The invention discloses a short-term traffic flow forecasting method based on three-layer K nearest neighbors. The short-term traffic flow forecasting method comprises the steps of: (1) counting traffic flow based on fixed time intervals and establishing a historical sample database; (2) evaluating shape similarity between a current point and points in the historical sample database by adopting similarity deviation degree and correlation coefficient respectively, and performing first-layer screening of points; (3) evaluating the points screened in the first layer according to hit rate and shape similar distance, and performing second-layer screening of points; (4) and evaluating matching distances between the current point and the points screened in the second layer by using an Euclidean distance method, and outputs a forecasting result by adopting a weighted mean value of inverse similar distance of a combination shape of the traffic flow at the corresponding next moment when nearest neighbor points are translated to the current point. The short-term traffic flow forecasting method adopts a two-layer shape similarity matching function, takes the shape matching distances between the nearest neighbor points and the current point into account, and improves accuracy and timeliness of short-term traffic flow forecasting.
Short-term traffic flow forecasting method based on three-layer K nearest neighbor
2016-02-17
Patent
Electronic Resource
English
A spatiotemporal correlative k-nearest neighbor model for short-term traffic multistep forecasting
Online Contents | 2016
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