Date of Award
3-2024
Document Type
Thesis
Degree Name
Master of Science in Cost Analysis
Department
Department of Systems Engineering and Management
First Advisor
Robert D. Fass, PhD
Abstract
This paper seeks to model risk classification levels (A-D) for 122 Space Vehicle programs. Models include multinomial logistic regression as well as random forest, a machine learning technique based on decision trees. We use independent variables (IVs) which are theoretically correlated to risk class for the regression and one random forest model. We then include all IVs and allow the random forest technique to use those which provide the most information on risk class before paring down the number of IVs to only 7. We show that the accuracy of predictions increases from 62% to 87% by using random forest and emphasize the adaptability of the models developed in code to new data.
AFIT Designator
AFIT-ENV-MS-24-M-124
Recommended Citation
Gwaltney, Collin A., "Standardization of Risk Classifications for Unmanned Space Vehicle Missions" (2024). Theses and Dissertations. 7794.
https://scholar.afit.edu/etd/7794
Included in
Artificial Intelligence and Robotics Commons, Risk Analysis Commons, Systems Engineering and Multidisciplinary Design Optimization Commons
Comments
A 12-month embargo was observed for posting this work on AFIT Scholar.
Distribution Statement A, Approved for Public Release. PA case number on file.