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: Socio-cultural Inspired Metaheuristics
  name:
    name part: Kulkarni, Anand J.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Singh, Pramod Kumar.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Satapathy, Suresh Chandra.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Husseinzadeh Kashan, Ali.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Tai, Kang.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: si
    date issued: 2019
    edition: 1st ed. 2019.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: X, 303 p. 155 illus., 69 illus. in color. online resource.
  abstract: This book presents the latest insights and developments in the field of socio-cultural inspired algorithms. Akin to evolutionary and swarm-based optimization algorithms, socio-cultural algorithms belong to the category of metaheuristics (problem-independent computational methods) and are inspired by natural and social tendencies observed in humans by which they learn from one another through social interactions. This book is an interesting read for engineers, scientists, and students studying/working in the optimization, evolutionary computation, artificial intelligence (AI) and computational intelligence fields.
  table of contents: Optimum Design of Four Mechanical Elements Using Cohort Intelligence Algorithm -- Premier League Championship Algorithm: a multi-population based Algorithm and its Application on Structural Design Optimization -- Socio-inspired Optimization Metaheuristics: A Review -- Social Group Optimization Algorithm for Pattern Optimization in Antenna Arrays -- A Self-organizing Multi-agent Cooperative Robotic System: An Application of Cohort Intelligence Algorithm -- Feature Selection for Vocal Segmentation Using Social Emotional Optimization Algorithm -- Simultaneous Size and Shape Optimization of Dome-shaped Structures Using Improved Cultural Algorithm -- A Socio-Based Cohort Intelligence Algorithm for Integer Discrete and Mixed Design Variables Engineering Problems -- Maximizing Profits in Crop Planning Using Socio Evolution and Learning Optimization -- Application of Cohort- intelligence Variations Designing Fractional PID Controller for Various Systems.
  note: edited by Anand J. Kulkarni, Pramod Kumar Singh, Suresh Chandra Satapathy, Ali Husseinzadeh Kashan, Kang Tai.
  subject:
    topic: Computational intelligence
  subject:
    topic: Artificial intelligence
  subject:
    topic: Mathematical optimization
  subject:
    topic: Computational Intelligence
  subject:
    topic: Artificial Intelligence
  subject:
    topic: Continuous Optimization
  classification: Q342
  classification: 006.3
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Studies in Computational Intelligence, 828
  identifier: 9789811365690
  identifier: https://doi.org/10.1007/978-981-13-6569-0
  record info:
    record creation date: 190329
    record change date: 20191021201749.0
    record identifier: 978-981-13-6569-0