Knowledge-Induced Multiple Kernel Fuzzy Clustering-Reference-Cited by-同舟云学术

Knowledge-Induced Multiple Kernel Fuzzy Clustering

Published:2023-12 Issue:12 Volume:45 Page:14838-14855
ISSN:0162-8828
Container-title:IEEE Transactions on Pattern Analysis and Machine Intelligence
language:
Short-container-title:IEEE Trans. Pattern Anal. Mach. Intell.

Author:

Tang Yiming¹^ORCID,Pan Zhifu²^ORCID,Hu Xianghui³^ORCID,Pedrycz Witold⁴^ORCID,Chen Renhao²^ORCID

Affiliation:

1. Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine, School of Computer and Information, Hefei University of Technology, Hefei, Anhui, China

2. School of Computer and Information, Hefei University of Technology, Hefei, Anhui, China

3. School of Computer Science and Engineering, Southeast University, Nanjing, China

4. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Vision and Pattern Recognition,Software

Link

http://xplorestaging.ieee.org/ielx7/34/10308548/10192920.pdf?arnumber=10192920

Reference35 articles.

1. Weighted Kernel Fuzzy C-Means-Based Broad Learning Model for Time-Series Prediction of Carbon Efficiency in Iron Ore Sintering Process

2. Oscillation-Bound Estimation of Perturbations Under Bandler-Kohout Subproduct

3. Clustering Incomplete Data Using Kernel-Based Fuzzy C-means Algorithm

4. Granular Symmetric Implicational Method

5. Feature-Weighted Possibilistic c-Means Clustering With a Feature-Reduction Framework

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