Application of Fuzzy Expert Systems in Assessing Risk Management in the US Army

Abstract

A risk management process is most effective when the users are properly educated on the process and the process itself promotes a uniform perception of risk. Every soldier in the US Army is expected to be capable of managing risk— eliminating it when possible or mitigating it to an acceptable level through the principles and application a formal, multistep, iterative process known as the US Army Risk Management program. This paper describes a study in which the researchers developed and used a fuzzy rule based expert system to evaluate a respondent population’s ability to assess risk using the US Army’s Risk Management program, and to determine if there were any common characteristics amongst those respondents with similar output. The results showed that while some factors such as active duty versus reserve status yielded negligible differences, there existed a significant difference between the way the commissioned and noncommissioned officer participants perceived risk. This information is one key to understanding that the differences in the way commissioned and non-commissioned officers are taught the Risk Management process and how it can affect their perceptions of risk and suggests that a better, more uniform method of risk training could be developed for the training audiences.