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Ghoddousi, P., Eshtehardian, E., Jooybanpour, S. and Javanmardi, A. (2013) When the Maximal Iteration Number for the Generation Is Reached, the Training Process for the Network Must Be Terminated, and the Established MLP Is Considered as a Well-Trained Network. Automation in Construction, 30, 216-227. http://dx.doi.org/10.1016/j.autcon.2012.11.014

has been cited by the following article:

• TITLE: Application of Artificial Neuron Network in Analysis of Railway Delays

  AUTHORS: Jia Hu, Bernd Noche

  KEYWORDS: Train-Delay Prediction, Artificial Neuron Network, Improvement of Artificial Neuron Network, Delay Reasons of Railway Freight

  JOURNAL NAME: Open Journal of Social Sciences, Vol.4 No.11, November 29, 2016

  ABSTRACT: 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.