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VEHICLE ACCIDENT RISK PREDICTION MODEL BASED ON ADABOOST-SO IN VANETS
VEHICLE ACCIDENT RISK PREDICTION MODEL BASED ON ADABOOST-SO IN VANETS
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机译：基于ADABOOST-SO的机动车事故风险预测模型。
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摘要
A vehicle accident risk prediction model based on AdaBoost-SO in VANETs, being able to provide a theoretical basis for an ITS and driving safety assistance. The model establishment method comprises: first populating a study dataset, balancing samples in the dataset by using an SMOTE algorithm, encoding each sample feature by means of One-Hot, then training the study dataset by using a trichotomy Adaboost-SO algorithm to obtain a system model, and finally importing traffic data by means of VANETs, so as to obtain a vehicle accident probability, AdaBoost-SO referring to trichotomy Adaboost with SMOTE and One-Hot encoding, VANETs referring to Vehicular Ad Hoc Networks, ITS referring to an Intelligent Transportation System, and SMOTE referring to a Synthetic Minority Oversampling Technique.
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