摘要
通过全面分析遗传算法和神经网络的优缺点,在充分考虑各种可量化因素的影响权重的基础上,建立了遗传神经网络模型,提出了城市公共交通枢纽客流量预测实用方法,并通过实例进行了分析验证。结果表明,该方法在城市公共交通枢纽客流量预测的应用过程中具有较强的学习能力和自适应性,,其预测的精度明显得到提高。
Taking full consideration of quantifiable influencing factors, a genetic neural network model was developed based on the features of genetic algorithm and neural network, Then a practical forecast method of passenger volume for urban public transport hub was brought forward. The method was validated by an example. The result shows that the passenger volume forecast method is equipped with learning ability and self-adaptability in the forecast course for urban public transport hub, and the prediction precision is good.
出处
《公路交通科技》
CAS
CSCD
北大核心
2005年第8期110-113,117,共5页
Journal of Highway and Transportation Research and Development
基金
国家十五科技攻关项目<城市公共交通系统优化技术>(2002BA404A04)
关键词
公共交通枢纽
遗传算法
神经网络
遗传神经网络
客流量预测
Urban public transport hub
Genetic algorithm
Neural network
Genetic neural network
Passenger volume forecast
