Jun 13, 2024 · This study introduces a novel approach that integrates dynamic Bayesian network with attention based spatio-temporal graph convolutional ...

Jul 2, 2024 · Abstract—This study introduces a novel approach that integrates dynamic Bayesian network with attention based spatio-temporal graph ...

Jun 13, 2024 · This study introduces a novel approach that integrates dynamic Bayesian network with attention based spatio-temporal graph convolutional ...

Jul 29, 2022 · It captures the complex nonlinear relationship between various factors affecting train delay, as well as the dynamic spatio-temporal dependence ...

Oct 22, 2024 · Xu, Li, and Ding (2022) proposed a dynamic spatio-temporal graph convolutional network (DB-STGCN) model, which employed a Bayesian combined ...

In this paper, we propose a Spatial–Temporal and Bi-directional Long Short-Term Memory (ST-BiLSTM) model to deal with the train delay prediction problem. The ...

For train dispatching and emergency planning, we offer a deep learning framework called the train spatio-temporal graph convolutional network (TSTGCN) that can ...

Jul 2, 2024 · Xu, Li, and Ding (2022) proposed a dynamic spatio-temporal graph convolutional network (DB-STGCN) model, which employed a Bayesian combined ...

Railway Delay Prediction with Spatial-Temporal Graph Convolutional Networks ... This trains the model for a default of 25 epochs. The accuracy metrics are ...

According to the spatio-temporal characteristics anddynamic spatio-temporal correlation of highspeed train operationdata, this paper builds a TSTGCN model based.