王红军 副研究员

硕士生导师

个人信息Personal Information


学历:博士研究生毕业

学位:工学博士学位

办公地点:犀浦3号教学楼31529

毕业院校:四川大学

学科:电子信息. 软件工程. 计算机应用技术

所在单位:计算机与人工智能学院

报考该导师研究生的方式

欢迎你报考王红军老师的研究生,报考有以下方式:

1、参加西南交通大学暑期夏令营活动,提交导师意向时,选择王红军老师,你的所有申请信息将发送给王红军老师,老师看到后将和你取得联系,点击此处参加夏令营活动

2、如果你能获得所在学校的推免生资格,欢迎通过推免方式申请王红军老师研究生,可以通过系统的推免生预报名系统提交申请,并选择意向导师为王红军老师,老师看到信息后将和你取得联系,点击此处推免生预报名

3、参加全国硕士研究生统一招生考试报考王红军老师招收的专业和方向,进入复试后提交导师意向时选择王红军老师。

4、如果你有兴趣攻读王红军老师博士研究生,可以通过申请考核或者统一招考等方式报考该导师博士研究生。

点击关闭

论文成果

当前位置: 中文主页 >> 科学研究 >> 论文成果

Particle Subswarms Collaborative Clustering

影响因子:4.747

DOI码:10.1109/TCSS.2019.2940740

所属单位:西南交通大学

发表刊物:IEEE Transactions on Computational Social Systems

刊物所在地:US

关键字:Collaborative clustering, crisp clustering, distributed data, fuzzy clustering, particle swarm optimization (PSO)

摘要:Collaborative clustering aims to find a common data structure between several distributed data sets governed by different privacy constraints and technical limitations that prohibit a central collection of data for processing. Therefore, it is required to process the data sets separately using collaboration, which allows clustering algorithms to work locally on an individual data set while exchanging information about the finding with algorithms in other data locations. Thus, the different data locations share information to improve individual clustering result amidst technical and privacy limitations but without breaching privacy. In this article, we present a framework of collaborative clustering that does not require interaction coefficients to regulate the effect of collaboration. We further adapt the framework to cluster distributed data using crisp and fuzzy clustering algorithms. We use particle swarm optimization techniques to inference the framework and, therefore, call it particle subswarms. Moreover, the collaboration increases the number of particles in the swarm without increasing the number of clusters in the data set. This article, therefore, provides the theoretical foundations of particle subswarms and some experimental results on several data sets.

合写作者:Ji Zhang, Ping Deng,李天瑞

第一作者:Collins Census

论文类型:学术论文

通讯作者:Hongjun Wang

论文编号:20194007492148

学科门类:工学

一级学科:计算机科学与技术

卷号:Volume: 6

期号:Issue: 6, December 2019

页面范围:1165 - 1179

ISSN号:2329-924X

是否译文:

发表时间:2019-09-27