Interval-Valued Features Based Machine Learning Technique for Fault Detection and Diagnosis of Uncertain HVAC Systems
The operation of heating, ventilation, and air conditioning (HVAC) systems is usually disturbed by many uncertainties such as measurement errors, noise, as well as temperature. Thus, this paper proposes a new multiscale interval principal component analysis (MSIPCA)-based machine learning (ML) techn...
Main Authors: | Sondes Gharsellaoui, Majdi Mansouri, Mohamed Trabelsi, Mohamed-Faouzi Harkat, Shady S. Refaat, Hassani Messaoud |
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Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9176993/ |
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