版权说明 操作指南
首页 > 成果 > 详情

A neuro-fuzzy Kohonen network for data stream possibilistic clustering and its online self-learning procedure

认领
导出
Link by 万方学术期刊
反馈
分享
QQ微信 微博
成果类型:
期刊论文
作者:
Hu, Zhengbing;Bodyanskiy, Yevgeniy V.;Tyshchenko, Oleksii K.*;Boiko, Olena O.
通讯作者:
Tyshchenko, Oleksii K.
作者机构:
[Hu, Zhengbing] Cent China Normal Univ, Sch Educ Informat Technol, 152 Louyu Rd, Wuhan 430079, Hubei, Peoples R China.
[Bodyanskiy, Yevgeniy V.; Tyshchenko, Oleksii K.; Boiko, Olena O.] Kharkiv Natl Univ Radio Elect, Control Syst Res Lab, 14 Nauky Ave, UA-61166 Kharkov, Ukraine.
通讯机构:
[Tyshchenko, Oleksii K.] K
Kharkiv Natl Univ Radio Elect, Control Syst Res Lab, 14 Nauky Ave, UA-61166 Kharkov, Ukraine.
语种:
英文
关键词:
Evolving system;Possibilistic fuzzy clustering;Kohonen neural network;Self-learning procedure;Neighborhood function;Neuro-fuzzy network;Data stream
期刊:
Applied Soft Computing
ISSN:
1568-4946
年:
2018
卷:
68
页码:
710-718
基金类别:
This scientific work was partially supported by RAMECS and CCNU16A02015 .
机构署名:
本校为第一机构
院系归属:
教育信息技术学院
摘要:
A task of Data Stream Fuzzy Clustering is considered when data is processed sequentially under a priori uncertainty conditions about both a number of clusters and a degree of clusters’ overlapping. A modified two-layer neuro-fuzzy Kohonen network is used for solving the possibilistic fuzzy clustering tasks. This system tunes centers’ coordinates and membership levels of every pattern to clusters during the self-learning procedure and automatically increases a number of neurons during data processing. A distinguishing feature of the proposed a...

反馈

验证码:
看不清楚,换一个
确定
取消

成果认领

标题:
用户 作者 通讯作者
请选择
请选择
确定
取消

提示

该栏目需要登录且有访问权限才可以访问

如果您有访问权限,请直接 登录访问

如果您没有访问权限,请联系管理员申请开通

管理员联系邮箱:yun@hnwdkj.com