Electric equipment breakdown is mainly caused by Partial Discharge (PD), so identification and diagnosis of PD are of great importance to the maintenance of electric equipment. This research analyzes the field TEV data of PD using SVM theory and establishes a model to detect and analyze PD, with related experiments verifying the validity of the model. According to the experience on site, we redesign the evaluation criteria and build a new model to guarantee that the identification rate reaches over 80%. The comparative experiment indicates that the SVM method proposed in this paper performs better on PD detection than BP Neural Network, laying foundation for further research.

In order to improve evaluation of e-learning systems, this paper introduces a model of learning content recommendation based on grey systems theory and gray relational analysis algorithms. This work analyses e-learners behaviours of e-learning and log files of the platform, find the most resemble e-learner, use his/her learning trail to recommend e-learning resources. The gray system theory can solve the problem of lacking historical data. And this model reach the purpose of selecting individual teaching contents intelligently.