High-speed Train Control System Big Data Analysis Based on the Fuzzy RDF model and Uncertain Reasoning

Dalin Zhang

Abstract


China high-speed train control system is a combination of computer, communication and control. Its events are diverse, including sensor data stream, GPS signal, GSM-R transmission data, real-time video monitoring data, train control software data, etc. These data have the typical characteristics of big data. If these data are well applied, this will be of great help to operations, maintenance, safety, passenger services, etc. This paper presents an efficient analysis method based on the fuzzy RDF model and uncertain reasoning for high-speed train control system big data. We have used the method proposed in this paper to analyze the data of the high-speed train control system. The experiment results show that the method proposed in this paper has good efficiency and scalability for the analysis of big data with different structures, types and context sensitive from high-speed train control system.

Keywords


high-speed train control system, fuzzy RDF, D-S theory, uncertain reasoning

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DOI: https://doi.org/10.15837/ijccc.2017.4.2914



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