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

被引：5

作者：

张丽玮 ^{[1
,2
]}

张茜 ^{[3
]}

汪雪锋 ^{[1
]}

朱东华 ^{[1
]}

机构：

[1] School of Management and Economics, Beijing Institute of Technology

[2] Information College, Capital University of Economics and Business

[3] Department of Computer Science, Kyungwon University

来源：

JournalofBeijingInstituteofTechnology | 2009年 / 18卷 / 04期

关键词：

D O I：

暂无

中图分类号：

F204 [科学技术管理];

学科分类号：

020201 [国民经济学];

摘要：

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.

引用

页码：497 / 501

页数：5

共 5 条

[1]

我国专利申请量的支持向量机预测模型研究 [J].