An Investigation of Contemporary Data-Driven Methods Applied to Complex Systems

Abstract

Understanding complex systems by the help of modeling, simulation, and control is a well-known challenge across several application domains. As such, these type of systems are not amenable to empirical models, typically due to their dynamic and non-linear nature. Data-driven methods, have in recent years gained traction regarding their application to such complex systems. This paper presents findings from a systematic literature review of data-driven methods applied to complex systems in recent years. The review is a result of a search strategy resulting in 1106 scientific publications, out of which forty one were identified as primary studies. It is our goal that the review findings will guide researchers with an evidence-base regarding data-driven methods, thereby equipping them with an arsenal of applied methods across various application domains. Also, the objective is to construct a knowledge-base based on these methods' contributions while applied to different types of problems. Additionally, the review findings may also guide researchers to realize potential gaps for future research.