Determination of dynamic warning intervals for macroscopic safety risks in railway operations based on K-means
WANG Lieni
HU Shike
HUANG Yi
ZENG Linhui
Abstract：To accurately divide the macroscopic safety risk warning intervals for railway operations and avoid relying solely on relevant standards or human experience to determine the safety risk warning intervals,as well as the lack of dynamism in the warning intervals,an indicator system for macroscopic safety risk warning is established.The K-means clustering algorithm is used to determine the dynamic warning intervals for macroscopic safety risks.The K-means clustering algorithm is employed to categorize different sets of indicators into three classes:good,moderate,and poor.The upper bounds of the three classes are used as the dividing points for the four warning intervals,to determine the warning intervals for the four risk warning levels of each indicator.The feasibility and applicability of this algorithm are verified through practical examples.The results show that the K-means clustering algorithm can determine the safety risk warning intervals for railway operations and can dynamically adjust them based on historical data changes.
Keywords：railway operationmacroscopic safety riskK-meanswarning interval
Publication Date：2023-12-30
Online Publishing Date：2026-05-22(First online date of this platform, not the publication date of the document)
Pages：7( 68-74 )