Open AccessEnhancing the Classification Performance of Machine Learning Techniques by Using Hjorth's and Other Statistical Parameters for Precise Tracking of Naturally Evolving Faults in Ball Bearings
Author(s) -
Sameera Mufazzal,
S. M. Muzakkir,
Sidra Khanam
Publication year - 2022
Publication title -
the international journal of acoustics and vibration
Language(s) - English
Resource type - Journals
eISSN - 2415-1408
pISSN - 1027-5851
DOI - 10.20855/ijav.2022.27.21847
Subject(s) - support vector machine , computer science , artificial intelligence , pattern recognition (psychology) , k nearest neighbors algorithm , entropy (arrow of time) , bearing (navigation) , data mining , random forest , fault (geology) , statistical learning theory , precision and recall , machine learning , physics , quantum mechanics , seismology , geology
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