首页> 外文会议>Knowledge Discovery and Data Mining, 2010. WKDD '10 >Transit Vehicle Dispatching Based on Genetic Algorithm-RBF Neural Network
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Transit Vehicle Dispatching Based on Genetic Algorithm-RBF Neural Network

机译:基于遗传算法-RBF神经网络的公交车辆调度

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Transit vehicle reasonable dispatching is very important to solve the congestion of traffic. Artificial neural network is the common dispatching method, among which RBF neural network is a feed-forward neural network with one hidden layer, which can uniformly approximate any continuous function to a prospected accuracy. In RBF neural network, the choice of the widths and centers of the Gaussian function, the output weights will affect the accuracy of RBF neural network model. In the paper, genetic algorithm is employed to determinate the RBF neural network's parameters. The genetic algorithm-RBF neural network is studied and applied to transit vehicle dispatching. The experimental results show that the calculation results of GA-RBF neural network are consistent with actual results.
机译:过境车辆的合理调度对于解决交通拥堵非常重要。人工神经网络是常见的调度方法,其中RBF神经网络是具有一个隐藏层的前馈神经网络,可以将任何连续函数均匀地逼近预期的精度。在RBF神经网络中,选择高斯函数的宽度和中心,输出权重将影响RBF神经网络模型的准确性。本文采用遗传算法确定RBF神经网络的参数。研究了遗传算法-RBF神经网络,并将其应用于运输车辆调度中。实验结果表明,GA-RBF神经网络的计算结果与实际结果吻合。

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