Date of Award

3-21-2019

Document Type

Thesis

Degree Name

Master of Science in Operations Research

Department

Department of Operational Sciences

First Advisor

Darryl K. Ahner, PhD

Abstract

Understanding what causes countries to be in a state of violent conflict is of vital importance to developing realistic national strategies on both a regional and global scale. Given these causes, it is important to understand the effects of missing data, how to impute that data, and the interrelation between data elements. Utilizing both open source data and previously generated equations that predict a country’s likelihood to transition conflict statuses, this research projects data into the future and predicts each nations’ subsequent conflict statuses. Future data is populated using a novel approach inspired by stochastic regression imputation. The replicated future data and predictions were interpreted as alternative futures of regional conflict in both the Arab world and Southeast Asia. The conflict occurrences in the Arab world region were projected to trend upward compared to the region’s historic behavior. In Southeast Asia, the next ten years forecasted a decline in total violent conflicts. Regional scenarios where the elements of national power influenced a data element were implemented to learn how alternative futures might be effected. These results can inform military and political leadership on the ever changing conflict landscapes in two world regions of immense political and strategic importance.

AFIT Designator

AFIT-ENS-MS-19-M-128

DTIC Accession Number

AD1077401

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