Subway train ATO speed curve prediction method based on BP neural network

The invention discloses a subway train ATO speed curve prediction method based on a BP neural network. The method comprises the following steps of establishing a train operation influence factor evaluation system based on a train ATO driving strategy, and determining the sample data; establishing a BP neural network model for the comprehensive prediction of an ATO speed curve of the subway train on the basis of the importance ranking result of the influence factors, determining the value boundary of the number of hidden layer units of the BP neural network model, setting the learning rate of the BP neural network model, and initializing the parameters of the BP neural network model; performing normalization processing on the sample data, determining a training sample and an inspection sample, and respectively inputting the training sample and the inspection sample into the BP neural network model for learning training and accuracy inspection; and utilizing the trained BP neural network model to predict the AT