An Asynchronous Quasi‐Cloud/Edge/Client Collaborative Federated Learning Mechanism for Fault Diagnosis

Author:

Xue MA1,Chenglin WEN12

Affiliation:

1. School of AutomationHangzhou Dianzi UniversityHangzhou310018China

2. School of AutomationGuangdong University of Petrochemical TechnologyMaoming525000China

Publisher

Institution of Engineering and Technology (IET)

Subject

Applied Mathematics,Electrical and Electronic Engineering

Reference24 articles.

1. Book review: Big data: A revolution that will transform how we live, work, and think;Calderaro Andrea;Media, Culture & Society,2015

2. Creating Strategic Business Value from Big Data Analytics: A Research Framework

3. Empowering things with intelligence: A survey of the progress, challenges, and opportunities in artificial intelligence of things;Zhang J.;IEEE Internet of Things Journal,2020

4. Research on intelligent fault diagnosis method based on CELCD and MFVPMCD;Pan H.;Acta Electronica Sinica,2017

5. Time‐frequency analysis method based on improved empirical wavelet transform and its application in rolling bearing fault diagnosis;Zheng J.;Acta Electronica Sinica,2018

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