Analysis Platform of Rail Transit Vehicle Signal System Based on Data Mining

Chunying Li, Zhonghua Mu

Abstract


According to the increasing demand of interactive information of rail transit on-board signal equipment, the author designed a rail transit on-board monitoring and maintenance system based on data mining to set association rules for operation data acquisition and propose a correlation rules algorithm to obtain more reliable understanding and operation quality evaluation of train operation information.From a lot of logs, quickly find key issues, applied in the train test and repair field.The simulation experiment results show that after analyzing the simulation data and the curve, the system extraction results have certain error in the manual calculation results, and the error value is between 0.5 and 0.6, but the overall meets the actual work needs, and optimize the invalid data to reduce the error.The reliable operation and maintainability of the system are verified.


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DOI: https://doi.org/10.31449/inf.v47i3.3942

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