Prediction of Car Accidents Using a Maximum Sensitivity Neural Network
作者： Erika Contreras , Luis Torres-Treviño , Francisco Torres
DOI: 10.1007/978-3-319-73323-4_9
关键词: Metropolitan area 、 Software 、 Sensitivity (control systems) 、 Transport engineering 、 Training (meteorology) 、 Artificial neural network 、 Road traffic 、 Computer science
摘要: In this paper, a model is made for the purpose of being tool in prediction road traffic accidents urban zones Nuevo Leon: Monterrey and its metropolitan area; by means Artificial Intelligence techniques, such as Neural Networks. The Maximum Sensitivity Network was developed, trained validated using Scilab development software. training patterns network are compilation obtained mainly from INEGI database through history Leon which took place 2015. density cars transiting municipalities, schedules, types causes used input variables to obtain quantity output data. system uses 80% data execute prediction, remaining 20% validate results further illustrate analysis these systems events.
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