Automatic identification method of wrong bayonet position information based on big data analysis

Abstract

The invention discloses an error checkpoint positional information automatic identification method based on big data analysis. The method comprises the steps of: calculating adjacent checkpoint pairs according to mass historical checkpoint vehicle passing data, calculating the shortest path length of the adjacent checkpoint pairs by combining with GIS map data, and calculating passing speed of vehicles between the checkpoint pairs through vehicle data; and finding out the checkpoint with error positional information according to checkpoint shortest path abnormity, checkpoint interval velocity abnormity and abnormal frequency iteration in sequence. The error checkpoint positional information automatic identification method utilizes real checkpoint vehicle passing data, and has the advantages of large data size, high data accuracy and the like, thus the accuracy of error checkpoint positional information analyzed according to attributes of vehicle passing data is high. The error checkpoint positional information automatic identification method achieves the automatic identification of the error checkpoint positional information, has the advantages of fast execution speed, high accuracy, high efficiency and the like, and omits a great deal of manual identification.

Description

technical field [0001] The invention belongs to the technical field of data mining, and in particular relates to an automatic recognition method for wrong bayonet position information based on big data analysis. Background technique [0002] With the development of economy and society, especially after the 18th National Congress of the Communist Party of China, the process of urbanization has accelerated, the scale of cities has continued to expand, the urban population has continued to increase, and the number of cars in cities has increased rapidly, especially in large cities and megacities. peak. Due to the limited basic traffic capacity of urban roads, the traffic load is constantly increasing, and traffic congestion can be seen everywhere. Traffic problems have become a common livelihood problem. [0003] With the introduction of "Internet +", smart transportation has also been pushed to a new climax. As one of the important components of traffic data, checkpoint data...

AI Technical Summary

Problems solved by technology

When conducting experimental research on the existing bayonet data, it can be found that the location information of the bayonet is a very critical basic data. Once the location information is wrong, data mining and big data analysis based on the bayonet passing information will cause serious misleading This will seriously affect the correctness and reliability of data analysis, and cause the analysis and research on checkpoint data to fail to proceed smoothly. Due to the large number of checkpoints, as many as tens of thousands, and distributed in every corner of the city, if the checkpoint data is manually Checking and comparing one by one will consume a lot of labor and transportation costs, and most of the wrong bayonet position information is difficult to find and eliminate manually

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