Peak management and mean management are common ways to manage the quality of high-speed railway tracks at present. The most popular method for evaluating such tracks is the track quality index (TQI) method, which can reflect the overall state of the equipment to a certain extent. However, this method is likely to ignore some potential risks that threaten the operation of a high-speed train. For more effective risk identification, an incentive factor-based dynamic comprehensive evaluation (DCE) method was introduced to assess the geometric parameters of a high-speed railway track. Moreover, the weights of geometric parameters were computed by a combination of the analytic hierarchy process (AHP) and entropy based on the correlation coefficient. The proposed method can highlight the sensitivity index of the geometric parameters, which is an advantage over the TQI method. A case study of a high-speed railway track was performed using the two methods, and the results were verified with the original data. It was found that the TQI method identified only one obvious risk while the proposed method identified one obvious risk and two potential risks. This suggests that the proposed method is more accurate in identifying the risky sections than the TQI method.

中文翻译：

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基于激励因素的高速铁路动态综合评价

高峰管理和均值管理是目前管理高速铁路轨道质量的常用方法。评估此类轨道的最流行方法是轨道质量指数（TQI）方法，它可以在一定程度上反映设备的整体状态。但是，这种方法可能会忽略一些威胁高速列车运行的潜在风险。为了更有效地识别风险，引入了基于激励因子的动态综合评估（DCE）方法来评估高速铁路的几何参数。此外，基于相关系数，通过层次分析法（AHP）和熵的组合来计算几何参数的权重。所提出的方法可以突显几何参数的灵敏度指标，与TQI方法相比，这是一个优势。使用这两种方法对高速铁路进行了案例研究，并用原始数据验证了结果。结果发现，TQI方法只能识别一种明显的风险，而所提出的方法可以识别一种明显的风险和两种潜在的风险。这表明，所提出的方法比TQI方法更准确地识别危险区域。