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This dataset contains source code of Modelica models of Glucose-Insulin regulation using different techniques. Accompanying Jupyter notebook is demo for system analysis (parameter estimation) of artificial data and to match model simulation able to be used in Teaching class. ModelicaIdentification.ipynb - default notebook - code contains ellipsis which needs to be replaced as per instruction in text ModelicaIdentificationResolution.ipynb - notebook - code with exemplar solution to default notebook glucoseinsulin.mo - Modelica source code PatientInsulinConcentration.csv - sample data to be fitted against model seminar11hw.GIExperiment.fmu - FMU exported from Modelica in order to run simulation in Python and PyFMI library Thanks to the MYBINDER service, the Jupyter notebook can be viewed and executed as https://mybinder.org/v2/zenodo/10.5281/zenodo.3633324/ note that you need to launch terminal first in Jupyter -> New -> Terminal and install pyfmi and matplotlib by: conda install -c conda-forge pyfmi matplotlib Most recent version with other models and notebooks https://mybinder.org/v2/gh/creative-connections/Bodylight-notebooks/master?filepath=Seminar11GlucoseInsulinIdentification/
Modelica, Jupyter notebook, glucose-insulin model
Modelica, Jupyter notebook, glucose-insulin model
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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| downloads | 16 |

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Downloads provided by UsageCounts