Time Series Analysis of Stochastic Networks with Correlated Random Arcs
Abstract
While modern day weather forecasting isn't perfect, there are many benefits given by the multitude and variety of prediction models. In the interest of routing airplanes, this paper uses time series analysis on successive weather forecast predictions to create wind based fuel-burn networks with stochastic correlated arcs. Networks are populated with either deterministic or ensemble based weather data, and the two data sources with and without time series analysis are compared. Methods were compared by fuel burn prediction accuracy and ability to predict a future optimal path. Of the four options, the ensemble-based methods were on average the least accurate. Using time series analysis with ensemble data gave a nominal change in correct future path prediction and an increase in fuel burn prediction accuracy. The deterministic method gave the most accurate results but the worst correct future path prediction rate. Time series analysis with deterministic data had a marginal decrease in accuracy but the highest correct future path prediction rate.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 04, 2019
- Accession Number
- AD1077554
Entities
People
- Brendon T. Sands
Organizations
- Air Force Institute of Technology