000 03773nam a2200445 i 4500
710 2 _aSpringerLink (Online service)
_9106996
999 _c119404
_d119404
001 119404
003 ES-MaUEC
005 20230102113947.0
006 a||||fo|||| 00| 0
007 cr nn nnnaamaa
008 200327s2020 gw a s |||| 0|eng d
020 _a9783030439507
024 7 _a10.1007/978-3-030-43950-7
_2doi
040 _aES-MaUEC
_bspa
_cES-MaUEC
_dES-MaUEC
050 4 _aQA9.64
_b2020 EB
100 _aValdez, Fevrier.
_eautor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_999482
245 1 0 _aGeneral Type-2 Fuzzy Logic in Dynamic Parameter Adaptation for the Harmony Search Algorithm
_cby Fevrier Valdez, Cinthia Peraza, Oscar Castillo.
250 _aFirst edition 2020.
264 1 _aCham
_bSpringer International Publishing
_c2020
300 _a1 recurso en línea (VII, 83 páginas)
_b47 ilustraciones, 32 ilustraciones a color
336 _2rdacontent
_aTexto
_btxt
337 _2rdamedia
_aelectrónico
_bc
338 _2rdacarrier
_arecurso electrónico
_bcr
347 _aArchivo de texto
_bPDF
490 0 _aSpringerBriefs in Computational Intelligence
_x2625-3704
490 0 _aIntelligent Technologies and Robotics (Springer-42732)
505 0 _aIntroduction to Fuzzy Harmony Search -- Theory of the Original Harmony Search Method -- Proposed Fuzzy Harmony Search Method -- Study Cases -- Conclusion.
520 3 _aThis book focuses on the fields of fuzzy logic and metaheuristic algorithms, particularly the harmony search algorithm and fuzzy control. There are currently several types of metaheuristics used to solve a range of real-world of problems, and these metaheuristics contain parameters that are usually fixed throughout the iterations. However, a number of techniques are also available that dynamically adjust the parameters of an algorithm, such as probabilistic fuzzy logic. This book proposes a method of addressing the problem of parameter adaptation in the original harmony search algorithm using type-1, interval type-2 and generalized type-2 fuzzy logic. The authors applied this methodology to the resolution of problems of classical benchmark mathematical functions, CEC 2015, CEC2017 functions and to the optimization of various fuzzy logic control cases, and tested the method using six benchmark control problems - four of the Mamdani type: the problem of filling a water tank, the problem of controlling the temperature of a shower, the problem of controlling the trajectory of an autonomous mobile robot and the problem of controlling the speed of an engine; and two of the Sugeno type: the problem of controlling the balance of a bar and ball, and the problem of controlling control the balance of an inverted pendulum. When the interval type-2 fuzzy logic system is used to model the behavior of the systems, the results show better stabilization because the uncertainty analysis is better. As such, the authors conclude that the proposed method, based on fuzzy systems, fuzzy controllers and the harmony search optimization algorithm, improves the behavior of complex control plants.
988 _aSpringer_Robotics_31032020
650 7 _2embne
_aLógica difusa
_9152594
650 7 _2embne
_aAlgoritmos
_9141162
700 1 _aPeraza, Cinthia
_eautor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_9673636
700 1 _aCastillo, Oscar
_eautor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_9673637
776 0 8 _iPrinted edition:
_z9783030439491
776 0 8 _iPrinted edition:
_z9783030439514
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-43950-7
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
998 _b05/2020
_dz
_ek
_zSI