An evolutionary approach for modeling the equivalent circuit for electrochemical impedance spectroscopy

Created by W.Langdon from gp-bibliography.bib Revision:1.4215

  author =       "Hongqing Cao and Jingxian Yu and Lishan Kang",
  title =        "An evolutionary approach for modeling the equivalent
                 circuit for electrochemical impedance spectroscopy",
  booktitle =    "Proceedings of the 2003 Congress on Evolutionary
                 Computation CEC2003",
  editor =       "Ruhul Sarker and Robert Reynolds and 
                 Hussein Abbass and Kay Chen Tan and Bob McKay and Daryl Essam and 
                 Tom Gedeon",
  pages =        "1819--1825",
  year =         "2003",
  publisher =    "IEEE Press",
  address =      "Canberra",
  publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ
                 08855-1331, USA",
  month =        "8-12 " # dec,
  organisation = "IEEE Neural Network Council (NNC), Engineers Australia
                 (IEAust), Evolutionary Programming Society (EPS),
                 Institution of Electrical Engineers (IEE)",
  ISBN =         "0-7803-7804-0",
  notes =        "CEC 2003 - A joint meeting of the IEEE, the IEAust,
                 the EPS, and the IEE.",
  keywords =     "genetic algorithms, genetic programming, Gene
                 Expression Programming, GEP, HEMA, Chemistry,
                 Electrochemical impedance spectroscopy, Equivalent
                 circuits, Gene expression, Laboratories, Linear
                 programming, Programming profession, Software
                 engineering, electrochemical impedance spectroscopy,
                 equivalent circuits, component parameters,
                 electrochemical impedance spectroscopy, equivalent
                 circuit, hybrid evolutionary modelling, parameter
  URL =          "",
  DOI =          "doi:10.1109/CEC.2003.1299893",
  abstract =     "This paper proposes an evolutionary approach to build
                 the equivalent circuit model for electrochemical
                 impedance spectroscopy. It works by using a hybrid
                 evolutionary modelling algorithm (HEMA) whose main idea
                 is to embed a genetic algorithm (GA) in gene expression
                 programming (GEP) where GEP is employed to discover and
                 optimise the structure of a circuit, while the GA is
                 employed to optimize the parameters of all the electric
                 components contained in the circuit. By running the
                 HEMA, the computer can automatically find suitable
                 circuit structures as well as optimise the component
                 parameters simultaneously. Compared with most available
                 methods, it has the advantages of automation of
                 modeling process, great diversity of model structures,
                 high stability and efficiency of parameter
  size =         "7 pages",

Genetic Programming entries for Hong-Qing Cao Jingxian Yu Li-Shan Kang