Title :
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
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;
Conference_Titel :
Intelligent Information Technology Application Workshops, 2008. IITAW '08. International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3505-0
DOI :
10.1109/IITA.Workshops.2008.160
