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
收藏
页码：497 / 501
页数：5
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