Application of Big Data Technology and K-Means Clustering Algorithm in Urban Rail Transit

With the continuous development of science and technology, the amount of data generated in life is increasing, and big data technology has now penetrated into all walks of life. This paper focuses on the application of big data technology in urban rail transit. Firstly, the related concepts of big data technology and urban rail transit are introduced in detail. Secondly, it emphasizes the necessity of using big data technology in urban rail transit; Finally, this paper expounds the examples of the application of big data technology in urban rail transit, including key applications such as operation and maintenance, accessibility analysis and passenger flow monitoring. Taking passenger flow monitoring as an example, based on the passenger flow data of Tianjin big data technology, the stations are classified by K-Means clustering algorithm. Big data technology can help urban rail transit improve its operational efficiency in many aspects, promote its intelligent development and accelerate the process of urbanization. Faced with the abundance and complexity of data in the era of science and technology, it will become an inevitable trend to assist management decision-making through big data technology.