| Due to the continuous development of the green economy and society,the concepts of "energy saving","emission reduction",and "environmental protection" have become more and more popular.When traveling,more people tend to choose fast,comfortable and accurate urban rail transit.However,due to the large passenger volume of urban rail transit,the energy consumption of rail transit operation is relatively large.Therefore,in recent years,more and more scholars have begun to pay attention to the research in the field of rail transit energy conservation.In the early stage of this research group,case-based reasoning technology was integrated into the energy-saving optimization study of train operation diagrams,which can help subway operators quickly find the best operation diagrams for new conditions,and the energy-saving effect is significant.With the increasing demand for passenger travel,when there is a sudden large passenger flow,the imbalance between subway transportation capacity and passenger travel demand is prone to occur,which greatly reduces passenger comfort.Therefore,this study adds a passenger comfort target.At the same time,in order to avoid the situation that the newly adjusted timetable deviates greatly from the original timetable after the operation diagram is adjusted,this study adds a target for the rate of change of the operation diagram.Therefore,how to increase the passenger comfort target and the change rate target of the operating graph based on the previous case base only considering the energy-saving research,and optimize and improve the case-based reasoning results is the research purpose of this article.Taking Nanjing Metro Line 10 as the research background,the influencing factors of subway operation energy consumption were comprehensively analyzed,the subway operation energy consumption model was constructed,the case representation was carried out using the frame notation,and the subway operation pattern example library was constructed;the hierarchical analysis was adopted.The method and entropy method are used to calculate the weights of the subjective and objective attributes of the case,and the optimal combination weighting method based on the moment estimation theory is proposed,which solves the problem of large deviation between the subjective and objective weights and the combined weights,and is verified by comparison experiments.The efficiency of the algorithm is verified by the algorithm;the nearest neighbor similarity algorithm is used to calculate the case similarity,and the cases that meet the threshold are obtained,and the retrieval stability of the algorithm is verified by the recall rate and the precision rate.Optimization of subway energy-saving operation pattern examples based on multi-objective decision-making.The calculation methods for two new targets are given: the passenger comfort calculation model based on the satisfactory membership function is used to obtain the passenger comfort value;through the analysis of the measured passenger flow data of Nanjing Metro Line 10,the characteristics of passenger flow based on different time periods are obtained.Based on the site importance value of the site,the calculation formula of the change rate of the operation graph based on the site importance in different periods is proposed.Design experiments,calculate the passenger comfort and the rate of change of the running diagram from the search results of the subway operating pattern database,and introduce the gray relational projection method and TOPSIS algorithm to make multi-objective decision-making,and find out that the subway enterprise’s energy consumption and passenger comfort are consistent.The optimal operation diagram required by the rate of change of the operation diagram.The reliability of the multi-objective algorithm is verified through comparative experiments based on the degree of scheme discrimination.Based on the above method,the prototype design of the multi-objective decision-making system of the operation diagram is carried out.Through the online no-load and passenger-carrying experiments,the effectiveness of the system is verified from the deviation rate from the actual results. |