Study on the Evaluation Model of the 3rd Party Logistic Provider Based on Rough Sets and Support Vector Machine

In this paper, we discretized the original data by self organized mapping (SOM) neural network based on the characteristic attributes of the 3rd party logistic providers. Decision table was achieved. The redundant attributes were removed by rough sets (RS) in order to get the simplified decision table. Then we trained the support vector machine (SVM) with the simplified decision table to construct the model that could embody the the mapping relationship between the characteristic attributes and the evaluation grades. The test result shows that the specific characteristic attributes of the 3rd party logistic providers from the same area can be distilled after processing the data with RS. These characteristic attributes' influence on the evaluation grades is determined by the core mined from the original data. Besides, the establishment of SVM model provides a new method that can reduce the calculation work of the grade evaluation on a new logistic service provider. Furthermore, this method can also store and reuse the experts' experiences of evaluation.