مقاله تشخیص خطای مدار خط راه‌آهن با استفاده از شبکه‌های عصبی مصنوعی

عنوان مقاله فارسی: تشخیص خطای مدار خط راه‌آهن با استفاده از شبکه‌های عصبی مصنوعی عنوان مقاله لاتین: Railway Track Circuit Fault Diagnosis Using Recurrent Neural Networks نویسندگان: Tim de Bruin; Kim Verbert; Robert Babuška تعداد صفحات: 10 سال انتشار: 2017 زبان: لاتین Abstract: Timely detection and identification of faults in railway track circuits are crucial for the safety and availability of railway networks. In this paper, the use of the long-short-term memory (LSTM) recurrent neural network is proposed to accomplish these tasks based on the commonly available measurement signals. By considering the signals from multiple track circuits in a geographic area, faults are diagnosed from their spatial and temporal dependences. A generative model is