The Academic Perspective Procedia publishes Academic Platform symposiums papers as three volumes in a year. DOI number is given to all of our papers.
Publisher : Academic Perspective

Journal DOI : 10.33793/acperpro
Journal eISSN : 2667-5862

Year :2018, Volume 1, Issue 1, Pages: 1110-1119
09.11.2018
Using Principal Component Analysis and Artificial Neural Networks for Fault Type Forecasting in an Automotive Company
Tülay Korkusuz Polat
557
246
Keywords: Principal Component Analysis, Artificial Neural Network, Fault Forecasting
Cite
  • BIBTEX
    @article{acperproISITES2018ID178, author={Polat, Tülay Korkusuz}, title={Using Principal Component Analysis and Artificial Neural Networks for Fault Type Forecasting in an Automotive Company}, journal={Academic Perspective Procedia}, eissn={2667-5862}, volume={1}, year=2018, pages={1110-1119}}
  • APA
    Polat, T.. (2018). Using Principal Component Analysis and Artificial Neural Networks for Fault Type Forecasting in an Automotive Company. Academic Perspective Procedia, 1 (1), 1110-1119. DOI: 10.33793/acperpro.01.01.178
  • ENDNOTE
    %0 Academic Perspective Procedia (ACPERPRO) Using Principal Component Analysis and Artificial Neural Networks for Fault Type Forecasting in an Automotive Company% A Tülay Korkusuz Polat% T Using Principal Component Analysis and Artificial Neural Networks for Fault Type Forecasting in an Automotive Company% D 11/9/2018% J Academic Perspective Procedia (ACPERPRO)% P 1110-1119% V 1% N 1% R doi: 10.33793/acperpro.01.01.178% U 10.33793/acperpro.01.01.178
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