Simulation data analysis using Fuzzy Graphs

Analysis of simulation models has gained considerable interest in the past. However, their complexity still remains a considerable drawback in practical applications. A promising concept is to analyze the data from simulation experiments. Existing approaches are either restricted to simple models or are hard to interpret. We present an efficient algorithm that constructs a fuzzy graph model from simulation data and we show that the resulting system approximates also complex model functions with an adjustable precision. In addition the Fuzzy Graph allows the analyst to directly access easy to interpret if-then-rules. These rules help to understand the original simulation model, which is shown with a real world token bus model.