Using an Improved Differential Evolution Algorithm for Parameter Estimation to Simulate Glycolysis Pathway

Chong, Chuii Khim; Mohamad, Mohd Saberi; Deris, Safaai; Shamsir, Mohd Shahir; Abdullah, Afnizanfaizal; Choon, Yee Wen; Chai, Lian En; Omatu, Sigeru

doi:10.1007/978-3-642-28765-7_85

Cited by 1 publication

(1 citation statement)

References 9 publications

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“…Developed by Storn and Price (1997), DE has shown good performance and quality compared with other EAs in parameter adjustment problems involving real-type variables analogous to the system considered in this work (Trejo-Zúñiga et al, 2013;Peng et al, 2009;Chong et al, 2012). In recent years, DE has been widely used to deal with a wide range of reference tests and real-world application problems (Cai et al, 2008;Neri and Tirronen, 2010;Das and Suganthan, 2011;Rocca et al, 2011;Liu and Qiao, 2015;Saber et al, 2017).…”

Section: Introductionmentioning

confidence: 91%

Fitting procedure based on Differential Evolution to evaluate impedance parameters of metal–coating systems

González

Greiner

Mena

et al. 2019

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Purpose Impedance data obtained by electrochemical impedance spectroscopy (EIS) are fitted to a relevant electrical equivalent circuit to evaluate parameters directly related to the resistance and the durability of metal–coating systems. The purpose of this study is to present a novel and more efficient computational strategy for the modelling of EIS measurements using the Differential Evolution paradigm. Design/methodology/approach An alternative method to non-linear regression algorithms for the analysis of measured data in terms of equivalent circuit parameters is provided by evolutionary algorithms, particularly the Differential Evolution (DE) algorithms (standard DE and a representative of the self-adaptive DE paradigm were used). Findings The results obtained with DE algorithms were compared with those yielding from commercial fitting software, achieving a more accurate solution, and a better parameter identification, in all the cases treated. Further, an enhanced fitting power for the modelling of metal–coating systems was obtained. Originality/value The great potential of the developed tool has been demonstrated in the analysis of the evolution of EIS spectra due to progressive degradation of metal–coating systems. Open codes of the different differential algorithms used are included, and also, examples tackled in the document are open. It allows the complete use, or improvement, of the developed tool by researchers.

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