VANETs vehicle accident risk prediction model based on AdaBoost-SO
A technology of accident risk and prediction model, applied in the field of Internet of Vehicles, can solve the problem of failure to obtain an accident prediction model, and achieve the effect of improving timeliness
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[0054] The technical solution of the present invention will be further described in detail below in conjunction with the accompanying drawings.
[0055] A kind of VANETs vehicle accident risk prediction model based on AdaBoost-SO, the step of described model establishment comprises:
[0056] Step 1: Populate the research dataset.
[0057] Specifically, before reconstructing the data, find and modify uncertain or incomplete road safety data to improve the data set; the usual implementation includes filling the average value of available features, special values, average values of similar samples, and directly ignoring Samples with missing values.
[0058] Step 2: Use the SMOTE algorithm to balance the samples in the data set, and encode the discrete features of each sample with One-Hot.
[0059] Specifically, the Synthetic Minority Oversampling Technique (SMOTE) algorithm is used to solve the problem of unbalanced number of samples for each category in the research data set...
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