print

Explainability and transparency of classifiers for air-handling unit faults using explainable artificial intelligence (XAI)

author
Meas, Molika
Machlev, Ram
Köse, Ahmet
Tepljakov, Aleksei
Loo, Lauri
Levron, Yoash
Petlenkov, Eduard
Belikov, Juri
statement of authorship
Meas, Molika, Machlev, Ram, Kose, Ahmet, Tepljakov, Aleksei, Loo, Lauri, Levron, Yoash, Petlenkov, Eduard, Belikov, Juri
source
Sensors
publisher
MDPI
journal volume number month
vol. 22, issue 17
year of publication
2022
pages
art. 6338 : ill
url
https://doi.org/10.3390/s22176338
subject term
hooned
tehisintellekt
rikked
tehisõpe
XGBoost
keyword
buildings
explainable artificial intelligence
fault detection and diagnosis
HVAC
machine learning
SHAP
XAI
XGBoost
ISSN
1424-8220
notes
Bibliogr.: 33 ref
Open Access
Open Access
scientific publication
teaduspublikatsioon
classifier
1.1
Scopus
Journal metrics at Scopus
Article at Scopus
WOS
Journal metrics at WOS
Article at WOS
category (general)
Physics and Astronomy
Engineering
Chemistry
Computer science
Biochemistry, genetics and molecular biology
category (sub)
Physics and Astronomy. Instrumentation
Engineering. Electrical and electronic engineering
Physics and astronomy. Atomic and molecular physics, and optics
Chemistry. Analytical chemistry
Computer science. Information systems
Biochemistry, genetics and molecular biology. Biochemistry
kvartiil
Q1
TTÜ department
arvutisüsteemide instituut
tarkvarateaduse instituut
language
inglise
Uurimisrühm
Nonlinear control systems group
Centre for intelligent systems
Meas, M., Machlev, R., Kose, A., Tepljakov, A., Loo, L., Levron, Y., Petlenkov, E., Belikov, J. Explainability and transparency of classifiers for air-handling unit faults using explainable artificial intelligence (XAI) // Sensors (2022) vol. 22, issue 17, art. 6338 : ill. https://doi.org/10.3390/s22176338