Optimization Operation Technology with Dynamic Feedback Mode for High-speed Railway

The study of the optimizing operation technology of high-speed railway has a great significance for achieving the economic benefit maximization. Therefore, a novel prediction method for the characteristics of passenger flow of high speed railway was designed in this paper, which combined wavelet decomposition, Relief algorithm feature selection and differential evolution support vector machine to establish a new scientific and accurate prediction model of passenger flow of high-speed railway, and then based on this prediction model, according to the mutual dynamic effect relationship among high speed railway faxes,operation diagram and passenger flow, using the dynamic feedback bi-direction compensation mechanism and the modified multi-objective differential evolution algorithm to optimize the operation technology of high speed railway, then the prediction results of passenger flow of high speed way will be used to optimize and guide the ticket pricing of high speed railway and the planning of operation diagram, and making the operation of high speed railway tends to optimal in the process of dynamic and bi-directional adjustment eventually by modifying the prediction model hierarchically and dynamically according to the feedback of changes of passenger flow of high speed railway after the operation optimization. Those studies will have an important theoretical and practical values for improving the market competitiveness and realizing the operation benefit maximization in high speed railway.