In the process of railway operation, equipment faults are inevitable, however, establishing emergency disposal plans manually is time-consuming, which may affect the efficiency and safety of railway operation. With lots of on-site historical emergency disposal cases, this paper introduces an assistant decision-making model based on CBR (Case-based Reasoning). A case database based on the case representation is constructed by keywords extracted from text files. The location information is used to perform case screening. Then, the attribute similarities of the detailed information can be obtained through similarity calculation. Meanwhile, the AHP (analytic hierarchy process) is used to obtain the weight vector of each attribute to calculate the case similarities, eventually, to obtain the most similar case. According to the most similar emergency disposal plan, combined with the train diagram, the emergency disposal plan for the current fault is automatically established, and this can reduce the time of establishment and execution.

CICTP