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: Introduction to Genetic Algorithms
  name:
    name part: Sivanandam, S.N.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Deepa, S.N.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2008
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XIX, 442 p. online resource.
  abstract: Genetic Algorithms are adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. The basic concept of Genetic Algorithms is designed to simulate processes in natural system necessary for evolution, specifically those that follow the principles first laid down by Charles Darwin of survival of the fittest. This book is designed to provide an in-depth knowledge on the basic operational features and characteristics of Genetic Algorithms. The various operators and techniques given in the book are pertinent to carry out Genetic Algorithm Research Projects. The book also explores the different types are Genetic Algorithms available with their importance. Implementation of Genetic Algorithm concept has been performed using the universal language C/C++ and the discussion also extends to Genetic Algorithm MATLAB Toolbox. Few Genetic Algorithm problems are programmed using MATLAB and the simulated results are given for the ready reference of the reader. The applications of Genetic Algorithms in Machine learning, Mechanical Engineering, Electrical Engineering, Civil Engineering, Data Mining, Image Processing, and VLSI are dealt to make the readers understand where the concept can be applied.
  table of contents: Evolutionary Computation -- Genetic Algorithms -- Terminologies and Operators of GA -- Advanced Operators and Techniques in Genetic Algorithm -- Classification of Genetic Algorithm -- Genetic Programming -- Genetic Algorithm Optimization Problems -- Genetic Algorithm Implementation Using Matlab -- Genetic Algorithm Optimization in C/C++ -- Applications of Genetic Algorithms -- to Particle Swarm Optimization and Ant Colony Optimization.
  note: by S.N. Sivanandam, S.N. Deepa.
  subject:
    topic: Engineering
  subject:
    topic: Artificial intelligence
  subject:
    topic: Applied mathematics
  subject:
    topic: Engineering mathematics
  subject:
    topic: Engineering
  subject:
    topic: Appl.Mathematics/Computational Methods of Engineering
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  classification: TA329-348
  classification: TA640-643
  classification: 519
  related item:
    title info:
      title: Springer eBooks
  identifier: 9783540731900
  identifier: http://dx.doi.org/10.1007/978-3-540-73190-0
  record info:
    record creation date: 100301
    record change date: 20151204164828.0
    record identifier: 978-3-540-73190-0