LEADER 04049nam  22006135  450 
001 9910483939503321
005 20251113201501.0
010   $a3-030-43950-X
024 7 $a10.1007/978-3-030-43950-7
035   $a(CKB)4100000010765518
035   $a(MiAaPQ)EBC6147526
035   $a(DE-He213)978-3-030-43950-7
035   $z(PPN)258861916
035   $a(PPN)243226519
035   $a(EXLCZ)994100000010765518
100   $a20200327d2020      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aGeneral Type-2 Fuzzy Logic in Dynamic Parameter Adaptation for the Harmony Search Algorithm /$fby Fevrier Valdez, Cinthia Peraza, Oscar Castillo
205   $a1st ed. 2020.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020.
215   $a1 online resource (86 pages)
225 1 $aSpringerBriefs in Computational Intelligence,$x2625-3712
311 08$a3-030-43949-6 
320   $aIncludes bibliographical references and index.
327   $aIntroduction to Fuzzy Harmony Search -- Theory of the Original Harmony Search Method -- Proposed Fuzzy Harmony Search Method -- Study Cases -- Conclusion.
330   $aThis book focuses on the fields of fuzzy logic and metaheuristic algorithms, particularly the harmony search algorithm and fuzzy control. There are currently several types of metaheuristics used to solve a range of real-world of problems, and these metaheuristics contain parameters that are usually fixed throughout the iterations. However, a number of techniques are also available that dynamically adjust the parameters of an algorithm, such as probabilistic fuzzy logic. This book proposes a method of addressing the problem of parameter adaptation in the original harmony search algorithm using type-1, interval type-2 and generalized type-2 fuzzy logic. The authors applied this methodology to the resolution of problems of classical benchmark mathematical functions, CEC 2015, CEC2017 functions and to the optimization of various fuzzy logic control cases, and tested the method using six benchmark control problems ? four of the Mamdani type: the problem of filling a water tank, theproblem of controlling the temperature of a shower, the problem of controlling the trajectory of an autonomous mobile robot and the problem of controlling the speed of an engine; and two of the Sugeno type: the problem of controlling the balance of a bar and ball, and the problem of controlling control the balance of an inverted pendulum. When the interval type-2 fuzzy logic system is used to model the behavior of the systems, the results show better stabilization because the uncertainty analysis is better. As such, the authors conclude that the proposed method, based on fuzzy systems, fuzzy controllers and the harmony search optimization algorithm, improves the behavior of complex control plants.
410  0$aSpringerBriefs in Computational Intelligence,$x2625-3712
606   $aComputational intelligence
606   $aArtificial intelligence
606   $aControl engineering
606   $aComputational Intelligence
606   $aArtificial Intelligence
606   $aControl and Systems Theory
615  0$aComputational intelligence.
615  0$aArtificial intelligence.
615  0$aControl engineering.
615 14$aComputational Intelligence.
615 24$aArtificial Intelligence.
615 24$aControl and Systems Theory.
676   $a511.313
700   $aValdez$b Fevrier$4aut$4http://id.loc.gov/vocabulary/relators/aut$0763074
702   $aPeraza$b Cinthia$4aut$4http://id.loc.gov/vocabulary/relators/aut
702   $aCastillo$b Oscar$4aut$4http://id.loc.gov/vocabulary/relators/aut
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910483939503321
996   $aGeneral Type-2 Fuzzy Logic in Dynamic Parameter Adaptation for the Harmony Search Algorithm$92846074
997   $aUNINA