基于模糊-神经网络的公交出行不确定性研究

为了合理规划公交线路,优化公交路网,提高乘客的舒适性,在交通工程学、模糊理论的指导下,通过对影响公交出行的主要因素定性分析,确定了影响出行生成量的模糊因素;结合对某地公交出行实地调研,分析出影响因素与出行量之间的相互关系规律;并采用空间静态模糊预测方法对调研数据进行处理,从而得到公交出行中快捷、舒适、方便、安全的隶属度,最后结合BP人工神经网络预测出该地区的公交出行生成量,为交通设施的建设提供了理论依据.

Transit Trip Generation Uncertainty Based on Fuzzy Neural Networks

There are certainty factors and uncertainty factors that influence the transit trip generation. Under the guidance of Traffic Engineering and fuzzy theory, for the purpose of planning the bus lines rationally and optimizing the transit network and making passengers feel more comfortable in their travel, the major factors that influence the trip generation were analyzed and the fuzzy factors were identified. With the help of spot investigation of transit trips in a certain place, this paper analyzed the relationship between the influential factors and trip generation. The static fuzzy prediction methods were employed to get the membership of speed, comfort, convenience and security. Finally, the BP Artificial Neural network was utilized to predict the regiong travel traffic. This paper intends to provide a theoretical basis for the development of public transit facilities in a region.