首页|Study Data from University of Hawaii Manoa Provide New Insightsinto Machine Lea rning (Estimating Equilibrium Scour Depth Around Non-circular Bridge Piers Using Interpretable Hybrid Machine Learning Models)
Study Data from University of Hawaii Manoa Provide New Insightsinto Machine Lea rning (Estimating Equilibrium Scour Depth Around Non-circular Bridge Piers Using Interpretable Hybrid Machine Learning Models)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Current study results on Machine Learn ing have been published. According to newsreporting out of Honolulu, Hawaii, by NewsRx editors, research stated, “Scouring at bridge piers is a crucialissue t hat risks bridge collapses, causing economic losses and endangering public safet y. Classic modelsstruggle to accurately estimate equilibrium scour depth (d(se) ) due to the complex scouring mechanism.”Funders for this research include Hawaii Department of Transportation (HDOT), Fe deral HighwayAdministration (FHWA).
HonoluluHawaiiUnited StatesNorth a nd Central AmericaCyborgsEmerging TechnologiesMachine LearningUniversity of Hawaii Manoa
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