The effective classification of cloud manufacturing resources is a prerequisite for resource service packaging and subsequent manufacturing resource service retrieval. And it aims for the classification of high-dimensional features and multi-category processing equipment resources. At first this paper extracted resource attribute characteristic values and performed vectorization processing by XML documents which described the characteristics of cloud manufacturing resource attributes. Then, based on the SVM algorithm, it established an automatic classification and prediction algorithm model for manufacturing resources. In order to improve the classification efficiency of the SVM classification algorithm, this paper introduced the SMO algorithm, and it used the grid search to find the optimal parameters of the SVM algorithm for optimizing the effect of the SVM algorithm. Finally, based on the original equipment information of a certain equipment resource set, the paper conducted a classification experiment on different processing equipment to verify the validity and feasibility of the classification model.

[2021-04-05] Printed Article /doc/2020.03.0139/v2