rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Gene Expression Programming
    sub title: Mathematical Modeling by an Artificial Intelligence
  name:
    name part: Ferreira, Cândida.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2006
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XX, 480 p. online resource.
  abstract: Cândida Ferreira thoroughly describes the basic ideas of gene expression programming (GEP) and numerous modifications to this powerful new algorithm. This monograph provides all the implementation details of GEP so that anyone with elementary programming skills will be able to implement it themselves. The book also includes a self-contained introduction to this new exciting field of computational intelligence, including several new algorithms for decision tree induction, data mining, classifier systems, function finding, polynomial induction, times series prediction, evolution of linking functions, automatically defined functions, parameter optimization, logic synthesis, combinatorial optimization, and complete neural network induction. The book also discusses some important and controversial evolutionary topics that might be refreshing to both evolutionary computer scientists and biologists. This second edition has been substantially revised and extended with five new chapters, including a new chapter describing two new algorithms for inducing decision trees with nominal and numeric/mixed attributes. Cândida Ferreira thoroughly describes the basic ideas of gene expression programming (GEP) and numerous modifications to this powerful new algorithm. This monograph provides all the implementation details of GEP so that anyone with elementary programming skills will be able to implement it themselves. The book also includes a self-contained introduction to this new exciting field of computational intelligence, including several new algorithms for decision tree induction, data mining, classifier systems, function finding, polynomial induction, times series prediction, evolution of linking functions, automatically defined functions, parameter optimization, logic synthesis, combinatorial optimization, and complete neural network induction. The book also discusses some important and controversial evolutionary topics that might be refreshing to both evolutionary computer sc…
  table of contents: Introduction: The Biological Perspective -- The Entities of Gene Expression Programming -- The Basic Gene Expression Algorithm -- The Basic GEA in Problem Solving -- Numerical Constants and the GEP-RNC Algorithm -- Automatically Defined Functions in Problem Solving -- Polynomial Induction and Time Series Prediction -- Parameter Optimization -- Decision Tree Induction -- Design of Neural Networks -- Combinatorial Optimization -- Evolutionary Studies.
  note: by Cândida Ferreira.
  subject:
    topic: Computer science
  subject:
    topic: Computers
  subject:
    topic: Artificial intelligence
  subject:
    topic: Bioinformatics
  subject:
    topic: Applied mathematics
  subject:
    topic: Engineering mathematics
  subject:
    topic: Computer Science
  subject:
    topic: Theory of Computation
  subject:
    topic: Appl.Mathematics/Computational Methods of Engineering
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: Bioinformatics
  classification: QA75.5-76.95
  classification: 004.0151
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Studies in Computational Intelligence, 21
  identifier: 9783540328490
  identifier: http://dx.doi.org/10.1007/3-540-32849-1
  record info:
    record creation date: 100301
    record change date: 20151204142431.0
    record identifier: 978-3-540-32849-0