Application Research of SVM in the Evaluation of Scientific Research Project

Author

Wang Xuejun ; Guo Jianfang

Author_Institution

Comput. & Inf. Eng. Manage., Shijiazhuang Railway Inst., Shijiazhuang

fYear

2008

fDate

21-22 Dec. 2008

Firstpage

364

Lastpage

367

Abstract

In the management of scientific research project, the evaluation of scientific research project is one of important processes. Traditional evaluation methods can not suffice the increasing need in the evaluation of scientific research project. In order to improve the efficiency of the evaluation of scientific research Project., this paper on the basis of support vector machines(SVM) based on statistical learning theory, especially analyzes SVM for classification theory, and proposes a binary tree multi-class method based on two-class SVM algorithm and applies this method in the evaluation of scientific research project.

Keywords

learning (artificial intelligence); natural sciences computing; pattern classification; project management; statistical analysis; support vector machines; tree data structures; trees (mathematics); binary tree multiclass method; classification theory; scientific research project evaluation; statistical learning theory; support vector machine; Application software; Binary trees; Information technology; Project management; Rail transportation; Research and development management; Statistical learning; Support vector machine classification; Support vector machines; Technology management;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Information Technology Application Workshops, 2008. IITAW '08. International Symposium on

Conference_Location

Shanghai

Print_ISBN

978-0-7695-3505-0

Type

conf

DOI

10.1109/IITA.Workshops.2008.160

Filename

4731953