/M integrated supply chain, Association rules, Risk prediction, Prove
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