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: Success in Evolutionary Computation
  name:
    name part: Yang, Ang.
    role:
      role term: editor.
  name:
    name part: Shan, Yin.
    role:
      role term: editor.
  name:
    name part: Bui, Lam Thu.
    role:
      role term: editor.
  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: VIII, 372 p. online resource.
  abstract: Darwinian evolutionary theory is one of the most important theories in human history for it has equipped us with a valuable tool to understand the amazing world around us. There can be little surprise, therefore, that Evolutionary Computation (EC), inspired by natural evolution, has been so successful in providing high quality solutions in a large number of domains. EC includes a number of techniques, such as Genetic Algorithms, Genetic Programming, Evolution Strategy and Evolutionary Programming, which have been used in a diverse range of highly successful applications. This book brings together some of these EC applications in fields including electronics, telecommunications, health, bioinformatics, supply chain and other engineering domains, to give the audience, including both EC researchers and practitioners, a glimpse of this exciting rapidly evolving field.
  table of contents: Theory -- Adaptation of a Success Story in GAs: Estimation-of-Distribution Algorithms for Tree-based Optimization Problems -- The Automated Design of Artificial Neural Networks Using Evolutionary Computation -- A Versatile Surrogate-Assisted Memetic Algorithm for Optimization of Computationally Expensive Functions and its Engineering Applications -- Data Mining and Intelligent Multi-Agent Technologies in Medical Informatics -- Applications -- Evolving Trading Rules -- A Hybrid Genetic Algorithm for the Protein Folding Problem Using the 2D-HP Lattice Model -- Optimal Management of Agricultural Systems -- Evolutionary Electronics: Automatic Synthesis of Analog Circuits by GAs -- Intuitive Visualization and Interactive Analysis of Pareto Sets Applied on Production Engineering System -- Privacy Protection with Genetic Algorithms -- A Revision of Evolutionary Computation Techniques in Telecommunications and An Application for The Network Global Planning Problem -- Survivable Network Design with an Evolution Strategy -- Evolutionary Computations for Design Optimization and Test Automation in VLSI Circuits -- Evolving Cooperative Agents in Economy Market Using Genetic Algorithms -- Optimizing Multiplicative General Parameter Finite Impulse Response Filters Using Evolutionary Computation -- Applying Genetic Algorithms to Optimize the Cost of Multiple Sourcing Supply Chain Systems – An Industry Case Study.
  note: edited by Ang Yang, Yin Shan, Lam Thu Bui.
  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
  related item:
    title info:
      title: Studies in Computational Intelligence, 92
  identifier: 9783540762867
  identifier: http://dx.doi.org/10.1007/978-3-540-76286-7
  record info:
    record creation date: 100301
    record change date: 20151204163603.0
    record identifier: 978-3-540-76286-7