LEADER 03743nam 22005895 450 001 9910629280803321 005 20250630101818.0 010 $a9783031201059 010 $a3031201051 024 7 $a10.1007/978-3-031-20105-9 035 $a(MiAaPQ)EBC7130117 035 $a(Au-PeEL)EBL7130117 035 $a(CKB)25264906300041 035 $a(PPN)266349161 035 $a(DE-He213)978-3-031-20105-9 035 $a(EXLCZ)9925264906300041 100 $a20221102d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAnalysis and Comparison of Metaheuristics /$fby Erik Cuevas, Omar Avalos, Jorge Gálvez 205 $a1st ed. 2023. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2023. 215 $a1 online resource (230 pages) 225 1 $aStudies in Computational Intelligence,$x1860-9503 ;$v1063 311 08$a9783031201042 311 08$a3031201043 320 $aIncludes bibliographical references. 327 $aFundamentals of Metaheuristic Computation -- A Comparative Approach for Two-Dimensional Digital IIR Filter Design Applying Different Evolutionary Computational Techniques -- Comparison of Metaheuristics for Chaotic Systems Estimation -- Comparison Study of Novel Evolutionary Algorithms for Elliptical Shapes in Images -- IIR System Identification using Several Optimization Techniques: A Review Analysis -- Fractional-order Estimation using Locust Search Algorithm -- Comparison of Optimization Techniques for Solar Cells Parameter Identification -- Comparison of Metaheuristics Techniques and Agent-Based Approaches. 330 $aThis book presents a comparative perspective of current metaheuristic developments, which have proved to be effective in their application to several complex problems. The study of biological and social entities such as animals, humans, or insects that manifest a cooperative behavior has produced several computational models in metaheuristic methods. Although these schemes emulate very different processes or systems, the rules used to model individual behavior are very similar. Under such conditions, it is not clear to identify which are the advantages or disadvantages of each metaheuristic technique. The book is compiled from a teaching perspective. For this reason, the book is primarily intended for undergraduate and postgraduate students of Science, Electrical Engineering, or Computational Mathematics. It is appropriate for courses such as Artificial Intelligence, Electrical Engineering, Evolutionary Computation. The book is also useful for researchers from the evolutionary and engineering communities. Likewise, engineer practitioners, who are not familiar with metaheuristic computation concepts, will appreciate that the techniques discussed are beyond simple theoretical tools since they have been adapted to solve significant problems that commonly arise in engineering areas. 410 0$aStudies in Computational Intelligence,$x1860-9503 ;$v1063 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aComputational Intelligence 606 $aArtificial Intelligence 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 14$aComputational Intelligence. 615 24$aArtificial Intelligence. 676 $a005.1 700 $aCuevas$b Erik$0761169 702 $aGa?lvez$b Jorge 702 $aAvalos$b Omar 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910629280803321 996 $aAnalysis and Comparison of Metaheuristics$92967782 997 $aUNINA