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Publication detail

Uncertainty Measurement
Year: 2017
Type of publication: ostatní - článek ve sborníku
Name of source: Mathematical Modeling in Physics and Engineering
Publisher name: Czestochowa University of Technology
Place: Czestochowa
Page from-to: 45-52
Titles:
Language Name Abstract Keywords
eng Uncertainty Measurement 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). 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.