Short-term Section Passenger Flow Prediction And Organization Optimization Of Urban Rail Transit

As an indispensable mode of transportation,urban rail transit has significant advantages in alleviating traffic congestion,optimizing spatial structure,improving the natural environment,and optimizing land resources.So it has developed rapidly in developed cities at home and abroad by virtue of its convenient,reliable,safe,and punctual functional features.However,at the same time as the development of urban rail transit,there are also problems such as congestion during peak hours,wasted transportation capacity during peak hours,and unclear traffic organization.The organization optimization can solve this problem well,which is closely related to the prediction of short-term section passenger flow.Therefore,improving the accuracy of short-term section passenger flow prediction is of great significance to the organization optimization.In terms of short-term section passenger flow prediction of urban rail transit,this paper introduced the method of organization optimization based on the time and space characteristics of section passenger flow.A section passenger flow data structure was established,which made it easier for the model to integrate and call data.And section passenger flow was processed by noise reduction and cluster analysis.After that,the Chicken Swarm Optimization was optimized and improved from three aspects: population initialization,constraints,and evolutionary mechanisms.The Wavelet Neural Network optimized by the Improved Chicken Swarm Optimization was used to predict the section passenger flow,and compared with the optimization effect of Genetic Algorithm and Particle Swarm optimization.Experiments show that ICSO-WNN’s prediction accuracy for short-term section passenger flow reaches 99.01%,which is better than GA-WNN and PSO-WNN.In terms of the organization optimization and system development of urban rail transit,this paper took the section passenger flow data of a subway company as an example to verify the prediction accuracy of the short-term section passenger flow prediction model and the effectiveness of the organization optimization scheme.Visual Studio 2017 and Matlab 2018 a was used as tools for the development of Urban Rail Transit Short-term Section Passenger Flow Prediction and Organization Optimization System,which was written using C#.The system takes historical vehicle passenger capacity as input,and outputs the predicted section passenger flow and the organization optimization scheme.It can provide a basis for the formulation of the organization optimization scheme for urban rail transit.