A method for automatic classification of railway dispatching  commands based on deep learning

Xinqin Li; Hongfeng Cao; Shengchun Yan

doi:10.1117/12.2689786

7 September 2023 A method for automatic classification of railway dispatching commands based on deep learning

Xinqin Li, Hongfeng Cao, Shengchun Yan

Proceedings Volume 12790, Eighth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023); 127900X (2023) https://doi.org/10.1117/12.2689786
Event: 8th International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023), 2023, Hangzhou, China

Abstract

A deep learning based scheduling command classification method is proposed for railway scheduling command text data. Firstly, text preprocessing is performed on the scheduling command, and Word2VEC is used to train the word vector of the scheduling command; To address the issue of imbalanced scheduling command data samples, the SMOTE method is used to automatically generate subcategory samples; Then, the word vector is embedded into the CNN input layer, and the features of the text are extracted using the convolutional and pooling layers of the CNN. The scheduling command is automatically classified using a SoftMax classifier. Through experimental verification of partial railway dispatch command data and comparison with other classification models, the experimental results show that the text classification method proposed in this paper can significantly improve various evaluation indicators

Citation Download Citation

Xinqin Li, Hongfeng Cao, and Shengchun Yan "A method for automatic classification of railway dispatching commands based on deep learning", Proc. SPIE 12790, Eighth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023), 127900X (7 September 2023); https://doi.org/10.1117/12.2689786

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