Generalized sensitivity functions for size-structured population models
@article{Keck2014GeneralizedSF, title={Generalized sensitivity functions for size-structured population models}, author={Dustin D. Keck and David M. Bortz}, journal={Journal of Inverse and Ill-posed Problems}, year={2014}, volume={24}, pages={309 - 321} }
Abstract Size-structured population models provide a popular means to mathematically describe phenomena such as bacterial aggregation, schooling fish, and planetesimal evolution. For parameter estimation, a generalized sensitivity function (GSF) provides a tool that quantifies the impact of data from specific regions of the experimental domain. This function helps to identify the most relevant data subdomains, which enhances the optimization of experimental design. To our knowledge, GSFs have…
4 Citations
An Inverse Problem for a Class of Conditional Probability Measure-Dependent Evolution Equations.
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The inverse problem of identifying a conditional probability measure in measure-dependent evolution equations arising in size-structured population modeling is investigated as a least squares problem for the probability measure estimation using the Prohorov metric framework and existence and consistency of the least squares estimates are proved.
Generalized sensitivity functions for multiple output systems
- Mathematics, Computer Science
- 2016
It is demonstrated that the generalized sensitivity matrix can be interpreted as the Jacobian of the estimated parameters with respect to the nominal parameter vector.
Evaluating the Effect of Distributed Generation on Power Supply Capacity in Active Distribution System Based on Sensitivity Analysis
- Engineering
- 2017
In active distribution system (ADS), the access of distributed generation (DG) can effectively improve the power supply capacity (PSC). In order to explore the effect of DG on the PSC, the influence…
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