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Application of Artificial Neuron Network in Analysis of Railway Delays

机译:人工神经网络在铁路延误分析中的应用

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Punctuality is a key performance indicator of train freight transport. However, train delay arises often in the practice. To improve the efficiency of cargo train, prediction of train delay is always an important research area. In this paper, a prediction model is established on the base of artificial neural network (ANN). Due the endogen drawback of ANN, Genetic Algorithm is adopted to improve the performance of ANN. Consequently, an experiment is design to train and test the ANN-based model by a set of data from the practice. The results of the experiment demonstrate the significant propagation ability of the model.
机译:守时是火车货运的关键绩效指标。然而,在实践中经常出现火车延误。为了提高货运列车的效率,预测列车延误一直是重要的研究领域。本文基于人工神经网络(ANN)建立了预测模型。由于人工神经网络的内生缺陷,采用遗传算法提高人工神经网络的性能。因此,设计了一个实验,以通过实践中的一组数据来训练和测试基于ANN的模型。实验结果证明了该模型的显着传播能力。

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