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 ...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 ability than BP neural network and RBF neural network. In addi- tion, it is feasible and effective in forecasting patent application counts.展开更多
基金Sponsored by "985" Philosophy and Social Science Innovation Base of the Ministry of Education of China (107008200400024)
文摘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 ability than BP neural network and RBF neural network. In addi- tion, it is feasible and effective in forecasting patent application counts.
