LEADER 04110nam 22006255 450 001 9910484748503321 005 20200630045820.0 010 $a981-13-6569-5 024 7 $a10.1007/978-981-13-6569-0 035 $a(CKB)5340000000061465 035 $a(MiAaPQ)EBC5923776 035 $a(DE-He213)978-981-13-6569-0 035 $a(PPN)243769156 035 $a(EXLCZ)995340000000061465 100 $a20190329d2019 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aSocio-cultural Inspired Metaheuristics /$fedited by Anand J. Kulkarni, Pramod Kumar Singh, Suresh Chandra Satapathy, Ali Husseinzadeh Kashan, Kang Tai 205 $a1st ed. 2019. 210 1$aSingapore :$cSpringer Singapore :$cImprint: Springer,$d2019. 215 $a1 online resource (308 pages) $cillustrations 225 1 $aStudies in Computational Intelligence,$x1860-949X ;$v828 311 $a981-13-6568-7 320 $aIncludes bibliographical references and index. 327 $aOptimum 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. 330 $aThis book presents the latest insights and developments in the field of socio-cultural inspired algorithms. Akin to evolutionary and swarm-based optimization algorithms, socio-cultural algorithms belong to the category of metaheuristics (problem-independent computational methods) and are inspired by natural and social tendencies observed in humans by which they learn from one another through social interactions. This book is an interesting read for engineers, scientists, and students studying/working in the optimization, evolutionary computation, artificial intelligence (AI) and computational intelligence fields. 410 0$aStudies in Computational Intelligence,$x1860-949X ;$v828 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aMathematical optimization 606 $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aContinuous Optimization$3https://scigraph.springernature.com/ontologies/product-market-codes/M26030 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 0$aMathematical optimization. 615 14$aComputational Intelligence. 615 24$aArtificial Intelligence. 615 24$aContinuous Optimization. 676 $a006.3 702 $aKulkarni$b Anand J$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSingh$b Pramod Kumar$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSatapathy$b Suresh Chandra$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aHusseinzadeh Kashan$b Ali$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aTai$b Kang$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484748503321 996 $aSocio-cultural Inspired Metaheuristics$92846314 997 $aUNINA