Characterization of Uncertainty in ETMS Flight Events Predictions and its Effect on Traffic Demand Predictions (Paperback)

Eugene P. Gilbo

ISBN 10: 1495416194 / ISBN 13: 9781495416194

Published by Createspace Independent Publishing Platform, 2008

About this Item

Paperback. This report presents the results of analysis and characterization of uncertainty in traffic demand predictions using Enhanced Traffic Management System (ETMS) data and probabilistic representation of the predictions. Our previous research, described in two prior reports, was focused on analysis of aggregate 15-minute traffic demand predictions in ETMS, on improving the accuracy of these predictions and increasing the stability of the ETMS monitor/alert function, while not explicitly considering the uncertainty in predictions of flight events for individual flights. This study continues the previous one. It also focuses on uncertainty in traffic demand predictions, but, unlike the previous one, it explicitly considers uncertainty in individual flights' predictions for estimation of uncertainty in aggregate demand count predictions at National Airspace System (NAS) elements and for probabilistic representation of those predictions. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Seller Inventory # 9781495416194

Bibliographic Details

• Title: Characterization of Uncertainty in ETMS Flight Events Predictions and its Effect on Traffic Demand Predictions (Paperback)
• Publisher: Createspace Independent Publishing Platform
• Publication Date: 2008
• Language: English
• ISBN 10: 1495416194
• ISBN 13: 9781495416194
• Binding: Paperback
• Condition: new

About this title

Synopsis

This report presents the results of analysis and characterization of uncertainty in traffic demand predictions using Enhanced Traffic Management System (ETMS) data and probabilistic representation of the predictions. Our previous research, described in two prior reports, was focused on analysis of aggregate 15-minute traffic demand predictions in ETMS, on improving the accuracy of these predictions and increasing the stability of the ETMS monitor/alert function, while not explicitly considering the uncertainty in predictions of flight events for individual flights. This study continues the previous one. It also focuses on uncertainty in traffic demand predictions, but, unlike the previous one, it explicitly considers uncertainty in individual flights’ predictions for estimation of uncertainty in aggregate demand count predictions at National Airspace System (NAS) elements and for probabilistic representation of those predictions.