• Estimating uncertainty of model parameters obtained using numerical optimisation 

      Brastein, Ole Magnus; Lie, Bernt; Pfeiffer, Carlos Fernando; Skeie, Nils-Olav (Peer reviewed; Journal article, 2019)
      Obtaining accurate models that can predict the behaviour of dynamic systems is important for a variety of applications. Often, models contain parameters that are difficult to calculate from system descriptions. Hence, ...
    • Machine Learning in Python for Weather Forecast based on Freely Available Weather Data 

      Abrahamsen, Erik Boye; Brastein, Ole Magnus; Lie, Bernt (Journal article; Peer reviewed, 2018)
      Forecasting weather conditions is important for, e.g., operation of hydro power plants and for flood management. Mechanistic models are known to be computationally demanding. Hence, it is of interest to develop models that ...
    • Parameter estimation for externally simulated thermal network models 

      Brastein, Ole Magnus; Lie, Bernt; Sharma, Roshan; Skeie, Nils-Olav (Peer reviewed; Journal article, 2019)
      Obtaining accurate dynamic models of building thermal behaviour requires a statistically solid foundation for estimating unknown parameters. This is especially important for thermal network grey-box models, since all their ...
    • Parameter estimation for grey-box models of building thermal behaviour 

      Brastein, Ole Magnus; Perera, Degurunnehalage Wathsala U.; Pfeiffer, Carlos Fernando; Skeie, Nils-Olav (Journal article; Peer reviewed, 2018)
      Good models for building thermal behaviour are an important part of developing building energy management systems that are capable of reducing energy consumption for space heating through model predictive control. A popular ...
    • Sensor placement and parameter identifiability in grey-box models of building thermal behaviour 

      Brastein, Ole Magnus; Sharma, Roshan; Skeie, Nils-Olav (Journal article; Peer reviewed, 2019)
      Building energy management systems can reduce energy consumption for space heating in existing buildings, by utilising Model Predictive Control. In such applications, good models of building thermal behaviour is important. ...