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: Parallel Architectures and Bioinspired Algorithms
  name:
    name part: Fernández de Vega, Francisco.
    role:
      role term: editor.
  name:
    name part: Hidalgo Pérez, José Ignacio.
    role:
      role term: editor.
  name:
    name part: Lanchares, Juan.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2012
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: VI, 290 p. online resource.
  abstract: This monograph presents examples of best practices when combining bioinspired algorithms with parallel architectures. The book includes recent work by leading researchers in the field and offers a map with the main paths already explored and new ways towards the future. Parallel Architectures and Bioinspired Algorithms will be of value to both specialists in Bioinspired Algorithms, Parallel and Distributed Computing, as well as computer science students trying to understand the present and the future of Parallel Architectures and Bioinspired Algorithms.
  table of contents: Creating and Debugging Performance CUDA C -- Optimizing Shape Design with Distributed Parallel Genetic Programming on GPUs -- Characterizing Fault-tolerance in Genetic Algorithms and programming -- Comparison of Frameworks for Parallel Multiobjective Evolutionary Optimization in Dynamic Problems -- An Empirical Study of Parallel and Distributed Particle Swarm Optimization -- The generalized Island Model -- Genetic Programming for the Evolution of Associative Memories -- Parallel Architectures for Improving the Performance of a GA based trading System -- A Knowledge-Based Operator for a Genetic Algorithm which Optimizes the Distribution of Sparse Matrix Data -- Evolutive approaches for Variable Selection using a Non-parametric Noise Estimator -- A chemical evolutionary mechanism for instantiating service-based applications.
  note: edited by Francisco Fernández de Vega, José Ignacio Hidalgo Pérez, Juan Lanchares.
  subject:
    topic: Engineering
  subject:
    topic: Artificial intelligence
  subject:
    topic: Computational intelligence
  subject:
    topic: Engineering
  subject:
    topic: Computational Intelligence
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  classification: Q342
  classification: 006.3
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Studies in Computational Intelligence, 415
  identifier: 9783642287893
  identifier: http://dx.doi.org/10.1007/978-3-642-28789-3
  record info:
    record creation date: 120426
    record change date: 20151125212311.0
    record identifier: 978-3-642-28789-3