Simulation modelling has emerged as a vital tool for understanding and managing the inherent complexity of numerous systems, from healthcare and manufacturing to logistics and business operations ...

Model-based systems engineering is widely used when designing complex systems, but the question remains of when is it right for your project or system.

‘Systems thinking’,1 2 complexity theory3 and the ‘complex systems approach’4–7 are gaining momentum among leading sports injury researchers. One reason for this is a growing recognition that ...

Scientists have made a significant advancement with quantum technologies that could transform complex systems modelling with an accurate and effective approach that requires significantly re-duced ...

In fields ranging from immunology and ecology to economics and thermodynamics, multi-scale complex systems are ubiquitous. They are also notoriously difficult to model. Conventional approaches ...

Topic: Uncertainty Quantification for Scientific Machine Learning Modeling and Simulations Uncertainty quantification (UQ) in scientific computing research is increasingly important for keeping pace ...

The COVID-19 pandemic has highlighted the potential of complex systems modelling for policymaking but it is crucial to also understand its limitations.

Companies like Atkins, a member of the SNC-Lavalin Group, [DMD1] are using Complex Systems Modeling in their system: the City Simulator to help policymakers plan for multiple disasters.

Xiaoquan Wen, Bayesian Model Selection in Complex Linear Systems, as Illustrated in Genetic Association Studies, Biometrics, Vol. 70, No. 1 (MARCH 2014), pp. 73-83 ...

While the DoD has heavily utilized systems engineering since WWII, modern day defense systems are becoming more complex and call for a different approach to ensure projects stay within budget and are ...

This year, for the first time, the Nobel Prize in Physics was explicitly awarded for research in complex systems—including climate change.