Measurement of the uncertainty

Abstract

Abstract. In recent years, a series of metrics began to develop that allow the quantification of specific properties of process models. These characteristics are, for example, complexity, comprehensibility, maintainability, cohesion and uncertainty. This work is focused on defining a method that allows to measure the uncertainty of process models that was modelled by Stochastic Petri Nets (SPN). The principle of this method consists in mapping the set of all reachable marking of SPN into the continuous-time Markov chain and then calculating its steady-state probabilities. The uncertainty is then measured as the Shannon entropy of the Markov chain (it is possible to calculate the uncertainty of the specific subset of places as well as whole Petri net). Alternatively, the uncertainty is quantified as a percentage of the calculated entropy against maximum entropy.