Model Order Reduction of Deterministic Microscopic Models - A Case Study

Abstract

In this paper we present a method for model order reduction of microscopic models, i.e. models that consist of a high number of entities that can interact and cooperate with each other. Due to this high numbers of entities such models are often highly computationally expensive. But classic model order reduction techniques often use the equations the models are based on to simplify the model and make it more performant. These approaches are not applicable for microscopic models. We present a data-based approach for model order reduction using radial basis functions and analyze the specifics and opportunities of model reduction for microscopic models. As a case study Conway’s Game Of Life is used.