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dc.contributor.editorMilani, Alfredo
dc.contributor.editorCarpi, Arturo
dc.contributor.editorPoggioni, Valentina
dc.date.accessioned2021-05-01T15:48:33Z
dc.date.available2021-05-01T15:48:33Z
dc.date.issued2020
dc.identifierONIX_20210501_9783039436118_1137
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/69391
dc.description.abstractEvolutionary algorithms and metaheuristics are widely used to provide efficient and effective approximate solutions to computationally hard optimization problems. With the widespread use of intelligent systems in recent years, evolutionary algorithms have been applied, beyond classical optimization problems, to AI system parameter optimization and the design of artificial neural networks and feature selection in machine learning systems. This volume will present recent results of applications of the most successful metaheuristics, from differential evolution and particle swarm optimization to artificial neural networks, loT allocation, and multi-objective optimization problems. It will also provide a broad view of the role and the potential of evolutionary algorithms as service components in Al systems.
dc.languageEnglish
dc.subject.classificationthema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industriesen_US
dc.subject.othermulti-objective optimization problems
dc.subject.otherparticle swarm optimization (PSO)
dc.subject.otherGaussian mutation
dc.subject.otherimproved learning strategy
dc.subject.otherbig data
dc.subject.otherinterval concept lattice
dc.subject.otherhorizontal union
dc.subject.othersequence traversal
dc.subject.otherevolutionary algorithms
dc.subject.othermulti-objective optimization
dc.subject.otherparameter puning
dc.subject.otherparameter analysis
dc.subject.otherparticle swarm optimization
dc.subject.otherdifferential evolution
dc.subject.otherglobal continuous optimization
dc.subject.otherwireless sensor networks
dc.subject.othertask allocation
dc.subject.otherstochastic optimization
dc.subject.othersocial network optimization
dc.subject.othermemetic particle swarm optimization
dc.subject.otheradaptive local search operator
dc.subject.otherco-evolution
dc.subject.otherPSO
dc.subject.otherformal methods in evolutionary algorithms
dc.subject.otherself-adaptive differential evolutionary algorithms
dc.subject.otherconstrained optimization
dc.subject.otherensemble of constraint handling techniques
dc.subject.otherhybrid algorithms
dc.subject.otherassociation rules
dc.subject.othermining algorithm
dc.subject.othervertical union
dc.subject.otherneuroevolution
dc.subject.otherneural networks
dc.subject.othern/a
dc.titleEvolutionary Algorithms in Intelligent Systems
dc.typebook
oapen.identifier.doi10.3390/books978-3-03943-612-5
oapen.relation.isPublishedBy46cabcaa-dd94-4bfe-87b4-55023c1b36d0
oapen.relation.isbn9783039436118
oapen.relation.isbn9783039436125
oapen.pages144
oapen.place.publicationBasel, Switzerland


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