Implementation of support-vector machine algorithm to develop a model for electronic commerce energy regulatory system

In the current stage, China has paid special focuses to the data and information utilization of the Electronic-commerce (e-commerce) energy regulatory system. However, it is difficult to guarantee the scientific data information management of the energy regulatory system at present. It was considering how to use the scientific framework for data mining has been the recent hot spot. Under this condition, this manuscript analysis the e-commerce energy regulatory system model based on data mining. This paper begins with the discussions on the current models of the energy regulatory system at home and abroad, enhances the methodology combined with the shortage of data mining, and then applies support-vector machine (SVM) algorithm in the e-commerce energy regulatory model. The experimental analysis shows that the revised SVM algorithm can realize the objective evaluation of regulatory efficiency based on data mining and can lead to the optimal strategy according to the scenarios in the actual application steps of the energy supervision system. The performance is satisfactory, which means the energy supervision system can reach more than 97%, this performance is better than most of the latest approaches.