Abstract
The paper proposes the computing environment which allows building forecasts based on System Dynamics models. The environment is equipped with GUI for building dynamic models according to Forrester’s methodology. The unique feature of the application is that the created models can be calibrated with the help of optimization procedures tailored for solving nonlinear least squares problems with differential–algebraic equations. Furthermore, the application enables verification of decision rules inherited in System Dynamics models by solving problems associated with the models dynamic optimization—then the model with optimal decision rules can be simulated to build forecasts of interests. To illustrate the functionalities of the environment, the example of the model of drug prevalence is discussed in some detail.
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Acknowledgements
The work was partially funded by the grant DOB-BIO7/05 /02/2015 of Polish National Office for Research and Development.
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Pytlak, R., Suski, D., Tarnawski, T., Wawrzyniak, Z., Zawadzki, T., Cichosz, P. (2019). Computing Environment for Forecasting Based on System Dynamics Models. In: Valenzuela, O., Rojas, F., Pomares, H., Rojas, I. (eds) Theory and Applications of Time Series Analysis. ITISE 2018. Contributions to Statistics. Springer, Cham. https://doi.org/10.1007/978-3-030-26036-1_4
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DOI: https://doi.org/10.1007/978-3-030-26036-1_4
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