The invention provides a train positioning method based on cross-line composite transfer learning, and the method is characterized in that the method comprises the steps: training an existing deep learning model through employing a mature line A as a source domain, and obtaining an available target domain deep learning model of the target domain of the line B through model parameter migration and statistical feature change method migration, and positioning the train operating on the line B through the available target domain deep learning model. By adopting the train positioning method provided by the invention, the deep learning model for train positioning can be quickly obtained for training and verifying a new train running line, and the output precision of the model on the train positioning position can be improved through the method, so that the train positioning accuracy and stability are improved.
本发明提供了一种基于跨线路复合型迁移学习的列车定位方法,其特征在于:所述列车定位方法包括:利用成熟线路A作为源域训练出的已有深度学习模型,通过模型参数迁移和统计特征变化法迁移后得到线路B这个目标域的可用目标域深度学习模型,通过可用目标域深度学习模型对线路B上运营的列车进行定位。采用本发明所述的列车定位方法,能快速为新的列车运行线路训练和验证得到用于列车定位的深度学习模型,且通过上述方法还能提高模型对列车定位位置的输出精度,从而提高列车的定位准确性和稳定性。
Train positioning method based on cross-line composite transfer learning
基于跨线路复合型迁移学习的列车定位方法
2022-07-29
Patent
Elektronische Ressource
Chinesisch
IPC: | G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / B61L Leiten des Eisenbahnverkehrs , GUIDING RAILWAY TRAFFIC / G06K Erkennen von Daten , RECOGNITION OF DATA / G06Q Datenverarbeitungssysteme oder -verfahren, besonders angepasst an verwaltungstechnische, geschäftliche, finanzielle oder betriebswirtschaftliche Zwecke, sowie an geschäftsbezogene Überwachungs- oder Voraussagezwecke , DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES |
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