00908nam a22002653i 450099100368235970753620030916132606.0031111s1988 it |||||||||||||||||ita 8811932254b12460448-39ule_instARCHE-049373ExLDip.to LingueitaA.t.i. Arché s.c.r.l. Pandora Sicilia s.r.l.813.54Benchley, Peter438768Classificazione Q /Peter BenchleyMilano :Garzanti,1988442 p. ;22 cmTrad. di Maria Teresa MarencoQ clearance.b1246044802-04-1413-11-03991003682359707536LE012 818.54 BEN12012000161672le012-E0.00-l- 00000.i1289028513-11-03Classificazione Q179460UNISALENTOle01213-11-03ma -itait 0103686nam 22005895 450 991029993570332120251113210310.03-319-89309-210.1007/978-3-319-89309-9(CKB)4100000003359633(DE-He213)978-3-319-89309-9(MiAaPQ)EBC6298138(MiAaPQ)EBC5578269(Au-PeEL)EBL5578269(OCoLC)1066198628(PPN)226696804(EXLCZ)99410000000335963320180410d2018 u| 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierAdvances in Metaheuristics Algorithms: Methods and Applications /by Erik Cuevas, Daniel Zaldívar, Marco Pérez-Cisneros1st ed. 2018.Cham :Springer International Publishing :Imprint: Springer,2018.1 online resource (XIV, 218 p. 48 illus., 13 illus. in color.) Studies in Computational Intelligence,1860-9503 ;775Includes index.3-319-89308-4 Introduction -- The metaheuristic algorithm of the social-spider -- Calibration of Fractional Fuzzy Controllers by using the Social-spider method -- The metaheuristic algorithm of the Locust-search -- Identification of fractional chaotic systems by using the Locust Search Algorithm -- The States of Matter Search (SMS) -- Multimodal States of Matter search -- Metaheuristic algorithms based on Fuzzy Logic.This book explores new alternative metaheuristic developments that have proved to be effective in their application to several complex problems. Though most of the new metaheuristic algorithms considered offer promising results, they are nevertheless still in their infancy. To grow and attain their full potential, new metaheuristic methods must be applied in a great variety of problems and contexts, so that they not only perform well in their reported sets of optimization problems, but also in new complex formulations. The only way to accomplish this is to disseminate these methods in various technical areas as optimization tools. In general, once a scientist, engineer or practitioner recognizes a problem as a particular instance of a more generic class, he/she can select one of several metaheuristic algorithms that guarantee an expected optimization performance. Unfortunately, the set of options are concentrated on algorithms whose popularity and high proliferation outstrip those of the new developments. This structure is important, because the authors recognize this methodology as the best way to help researchers, lecturers, engineers and practitioners solve their own optimization problems.Studies in Computational Intelligence,1860-9503 ;775Computational intelligenceArtificial intelligenceComputational IntelligenceArtificial IntelligenceComputational intelligence.Artificial intelligence.Computational Intelligence.Artificial Intelligence.519.6Cuevas Erikauthttp://id.loc.gov/vocabulary/relators/aut761169Zaldívar Danielauthttp://id.loc.gov/vocabulary/relators/autPérez-Cisneros Marcoauthttp://id.loc.gov/vocabulary/relators/autMiAaPQMiAaPQMiAaPQBOOK9910299935703321Advances in Metaheuristics Algorithms: Methods and Applications2504749UNINA