?url_ver=Z39.88-2004&rft_id=10.3390%2Fapp12031722&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.aulast=Lo&rft.au=Lo%2C+M.&rft.aufirst=M.&rft.atitle=An+Artificial+Neural+Network-Based+Equation+for+Predicting+the+Remaining+Strength+of+Mid-to-High+Strength+Pipelines+with+a+Single+Corrosion+Defect&rft.title=Applied+Sciences+(Switzerland)&rft.date=2022&rft.issue=3&rft.issn=20763417&rft.volume=12&rft.genre=article