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

被引：2

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：

Journal of Beijing Institute of Technology | 2009年 / 18卷 / 04期

关键词：

support vector machine; cross-validation algorithm; patent application count; forecasting;

D O I：

10.15918/j.jbit1004-0579.2009.04.025

中图分类号：

F204 [科学技术管理];

学科分类号：

020201 ;

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

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