Bayramoglu Law Offices LLC
Method for recognizing multi-dimensional anomalous urban traffic event based on ternary gaussian mixture model
A method for recognizing multi-dimensional anomalous urban traffic events based on a ternary Gaussian mixture model includes: reading a data sample of urban road traffic events; randomly dividing the data sample into a first subsample and a second subsample; performing modeling based on the first subsample by using the ternary Gaussian mixture model to obtain a second ternary Gaussian mixture model to calculate a distribution probability p of any sample point; clustering the second subsample, recognizing an outlier in the second subsample, and labeling the outlier and a normal point to obtain a labeled subsample; calculating the labeled subsample to obtain the distribution probability p corresponding to each sample point in the labeled subsample; when a new traffic event occurs, obtaining features of three dimensions of the new traffic event, calculating a distribution probability p by using the second model, and recognizing the new traffic event as anomalous if p<t-score.
SHANGHAI SEARI INTELLIGENT SYSTEM CO., LTD.
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Wei Chaoteng Lu Yu Xuechen Xiao
Zhao Wu Zhang Zhou Yang Gao