Using RSM, DOE, and Linear Regression to Develop a Metamodel to Predict Cargo Delivery of a Time Phase Force Deployment Document

Abstract

Air Mobility Command (AMC) uses the Airlift Flow Model as their primary tool to estimate the amount of cargo delivered in a Time Phase Force Deployment Document (TPFDD). The primary objective of this research was an exploratory investigation in the development of a metamodel to predict the amount of cargo delivered from a TPFDD by AMC into a theater. In creating a valid metamodel the analyst would be able to quickly provide the decision-maker with accurate insights should input parameters change. This would save valuable time and replace the need to physically change the input parameters and re-run the simulation. Techniques that were applicable to create this metamodel include DOE, RSM, and Linear Regression. Using the techniques outlined in this research a second metamodel was constructed using a separate set of data to validate the procedure. In both cases, the results substantiated good predictive capability between the simulation and the metamodel. The analysis procedures outlined in this effort allows the researcher to identify the salient factors to the metamodel in a timely, efficient manner.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2000
Accession Number
ADA378137

Entities

People

  • Ken S. Browne

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Air Force
  • Aircrafts
  • Combinatorial Analysis
  • Computational Science
  • Computer Simulations
  • Data Science
  • Deployment
  • Experimental Design
  • Factorial Design
  • Information Science
  • Knowledge Management
  • Manufacturing
  • Mathematical Analysis
  • Mathematical Models
  • Regression Analysis
  • Simulations
  • Statistical Analysis

Readers

  • Aerospace logistics and air mobility.
  • Computational Modeling and Simulation