Twin Broad Learning System for Fault Diagnosis of Rotating Machinery-Reference-Cited by-同舟云学术

Twin Broad Learning System for Fault Diagnosis of Rotating Machinery

Author:

Yang Le¹^ORCID,Yang Zelin²^ORCID,Song Shiji³^ORCID,Li Fan¹^ORCID,Chen C. L. Philip⁴^ORCID

Affiliation:

1. School of Information and Communications Engineering, Xi’an Jiaotong University, Xi’an, China

2. School of Software Engineering, Xi’an Jiaotong University, Xi’an, China

3. Department of Automation, Tsinghua University, Beijing, China

4. School of Computer Science and Engineering, South China University of Technology, Guangzhou, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Sichuan Province

Shaanxi Province Key Research and Development Program

Science and Technology Major Project of Guangzhou

Program for Guangdong Introducing Innovative and Entrepreneurial Teams

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

Reference49 articles.

1. Twin support vector machines for pattern classification;khemchandani;IEEE Trans Pattern Anal Mach Intell,2007

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