Search Results for author:
Found 5 papers, 0 papers with code
Multi-Graph Convolutional-Recurrent Neural Network (MGC-RNN) for Short-Term Forecasting of Transit Passenger Flow
Spatial dependencies, temporal dependencies, inter-station correlations driven by other latent factors, and exogenous factors bring challenges to the short-term forecasts of passenger flow of urban rail transit networks.
Data-driven Method for Estimating Aircraft Mass from Quick Access Recorder using Aircraft Dynamics and Multilayer Perceptron Neural Network
This paper presents a data-driven method involving use of the quick access recorder (QAR)-a digital flight-data recorder-installed on all aircrafts to record the initial aircraft climb mass during each flight.
From Aircraft Tracking Data to Network Delay Model: A Data-Driven Approach Considering En-Route Congestion
In this study, we propose a new flight delay model, Multi-layer Air Traffic Network Delay (MATND) model, to capture the impact of en-route congestion on flight delays over an air traffic network.
An Incremental Clustering Method for Anomaly Detection in Flight Data
It trains an initial GMM model based on historical offlline data.
Flight Time Prediction for Fuel Loading Decisions with a Deep Learning Approach
We also show that, with the improved flight time prediction, fuel loading can be optimized and resulting in reduced fuel consumption by 0. 016%-1. 915% without increasing the fuel depletion risk.
