Efficient predictive modelling

 

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Keywords
  • Hybrid models
  • Predictive models 

 

Technology & Advantages
Our group develops models that combine physically-based models and data-based models. Our models can overcome the limitations of standard models in terms of prediction performances.

 

The UCL background
The system analysis group has over 30 years experience in the modelling of dynamical systems in a wide variety of application fields, ranging from biological and chemical systems to environmental systems, via hydraulic systems (including predictions of heavy rains and floods), electrical systems, mechanical systems and biomedical systems.

 

The UCL collaboration offer
The system analysis group proposes the development and validation of hybrid models, i.e. combinations of physicallybased models and data-based models, in a wide spectrum of applications that can include for instance the prediction of electricity generated by wind farms or the prediction of the physical performance of a (top) athlete.

 

Technology Status
TRL 5 : technology validation in relevant environment

 

Preferred partnership
Collaborative projects
Development of the technology

 

Interested to collaborate and co-develop this technology ?
Please contact :

Céline DESSAUCY 
Technology Transfer Advisor 
010 47 86 13 
celine.dessaucy@uclouvain.be 
www.ltto.com