Team:Manchester/Model/ParameterRelationships
Parameter Relationshpis Analysis
Contents
Overview and Motivation Methodology Results ConclusionsOverview and Motivation
During the early experimental phase of the model production, it was noticed that for some parameters the actual value did not matter too much, these 'sloppy' parameters could have a large range of values with minimal impact on the main model predictions. Instead it was notices that these parameters were often grouped and whilst individually they are 'sloppy' some relationship between them is in fact not. This analysis is to look at and highlight these realtionships.
Return to top of pageMethodology
The model was run many times, the concentration vs time data was then compared with experimental data.
The data was assessed using a mean squared error
$$MSE = n^{-1}{\sum_{i=1}^n(y_{i,experimental}-y_{i,model})^2}$$the top 10% of model runs were recorded. The parameter sets which generated this data was then stored.
This process was repeated Return to top of page
Results
PLACEHOLDER FOR GRAPHS, 2D and 3D
Return to top of pageConclusions
PLACEHOLDER
Return to top of page Return to overview
