Abstract
Ridership forecast is one of the important bases for urban rail transport network planning, design, construction and operation. For the shortcomings of traditional ridership forecast in the stiff human-computer interaction forms, the signal forecast model, the low computational efficiency and the intensive labor, multi-agent-based urban rail transport ridership forecast system was designed. The Man-Machine-Agent accepted the data from the users and allocated the forecast task to the Management-Agent, in the collaboration and coordination to the next Data-Evaluation-Agent, Model-Selection-Agent, Ridership-Forecast-Agent, returned the forecast results to the Man-Machine-Agent and gave the users the proposed forecast advice and guidance by the User-Proposed-Agent. The system have the excellence of playing a variety of forecast models for a variety of different conditions, and can satisfy the randomness, non-linear and non-deterministic case for the strong adaptability, robustness and flexibility.
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