基于人工神经网络的世博园行人交通组织优化方案
首发时间:2012-12-17
摘要:针对世博园等国际大型博览会行人交通的特点,基于对西安世园会的实地调研,进行数学模型分析, 引入人工神经网络的调控方法,将园区客流拟化成神经电流,把园区内各景点作为神经兴奋点。通过统计及流量与人流关系公式,得到世博园相应的人流密度,建立标准ρk ;建立各时段相应的人流密度曲线并划分为若干时段,在问卷调查及统计分析的基础上,得到游客兴奋度曲线图。并通过改变兴奋点的兴奋度来对客流进行调控,可以实现园区内行人交通组织的优化,提高运行效率。
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Optimization of tourist organization in Expo based on ANN
Abstract:Based on the investigation in Xi'an expo, and considering to the traffic characteristics of pedestrian, we use the mathematical model to analysis this problem with the introduction of artificial neural network. With this method, we simulate the passenger flow into neural current and the scenery spot into t. Through statistics and the flow formula, it seems to get corresponding flow density, and establish the standard ρk. We establish corresponding flow density curve and divide it into several periods of time, and get visitors' exciting plot on the base of questionnaire investigation and statistics. Also by changing the excitement of nerve spot we can control the passenger flow, and realize the optimization of the traffic organization, so that it can improve operation efficiency.
Keywords: large-scale event the International Horticultural Expo neural network tourist traffic exciting point
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