Identification of the parameters of the Beeler-Reuter ionic equation with a partially perturbed particle swarm optimization.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 22955867.
- Also identified by DOI 10.1109/TBME.2012.2216265.
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Abstract
A partially perturbed particle swarm optimization (PPSO) has been proposed for identifying the parameters of the Beeler-Reuter (BR) equation from action potential data. In the PPSO algorithm, the 63 BR equation parameters are divided into groups, and parameter patterns are made from the combination of the groups. PPSO enhances the capability of conventional particle swarm optimization (CPSO) by partially perturbing the coordinates of the globally best particle with the patterns when the searching process is locally confined. "Experimental data" were produced for cardiac myocytes simulated by the BR equation and the equation of Luo and Rudy (1991), and were used to test the algorithm of PPSO. The test results show that PPSO was able to identify the parameters of the BR equation effectively for different cardiac myocytes, while still retaining the conceptual simplicity and easy implementation of CPSO.
Medical subject headings
- Action Potentials
- Algorithms
- Models, Biological