Numerical interval simulation: combined qualitative and quantitative simulation to bound behaviors of non-monotonic systems

Abstract

Models of complex physical systems often cannot be defined precisely, either because of lack of knowledge or because the system parameters change over time according to unknown phenomena. Such systems can be represented by semi-quantitative models that combine both qualitative and quantitative knowledge. This paper presents Numerical Interval Simulation, a method that can produce tight predictions of systems involving nonmonotonic functions. We present a successful application of NIS to predict the behavior of a complex process at a Brazilian-Japanese steel company. We claim that such capability of simulating nonmonotonic functions is fundamental in order to handle real-world complex industrial processes. 1