Measuring explainability and trustworthiness of power quality disturbances classifiers using XAI - explainable artificial intelligence
author
Machlev, Ram
Perl, Michael
Belikov, Juri
Levy, Kfir
Levron, Yoash
statement of authorship
Ram Machlev, Michael Perl, Juri Belikov, Kfir Yehuda Levy, Yoash Levron
source
IEEE transactions on industrial informatics
publisher
IEEE
journal volume number month
vol. 18, 8
year of publication
2022
pages
p. 5127−5137
url
https://doi.org/10.1109/TII.2021.3126111
subject term
sügavõpe
tehisintellekt
kvaliteet
hindamine
keyword
convolutional neural network (CNN)
deep-learning (DL)
energy
evaluation metrics
Explainable Artificial Intelligence (XAI)
power quality disturbances (PQDs)
power
ISSN
1551-3203
notes
Bibliogr.: 36 ref
scientific publication
teaduspublikatsioon
classifier
1.1
Scopus
https://www.scopus.com/sourceid/144912
https://www.scopus.com/record/display.uri?eid=2-s2.0-85131174076&origin=inward&txGid=503ddfa05b3d9f33dbd130a0a11e0143
WOS
https://www.webofscience.com/wos/woscc/full-record/WOS:000793847600014
https://www.webofscience.com/wos/woscc/full-record/WOS:000793847600014
category (general)
Engineering
Computer science
Tehnika
Arvutiteadus
category (sub)
Engineering. Control and systems engineering
Computer science. Computer science applications
Engineering. Electrical and electronic engineering
Computer science. Information systems
Tehnika. Juhtimis- ja süsteemitehnika
Arvutiteadus. Arvutiteaduse rakendused
Tehnika. Elektri- ja elektroonikatehnika
Arvutiteadus. Infosüsteemid
quartile
Q1
TalTech department
tarkvarateaduse instituut
language
inglise
Reserch Group
Nonlinear control systems group
Centre for intelligent systems