Forecasting USAF JP-8 Fuel Needs

Abstract

Oil is still one of the strategic energy resources for both the U.S. and the USAF today. Accurate oil prediction is important for the U.S. in order to improve the national strategy and the related budget concerns. Today, the U.S. is roughly importing 58% of its petroleum products. Moreover, in Financial Year (FY) 2007 the USAF total energy costs exceeded $6.9 billion. Aviation fuel accounted for approximately 81% of the total AF energy costs. Fluctuations in oil prices have huge impacts on the USAF's JP-8 budgetary calculations. In order to handle this problem, the need for accurate forecasts arises. In this study, we forecast the USAF's JP-8 consumption and costs for the next five year period. The study shows that the JP-8 consumption figures will go on to follow the recent trend via Holt's Linear Method. Also, the study shows that short-term predictions could be performed with more simple and easy-to-implement methods, versus complex ones. When we consider long-term 5-year forecasts, our multiple regression model outperforms ANN modeling within the specified forecast accuracy measures. Our results indicate that the USAF's JP-8 cost for each of the next 5 years will be somewhere between 6.3 and 7.5 billion dollars, via a multiple regression model.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2009
Accession Number
ADA500354

Entities

People

  • Omer Saglam

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Air Force
  • Business Administration
  • Computational Science
  • Computers
  • Fossil Fuels
  • Fuel Efficiency
  • Information Processing
  • Information Science
  • Information Systems
  • Management Personnel
  • National Security
  • Neural Networks
  • Nonlinear Dynamics
  • Organizational Structure
  • Petroleum
  • Students
  • War Colleges

Fields of Study

  • Environmental science

Readers

  • Computational Modeling and Simulation
  • Economics
  • Life Cycle Cost Analysis