Optimizing Thermostable Enzymes Production Using Multigene Symbolic Regression Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3963

@Article{Sheta2013a,
  author =       "Alaa Sheta and Rania Hiary and Hossam Faris and 
                 Nazeeh Ghatasheh",
  title =        "Optimizing Thermostable Enzymes Production Using
                 Multigene Symbolic Regression Genetic Programming",
  journal =      "World Applied Sciences Journal",
  year =         "2013",
  volume =       "22",
  number =       "4",
  pages =        "485--493",
  keywords =     "genetic algorithms, genetic programming, Multigene
                 Genetic Programming, Symbolic regression, Optimisation,
                 Thermostable Enzymes",
  ISSN =         "1818-4952",
  publisher =    "IDOSI",
  URL =          "http://www.idosi.org/wasj/wasj22(4)13/6.pdf",
  URL =          "http://www.idosi.org/wasj/wasj22(4)2013.htm",
  bad_doi =      "doi:10.5829/idosi.wasj.2013.22.04.7694",
  size =         "9 pages",
  abstract =     "Thermostable enzymes production depends on number of
                 attributes such as temperature, pH, inoculum, time and
                 agitation. Optimising the relationship between these
                 attributes has been a challenge in biochemical research
                 field. Machine learning techniques such as Artificial
                 Neural Networks (ANN), Fuzzy Logic (FL) and Genetic
                 Algorithms (GAs) were used to solve the lipase activity
                 modelling problem. In this paper, we explore the use of
                 Multigene Symbolic Regression Genetic Programming to
                 solve the production problem of a solvent, detergent,
                 and thermo-tolerant lipase using the Newly Isolated
                 Acinetobacter sp. in submerged and solid-state
                 fermentation. Five attributes will be used to develop a
                 mathematical model for the lipase activities. They are
                 temperature, pH, inoculum, time and agitation. Genetic
                 Programming shows promising results compared to
                 reported results in the literature.",
  notes =        "GPTIPS Matlab
                 toolbox

                 http://www.idosi.org/wasj/wasj.htm",
}

Genetic Programming entries for Alaa Sheta Rania Hiary Hossam Faris Nazeeh A L Ghatasheh

Citations