Application Research of Robust LS-SVM Regression Model in Forecasting Patent Application Counts

A forecasting system of patent application counts is studied in this paper. The optimization model proposed in the research is based on support vector machines (SVM), in which cross-validation algorithm is used for preferences selection. Results of data simulation show that the proposed method has higher forecasting precision power and stronger generalization abi1ity than BP neural network and RBF neural network. In addition, it is feasible and effective in forecasting patent application counts.