The present disclosure provides a deep learning-based stop control method and system for a high-speed train, and relates to the technical field of rail transit management and control. The method includes: obtaining a training data set; establishing a convolutional neural network (CNN); training and optimizing the CNN by using the training data set, to obtain an optimized CNN; obtaining actual running data of a to-be-controlled train; inputting the actual running data into the optimized CNN to obtain a stop position of the to-be-controlled train; determining whether the stop position of the to-be-controlled train is 0; and if the stop position of the to-be-controlled train is 0, outputting a breaking command; or if the stop position of the to-be-controlled train is not 0, performing the step of “obtaining actual running data of a to-be-controlled train”. The present disclosure can ensure accurate stop of a high-speed train without high costs.


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    Title :

    DEEP LEARNING - BASED STOP CONTROL METHOD AND SYSTEM FOR HIGH-SPEED TRAIN


    Contributors:
    YIN JIATENG (author) / NING CHENHE (author) / SU SHUAI (author) / LI KAICHENG (author) / TANG TAO (author)

    Publication date :

    2022-04-28


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    IPC:    B61H Bremsen oder andere Verzögerungseinrichtungen ausgebildet für Schienenfahrzeuge , BRAKES OR OTHER RETARDING APPARATUS PECULIAR TO RAIL VEHICLES / G06K Erkennen von Daten , RECOGNITION OF DATA / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen



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