Modelling the variation in human decision making
Turhan Ozen, Jonathan M. Garibaldi, Salang Musikasuwan · IEEE Annual Meeting of the Fuzzy Information, 2004. Processing NAFIPS '04. · 2004
This paper presents the results of the research on modelling the variation in human decision making. The relationship between the uncertainty introduced to the membership functions (mfs) of a fuzzy logic system (FLS) and the variation in FLS's decision making is explored using two separate methods. Initially uncertainty is introduced to a type-1 FLS by adding noise to its mfs and the effect on decision making is examined. Secondly an interval type-2 FLS is developed by representing the terms used in the FLS with interval type-2 fuzzy sets and the variation in decision making is studied using the FLS's interval outputs. The variations in ranking of umbilical acid-base assessments by six experts are compared to the simulation results from the developed FLSs. It is shown that there is a direct relationship between the variation in decision making and the uncertainty in the linguistic terms used, and the level of variation is proportional to the magnitude of uncertainty.