Research

The mission of the Centre for the Mathematics of Human Behaviour (CMoHB) is to to be the originator of modelling concepts, methods and applications delivering high impact and value to public and data rich R&D sectors. Our research focuses on

  • The dynamics of evolving networks - What are the long-term trends of an evolving network? How do cliques form? How can model networks be used to contain the spread of infectious diseases, or reduce radicalisation of elements of society, or improve marketing effectiveness?
  • Agent-based Modelling - How can we best model people's behaviour and make accurate forecasts when events occur for which there is no previous history (for example: new product launches in retail or uptake of electric vehicles in energy).
  • Time Series Analysis - How does people's behaviour change over time? How do we best account for pseudo-periodic patterns without averaging out the peaks?

The main areas of our current research are:

 

Smart Grid Networks

The UK government aims to reduce carbon emissions by encouraging and supporting the uptake of low carbon technologies (LCTs) such as electric vehicles and photovoltaics. The increased uptake of LCTs is expected to increase the electrical energy usage in the UK which may threaten the security of the network and disrupt the supply to customers.

As part of New Thames Valley Vision NTVV project CMoHB in collaboration with the School of Systems Engineering is modelling household and low-voltage (LV) substation level data in order to better understand current and future network demand behaviour as well as look at how smart control can be combined with network storage to reduce peak demand and balance the networks. See more details on the project here: New Thames Valley Vision Project

Temporal Networks

The early 2000s brought some huge developments in social networking and social media. With the increasing importance of social networks it becomes important to have identifying mechanisms and to develop models for social network based interventions.

Our aim is to incorporate social psychological theories in the building of mathematical models of the spread of mood through the networks, and to combine internal and external motivations for behaviour change using actor-based modelling. See more details on our work here: Temporal Networks

Traffic Flow

The Department has also been involved in the analysis of traffic flows to enable smoother transition at traffic lights for cars and pedestrians. More on this research can be found here: Traffic Flow

 

 

 

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