Online Feature Selection Method Based on Change Rate for Process Monitoring
Author:
Affiliation:
1. College of Information Science and Technology, Beijing University of Chemical Technology,Beijing,P. R. China,100029
Funder
Fundamental Research Funds for the Central Universities
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9901509/9901494/09901850.pdf?arnumber=9901850
Reference18 articles.
1. Multiple kernel learning based feature selection for process monitoring
2. Feature selection for fault detection systems: application to the Tennessee Eastman process;hafida;Applied Intelligence,2016
3. An Efficient Feature Selection Approach using Sensitivity Analysis for Machine Learning based Heart Desease Classification
4. A Feature Subset Selection Method Based on the Combination of PCA and Improved GA
5. Bearing Fault Feature Selection Method Based on Weighted Multidimensional Feature Fusion
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