Congestion prediction method and device
A prediction method and congestion information technology, applied in the direction of prediction, instrumentation, data processing applications, etc., can solve the problem of low accuracy of congestion prediction
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Embodiment 1
[0048] figure 1 A schematic diagram of a congestion prediction process provided by an embodiment of the present invention, the process includes the following steps:
[0049] S101: Receive the first data information of the current time period sent by the first control sensor deployed in the first monitoring area, and obtain the first data information corresponding to the target characteristic parameter in the first data information according to the preset target characteristic parameter. A feature parameter value.
[0050] The congestion prediction method provided by the embodiments of the present invention is applied to electronic devices with data analysis and machine learning capabilities.
[0051] A plurality of first control sensors are deployed in the first monitoring area, and the plurality of first control sensors include speed measurement control sensors, uncivilized monitoring control sensors, violation monitoring control sensors, floating car control sensors, and th...
Embodiment 2
[0059] In order to make the congestion prediction of the first monitoring area more accurate, the electronic device is preset with target characteristic parameters highly correlated with the congestion prediction. On the basis of the above-mentioned embodiments, in the embodiment of the present invention, the process of preset target characteristic parameters includes:
[0060] According to the data information sent by each control sensor in each monitoring area within the preset range including the first monitoring area, and the preset characteristic parameters, the corresponding information in the data information is obtained. A characteristic parameter value of the characteristic parameter;
[0061] According to the characteristic parameter value and the congestion information corresponding to each monitoring area obtained when the first time period is delayed by the preset second time length, a correlation analysis algorithm is used to determine the characteristic paramete...
Embodiment 3
[0083] On the basis of the above-mentioned embodiments, in the embodiment of the present invention, the process of presetting the association group includes:
[0084] Taking the first monitoring area as the target monitoring area, for the third monitoring area adjacent to the target monitoring area, according to the third data information of the second time period sent by the first regulation sensor, and deploying the third data information in the second time period The fourth data information of the second time period sent by the third control sensor in the third monitoring area, acquire the third characteristic parameter value corresponding to the target characteristic parameter in the third data information, and the fourth data information The fourth characteristic parameter value corresponding to the target characteristic parameter; according to the corresponding third characteristic parameter value and fourth characteristic parameter value, and the correlation analysis alg...
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