Continuous Time Stochastic Modelling

 The project on continuous time stochastic modelling (CTSM) is very useful for grey-box modelling of physical systems using data. The grey-box modelling approach bridges the gap between physical and statistical modelling.
The solution is widely used for estimating and identifying models for physical systems, like the heat dynamics of a building, the hydraulics in a rainfall run-off system, bacterial growth, pharmacokinetic-pharmacodynamic (PK/PD) models, the dynamics of a heat pump, etc.In this framework the dynamics is described in continuous time, which implies that any physical prior knowledge is easily formulated as a part of the model. CTSM is therefore well suited for modelling both nonlinear and non-stationary systems.Observations are discrete time data (time series), and there are no restriction on the sampling time, which can be either constant or fully varying in time.

Further description and insights into the project is coming soon.

In the meantime please read more here

Contact

Henrik Madsen   Professor for Applied Mathematics and Computer Science, Center Manger of CITIES Research Project  at DTU Compute

+ 45 45253408
henrik.madsen@smart-cities-centre.org
Copyright © 2018 | CITIES Innovation Center
Article location: https://www.citiesinnovation.org/continuous-time-stochastic-modelling/

Leave a Reply

Your email address will not be published. Required fields are marked *

Popular articles

Solution#6: Heat Pump Controller

The Heat Pump Controller is a price responsive predictive controller for heat pumps in domestic houses. With the new controller, energy costs can be reduced by demand modelling and controlling of the heat pump. By means of flexible demand side response, a balance between energy production and consumption is achieved using a market price responsive …