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New machine learning model can predict what roads are most dangerous

Researchers studied features of roads most likely to cause crashes using a dataset of 15,000 kilometers of roads across 7,000 locations in Greece.

Tel avivIsrael generalEgnatia odosEleni christofaSimos gerasimidisTransportation research recordUniversity of massachusettsCentral bureau of statisticsCentral bureauDecision treesJimi okeScientific studyCar crashRoad safetyAi and machine learningTechnology innovation

Road features that predict crash sites identified in new machine-learning model

Road features that predict crash sites identified in new machine-learning model
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United statesEgnatia odosSimos gerasimidisEleni christofaTransportation research recordUmass transportation centerJimi okeTransportation center

Road features that predict crash sites identified in new machine-learning model

Road features that predict crash sites identified in new machine-learning model
techxplore.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from techxplore.com Daily Mail and Mail on Sunday newspapers.

United statesSimos gerasimidisEleni christofaEgnatia odosDimitrios sarigiannisJournal of the transportation research boardUniversity of massachusetts amherstTransportation research recordUmass transportation centerMassachusetts amherstJimi okeTransportation centerFeature engineeringDecision treesTransportation research board

Verification & Validation

Verification & Validation of Computational Models Associated with the Mechanics of Materials

United statesMechanical engineeringDominik schillingerBo liJaroslaw knapMircea grigoriuAdrian lewMichael shieldsPolytechnique montrVikas tomarJo culbertsonMichael tonksMichelle schwalbeJaimie tileyRobert sargentMarisol koslowski