LEADER 03784nam 22005655 450 001 9910483689303321 005 20251113181701.0 010 $a3-030-66007-9 024 7 $a10.1007/978-3-030-66007-9 035 $a(CKB)4100000011747022 035 $a(MiAaPQ)EBC6469877 035 $a(PPN)253859026 035 $a(DE-He213)978-3-030-66007-9 035 $a(EXLCZ)994100000011747022 100 $a20210204d2021 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aRecent Metaheuristic Computation Schemes in Engineering /$fby Erik Cuevas, Alma Rodríguez, Avelina Alejo-Reyes, Carolina Del-Valle-Soto 205 $a1st ed. 2021. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2021. 215 $a1 online resource (xi, 277 pages) 225 1 $aStudies in Computational Intelligence,$x1860-9503 ;$v948 311 1 $a3-030-66006-0 327 $aIntroductory Concepts of Metaheuristic Computation -- A Metaheuristic Scheme Based on the Hunting Model of Yellow Saddle Goatfish -- Metaheuristic Algorithm Based on Hybridization of Invasive Weed Optimization and Estimation Distribution Methods -- Corner Detection Algorithm Based on Cellular Neural Networks (CNN) and Differential Evolution (DE) -- Blood Vessel Segmentation Using Differential Evolution Algorithm -- Clustering Model Based on the Human Visual System -- Metaheuristic Algorithms for Wireless Sensor Networks -- Metaheuristic Algorithms Applied to the Inventory Problem. 330 $aThis book includes two objectives. The first goal is to present advances and developments which have proved to be effective in their application to several complex problems. The second objective is to present the performance comparison of various metaheuristic techniques when they face complex optimization problems. The material has been compiled from a teaching perspective. Most of the problems in science, engineering, economics, and other areas can be translated as an optimization or a search problem. According to their characteristics, some problems can be simple that can be solved by traditional optimization methods based on mathematical analysis. However, most of the problems of practical importance in engineering represent complex scenarios so that they are very hard to be solved by using traditional approaches. Under such circumstances, metaheuristic has emerged as the best alternative to solve this kind of complex formulations. This book is primarily intended for undergraduate and postgraduate students. Engineers and application developers can also benefit from the book contents since it has been structured so that each chapter can be read independently from the others, and therefore, only potential interesting information can be quickly available for solving an industrial problem at hand. . 410 0$aStudies in Computational Intelligence,$x1860-9503 ;$v948 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aCooperating objects (Computer systems) 606 $aComputational Intelligence 606 $aArtificial Intelligence 606 $aCyber-Physical Systems 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 0$aCooperating objects (Computer systems) 615 14$aComputational Intelligence. 615 24$aArtificial Intelligence. 615 24$aCyber-Physical Systems. 676 $a519.6 700 $aCuevas$b Erik$0761169 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483689303321 996 $aRecent metaheuristic computation schemes in engineering$92918867 997 $aUNINA