Project Introduction In this project, the goal is to develop a Long Short-Term Memory (LSTM) model to predict traffic flow across different roads. With increasing traffic congestion in urban areas, ...

This article investigates a traffic-flow forecasting problem based on long–short term memory (LSTM), an artificial recurrent neural network architecture used in deep learning. By representing the road ...

The flow information is collected from High-Speed Railway data network and preprocessed to obtain time-flow series. Two time-flow series are used to verify the network flow forecasting accuracy.

This repository is the implementation of MGN-LSTM, a novel graph neural network-based, deep-learning models for multiphase flow in carbon capture and storage (CCS) reservoirs with complex fault ...