Open AccessFault Analysis of Ship Machinery Using Machine Learning Techniques
Author(s) -
Funda Kaya İnceişçi,
Ayça Ak
Publication year - 2022
Publication title -
the international journal of maritime engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.242
H-Index - 17
eISSN - 1740-0716
pISSN - 1479-8751
DOI - 10.5750/ijme.v164i1.769
Subject(s) - decision tree , fault (geology) , machine learning , artificial neural network , fault tree analysis , random forest , regression analysis , artificial intelligence , regression , computer science , linear regression , bayesian network , engineering , data mining , reliability engineering , statistics , mathematics , geology , seismology
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