From data to simulation models: Component-based model generation with a data-driven approach

Model building is time-consuming and requires expertise in different areas. In this paper, we propose a data-driven approach for automatic model generation using pre-built and validated model components (or building blocks). We view this approach as an automated reuse of model components. Issues such as modularity and composability of model components are addressed. Models can be generated by automatically selecting, structuring and configuring the model components. The formulated rules can be structural and behavioral, by which a relational representation of the desired model composite structure is incrementally constructed. An example of generating a rail network model is given to demonstrate the steps.