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A Fatigue Strength Predictor for Steels Using Ensemble Data Mining
2016
Proceedings of the 25th ACM International on Conference on Information and Knowledge Management - CIKM '16
Fatigue strength is one of the most important mechanical properties of steel. High cost and time for fatigue testing, and potentially disastrous consequences of fatigue failures motivates the development of predictive models for this property. We have developed advanced data-driven ensemble predictive models for this purpose with an extremely high cross-validated accuracy of >98%, and have deployed these models in a user-friendly online web-tool, which can make very fast predictions of fatigue
doi:10.1145/2983323.2983343
dblp:conf/cikm/AgrawalC16
fatcat:tr5rjwkrebfxpdnreaezvusc5e