2012
DOI: 10.21014/acta_imeko.v1i1.16
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Gene expression programming and genetic algorithms in impedance circuit identification

Abstract: Impedance circuit identification through spectroscopy is often used to characterize sensors. When the circuit topology is known, it has been shown that the component values can be obtained by genetic algorithms. Also, gene expression programming can be used to search for an adequate circuit topology. In this paper, an improved version of the impedance circuit identification based on gene expression programming and hybrid genetic algorithm is presented to both identify the circuit and estimate its parameters. S… Show more

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Cited by 8 publications
(2 citation statements)
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“…The selection of a suitable electrical model can be made empirically by iterating through the available set of models determined by the system function (1). To implement this process, experimental data can be approximated using an acceptable set of equivalent circuits and utilising available fitting programs, such as LEVM [6] or method described in [13].…”
Section: Interpretation Using Electrical Modelsmentioning
confidence: 99%
“…The selection of a suitable electrical model can be made empirically by iterating through the available set of models determined by the system function (1). To implement this process, experimental data can be approximated using an acceptable set of equivalent circuits and utilising available fitting programs, such as LEVM [6] or method described in [13].…”
Section: Interpretation Using Electrical Modelsmentioning
confidence: 99%
“…Impedance circuit identification through spectroscopy is the subject of [2] where the authors use gene expression programming and genetic algorithms for automatic impedance circuit identification. Multiple experimental and simulation results are presented.…”
Section: The Articlesmentioning
confidence: 99%