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.
Rough Sets the 3rd party logistic provider Support Vector Machine Evaluation
Yingchun Zhong Yinghong Zhong
Automatic College Guangdong University of Technology Donfengdong Road 729,Guangzhou City,Guangdong P School of Economic and Management Guangdong University of Technology Donfengdong Road 729,Guangzhou
国际会议
2007 IEEE International Conference on Automation and Lofistics
山东济南
英文
2007-08-18（万方平台首次上网日期，不代表论文的发表时间）