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. R esults of data simulation show that the proposed method has higher forecasting p recision power and stronger generalization abi1ity than BP neural network and RB F neural network. In addition, it is feasible and effective in forecasting paten t application counts.     

微处理器中国专利发明主体合著关系分析

为发现微处理器中国专利发明主体的创新能力、主体间的合著模式、合著特点与规律,结合国内外合著分析方法研究状况,构建了发明主体合著关系可视化模型。该模型应用信息可视化技术挖掘隐含于专利数据库中的内在的、客观的、定量的信息,并以图形直观的呈现挖掘结果;同时,以科学计量学的合著率分析该领域科学合著程度。实证分析结果表明,我国的微处理器专利技术多集中在2000年以后,发明人合著强度大,申请机构与区域合著强度小,国内发明人创新能力低于国外发明人。