南方科技大学知识苑(SUSTech KC): Robust TSK Fuzzy System Based on Semisupervised Learning for Label Noise Data

题名	Robust TSK Fuzzy System Based on Semisupervised Learning for Label Noise Data
作者	Zhang，Te1 ; Deng，Zhaohong 2; Ishibuchi，Hisao3 ; Pang，Lie Meng4
发表日期	2021-08
DOI	10.1109/TFUZZ.2020.2994979
发表期刊	IEEE Transactions on Fuzzy Systems 影响因子和分区
ISSN	1941-0034
卷号	29 期号:8页码:2145-2157
关键词	Classification label noise semisupervised learning TSK fuzzy system
相关链接	[IEEE记录]
收录类别	SCI ; EI
学校署名	第一
EI入藏号	20202308787349
EI主题词	Learning algorithms ; Soft computing ; Supervised learning ; Fuzzy sets
EI分类号	Data Storage, Equipment and Techniques:722.1 ; Computer Software, Data Handling and Applications:723 ; Machine Learning:723.4.2 ; Combinatorial Mathematics, Includes Graph Theory, Set Theory:921.4
ESI学科分类	ENGINEERING
来源库	IEEE
全文链接	https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9094299
引用统计	被引频次[WOS]：13
成果类型	期刊论文
条目标识符	http://sustech.caswiz.com/handle/2SGJ60CL/242367
专题	工学院_计算机科学与工程系
作者单位	1.Department of Computer Science and Engineering, Southern University of Science and Technology, 255310 Shenzhen, Guangdong China (e-mail: ztcsrookie@qq.com) 2.School of Digital Media, Jiangnan University, 66374 Wuxi China 214122 (e-mail: dengzhaohong@jiangnan.edu.cn) 3.Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong China 518055 (e-mail: hisaoi@cs.osakafu-u.ac.jp) 4.Department of Computer Science and Engineering, Southern University of Science and Technology, 255310 Shenzhen China 518055 (e-mail: plm_1206@hotmail.my)
第一作者单位	计算机科学与工程系
第一作者的第一单位	计算机科学与工程系
推荐引用方式 GB/T 7714	Zhang，Te,Deng，Zhaohong,Ishibuchi，Hisao,et al. Robust TSK Fuzzy System Based on Semisupervised Learning for Label Noise Data[J]. IEEE Transactions on Fuzzy Systems,2021,29(8):2145-2157.
APA	Zhang，Te,Deng，Zhaohong,Ishibuchi，Hisao,&Pang，Lie Meng.(2021).Robust TSK Fuzzy System Based on Semisupervised Learning for Label Noise Data.IEEE Transactions on Fuzzy Systems,29(8),2145-2157.
MLA	Zhang，Te,et al."Robust TSK Fuzzy System Based on Semisupervised Learning for Label Noise Data".IEEE Transactions on Fuzzy Systems 29.8(2021):2145-2157.