Research on Risk Index Reduction in Chain Retail Enterprises

Abstract:

A risk index reduction model based on rough set theory is put forward, because of the risk index of distribution of supply chain in retail enterprises is large and much redundant, and it is difficult to determine the decision rules through the complex index. Naive Scaler algorithm is used to discrete the risk index data, then an algorithm of attribute reduction based on mutual information entropy is used in decision table to reduce index and build risk index system optimal model. The results of example show that this system can reduce the redundancy index of risk index system fast and efficient and provide the basis for making the risk decision.

• Periodical: Applied Mechanics and Materials (Volumes 278-280)
• Pages: 2183-2186
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.278-280.2183
• Online since: January 2013
• Authors: Mei Luan Cui, Hui Yan Zhang, Hong Xue
• Keywords: Discretization, Distribution Risk, Information Entropy, Rough Set (RS)

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