?url_ver=Z39.88-2004&rft_id=10.1627%2Fjpi.57.65&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.aulast=Bataee&rft.au=Bataee%2C+M.&rft.aufirst=M.&rft.volume=57&rft.issn=13468804&rft.issue=2&rft.atitle=Artificial+neural+network+model+for+prediction+of+drilling+rate+of+penetration+and+optimization+of+parameters&rft.pages=65-70&rft.title=Journal+of+the+Japan+Petroleum+Institute&rft.date=2014&rft.genre=article