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

摘要：

A forecasting system of patent application quantities is studied by means of applying the support vector machine (SVM) which uses cross-validation algorithms to select preferences. The result of data emulation shows the proposed method has higher forecasting precision and stronger generalization ability than BP neural network and RBF neural network, and it is feasible and effective in forecasting patent application quantities.

关键词： support vector machine (SVM) cross-validation algorithm forecasting patent application quantities

作者: Zhang Liwei Zhang Qian Zhu Donghua Wang Xuefeng Yu Bo

作者单位: School of Management & Economics, Beijing Institute of Technology.Beijing, 100081, China Department of Computer Science, Kyungwon University.Gyeonggi-Do, Seongnam-Si, 461701, Korea

会议类型: 国际会议

会议名称: 2008年技术创新与竞争情报国际学术会议

会议地点: 北京

会议语种:英文

页码: 141-146

在线出版日期: 2008-10-16（万方平台首次上网日期，不代表论文的发表时间）