A Novel Fault Diagnosis Method of PEMFC System Based on Data Space Feature Decision Tree Group and Extreme Learning Machine
Author:
Affiliation:
1. School of Automation, Northwestern Polytechnical University,Xi'an,China
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10311571/10311610/10312280.pdf?arnumber=10312280
Reference14 articles.
1. Data-driven Fault Diagnosis for PEM Fuel Cell System Using Sensor Pre-Selection Method and Artificial Neural Network Model
2. A Novel Diagnosis Method of Proton Exchange Membrane Fuel Cells Based on Multi-Grained Cascade Forest and Principal Component Analysis
3. Extreme Learning Machine for Regression and Multiclass Classification
4. Hydrogen fuel cell diagnostics using random forest and enhanced feature selection
5. Fault diagnosis of PEMFC based on spatio-temporal characteristics of operation data and Stacking integrated learning [J];tiejiang;Journal of Electrical Engineering China,2023
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