| 一种基于优化的RBF神经网络交通流预测新算法 |
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| 引用本文： | 杨建华,郎宝华.一种基于优化的RBF神经网络交通流预测新算法[J].计算机与数字工程,2010,38(9):127-129,139. |
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| 作者姓名： | 杨建华 郎宝华 |
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| 作者单位： | 西安工业大学电信学院,西安,710032 |
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| 摘 要： | 提出了一种基于遗传算法优化的RBF神经网络交通流预测新方法,该方法把遗传算法应用于RBF神经网络的参数确定中,实现了RBF神经网络隐层高斯函数的中心矢量和基宽向量以及隐层与输出层之间的权值的优化,提高了RBF神经网络的泛化能力。仿真结果表明：改进的RBF网络用于交通流预测中具有可靠的精度和较好的收敛速度,具有广阔的应用推广前景。
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| 关 键 词： | 遗传算法 RBF神经网络 参数优化 交通流量预测 |
A New Method of Traffic Flow Forecasting Based on Optimized RBF Neural Networks |
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| Yang Jianhua,Lang Baohua.A New Method of Traffic Flow Forecasting Based on Optimized RBF Neural Networks[J].Computer and Digital Engineering,2010,38(9):127-129,139. |
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| Authors: | Yang Jianhua Lang Baohua |
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| Affiliation: | Yang Jianhua Lang Baohua (School of Electronic Information Engineering, Xi＇an University of Technology, Xi＇an 710032) |
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| Abstract: | A new method of traffic flow forecasting based on optimized RBF neural networks using genetic algorithm was improved. Genetic algorithm was applied to optimize position of data centers, widths and weights of RBF neural network in this method. Consequently, RBF neural networks designed with this method could generalize well. The simulation results show that the improved RBF neural networks applied in traffic flow forecasting with reliable accuracy and good convergence rate. The method possesses high value being generalized. |
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| Keywords: | genetic algorithm RBF neural networks parameter optimization traffic flow forecasting |
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