?url_ver=Z39.88-2004&rft_id=10.1108%2FAEAT-01-2018-0013&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.aulast=Fentaye&rft.au=Fentaye%2C+A.D.&rft.aufirst=A.D.&rft.pages=992-999&rft.atitle=Gas+turbine+gas-path+fault+identification+using+nested+artificial+neural+networks&rft.volume=90&rft.issn=17488842&rft.issue=6&rft.date=2018&rft.title=Aircraft+Engineering+and+Aerospace+Technology&rft.genre=article