Current position: Home >> Scientific Research >> Paper Publications

An improved incremental learning model for network data stream classification problems

Release Time:2019-03-11  Hits:

Indexed by: Journal Article

Date of Publication: 2012-02-01

Journal: Journal of Convergence Information Technology

Included Journals: Scopus、EI

Volume: 7

Issue: 3

Page Number: 84-90

ISSN: 19759320

Abstract: Network attack detection is an important aspect in maintaining a stable network. It is usually done by a rule-based method, such as firewall technology. In the case of network data stream, rule-based method cannot be changed with the help of the outside data dynamic environment. In this paper, we proposed an incremental learning method based on support vector machine (SVM), which can improve the classification accuracy as well as reduce the time-consuming aspect. The validation of our method compares with two other models: k-nearest neighbor algorithm (KNN) and decision tree. The experimental results show the robustness of the proposed model.

Prev One:开设数学建模系列课程,增强本科生科研能力培养

Next One:Obstacle prediction-based dynamic path planning for a mobile robot