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Urban rail transit as a way of public transport in the city, there is a big difference with the conventional public transport in terms of project investment, operating characteristics, the network density. Urban rail traffic passenger flow forecast is an important basis for urban rail transit reasonable line network planning, design, construction and operation of the stereotype exists for the traditional passenger traffic forecasting system support in the form of human-computer interaction, a single prediction model calculation inefficient, labor strength and shortcomings, passenger flow forecast system design is based on Multi-Agent Systems (Multi-Agent System, MAS). The main functions include: (1) analysis and study of the particularity of the passenger flow forecasting system complexity, operational features, and hierarchical distribution structure, according to the Suzhou city rail transportation planning requirements, given the range of passenger flow forecast, age, according to The premise for the design and development of passenger flow forecast system and method. (2) designing the prediction system structure, the structure contains the supporting layer, the hierarchical structure of the application layer and the interface layer is composed by sections the workstation Agent, line Agent and reticle Agent. Sections of passenger flow forecast information sections Workstation Agent, and sections of the workstation as an Agent with the other sections of the workstation on the line to coordinate scheduling, passenger flow projections of the line obtained by the prediction model; then the line as an Agent with other lines coordination of scheduling, the final line network of passenger flow forecast. (3) \model, mode split model and traffic assignment model point of passenger flow forecast model. (4) Joint JADE platform, TransCAD, Mapinfo and the Microsoft SQL Server software, the design of the passenger flow forecasting system, the passenger flow forecast problem into multiple collaborative Agent unit, can be an effective solution to the passenger flow forecast system complexity and distribution of sexual problems. Using close-range 2020 traffic demand forecast analysis, line analysis and line of the network passenger flow forecast passenger flow forecast. The results show that the system has strong adaptability, robustness and flexibility to meet the complexity of the forecasting process, randomness characteristics.
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