基于多智能体的城市轨道交通客流量预测系统研究

Yi-song Liu, Hai-mei Liu, Jing-bo Zhao
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引用次数: 1

摘要

客流量预测是城市轨道交通网规划、设计、建设和运营的重要依据之一。针对传统的城市轨道交通客运量预测存在人机交互形式僵硬、信号预测模型单一、计算效率低、劳动强度大等缺点,设计了基于多智能体的城市轨道交通客运量预测系统。人机代理接收用户提供的数据,将预测任务分配给管理代理,在协同协调下由data - evaluation - agent、Model-Selection-Agent、rider - forecasting - agent将预测结果返回给人机代理,并由用户建议代理向用户提出预测建议和指导。该系统具有适合多种不同条件下的多种预测模型的优点,能够满足随机性、非线性和非确定性情况,具有较强的适应性、鲁棒性和灵活性。
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On multi-agent based urban rail transport ridership forecast system
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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