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- W2389977054 abstract "Considering that traditional credit evaluation methods mostly belong to the category of static credit evaluation,a dynamic credit evaluation method which integrates SOM and K-means algorithm is proposed to deal with this problem. Firstly,the paper introduces the basic model of dynamic credit evaluation,and employs E-TOPSIS to cluster the static information at single time points. Next,combining advantages of both SOM algorithm and K-means algorithm,the paper puts forward the principle and steps of SOM-k-means algorithm; then the integrated clustering algorithm is utilized to cluster the evaluation alternatives and determine the corresponding credit rating of them. Finally,to verify the effectiveness of the method proposed,an example is employed. The example shows that the problem of information mutation under static situation can be greatly solved by the method proposed." @default.
- W2389977054 created "2016-06-24" @default.
- W2389977054 creator A5009891585 @default.
- W2389977054 date "2014-01-01" @default.
- W2389977054 modified "2023-09-27" @default.
- W2389977054 title "Research on a Dynamic Credit Evaluation Method Integrating SOM and K-means Clustering Algorithm" @default.
- W2389977054 hasPublicationYear "2014" @default.
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