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001432608 001__ 1432608
001432608 003__ OCoLC
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001432608 020__ $$a9783030621339$$q(electronic bk.)
001432608 020__ $$a3030621332$$q(electronic bk.)
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001432608 020__ $$z9783030621322
001432608 0247_ $$a10.1007/978-3-030-62133-9$$2doi
001432608 035__ $$aSP(OCoLC)1224019548
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001432608 049__ $$aISEA
001432608 050_4 $$aQA9.64$$b.C27 2021eb
001432608 08204 $$a511.3/13$$223
001432608 1001_ $$aCastillo, Oscar,$$d1959-
001432608 24510 $$aDifferential evolution algorithm with type-2 fuzzy logic for dynamic parameter adaptation with application to intelligent control /$$cOscar Castillo, Patricia Ochoa, Jose Soria.
001432608 264_1 $$aCham :$$bSpringer,$$c2021.
001432608 264_4 $$c©2021
001432608 300__ $$a1 online resource (vii, 61 pages)
001432608 336__ $$atext$$btxt$$2rdacontent
001432608 337__ $$acomputer$$bc$$2rdamedia
001432608 338__ $$aonline resource$$bcr$$2rdacarrier
001432608 347__ $$atext file
001432608 347__ $$bPDF
001432608 4901_ $$aSpringerBriefs in applied sciences and technology, Computational intelligence
001432608 504__ $$aIncludes bibliographical references and index.
001432608 50500 $$tIntroduction --$$tFuzzy Logic Systems --$$tDifferential Evolution Algorithm --$$tProposed Method --$$tCase studies --$$tConclusions.
001432608 506__ $$aAccess limited to authorized users.
001432608 520__ $$aThis book focuses on the fields of fuzzy logic, bio-inspired algorithm, especially the differential evolution algorithm and also considering the fuzzy control area. The main idea is that these two areas together can help solve various control problems and to find better results. In this book, the authors test the proposed method using five benchmark control problems. First, the water tank, temperature, mobile robot, and inverted pendulum controllers are considered. For these 4 problems, experimentation was carried out using a Type-1 fuzzy system and an Interval Type-2 system. The last control problem was the D.C. motor, for which the experiments were performed with Type-1, Interval Type-2, and Generalized Type-2 fuzzy systems. When we use fuzzy systems combined with the differential evolution algorithm, we can notice that the results obtained in each of the controllers are better and with increasing uncertainty, the results are even better. For this reason, the authors consider in this book the proposed method using fuzzy systems and the differential evolution algorithm to improve the fuzzy controllers behavior in complex control problems.
001432608 650_0 $$aFuzzy logic.
001432608 650_0 $$aEvolution equations.
001432608 650_6 $$aLogique floue.
001432608 650_6 $$aÉquations d'évolution.
001432608 655_0 $$aElectronic books.
001432608 7001_ $$aOchoa, Patricia.
001432608 7001_ $$aSoria, José$$q(José Luciano Soria Arteche)
001432608 77608 $$iPrint version:$$aCastillo, Oscar.$$tDifferential evolution algorithm with type-2 fuzzy logic for dynamic parameter adaptation with application to intelligent control.$$dCham : Springer, 2021$$z3030621324$$z9783030621322$$w(OCoLC)1197851373
001432608 830_0 $$aSpringerBriefs in applied sciences and technology.$$pComputational intelligence.
001432608 852__ $$bebk
001432608 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-62133-9$$zOnline Access$$91397441.1
001432608 909CO $$ooai:library.usi.edu:1432608$$pGLOBAL_SET
001432608 980__ $$aBIB
001432608 980__ $$aEBOOK
001432608 982__ $$aEbook
001432608 983__ $$aOnline
001432608 994__ $$a92$$bISE