modules

This module will probe new developments in complex systems modelling. The current era of big, complex and diverse datasets necessitates the development and understanding of complex system models. In this module, you will explore how simple rule-based inter-connected systems can give rise to enormous complexity in natural and man-made systems. Informed by practical examples, you will learn concepts from nonlinear dynamics such as chaos and bifurcation in deterministic and stochastic systems, fractal geometry, complex networks, emergence in cellular automata, self-organization, adaption, feedback loops, random fields and cascaded failures. Using state-of-the-art scientific computing software, you will simulate and develop your understanding of the nonlinear and often chaotic behaviours of weather sciences, interconnected power systems and financial systems; and visualise the real-life patterns found in remote sensing images of coastlines, plant leaves, animal skins and chemical reactions.

Prerequisites: MTHM607 ; Students should also have a general understanding of dynamical systems and differential equations at undergraduate level.

_{Please note that all modules are subject to change, please get in touch if you have any questions about this module.}