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000778837 019__ $$a970753052$$a971048098$$a971091161$$a974649734$$a981103427
000778837 020__ $$a9783319511092$$q(electronic book)
000778837 020__ $$a3319511092$$q(electronic book)
000778837 020__ $$z9783319511085
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000778837 0247_ $$a10.1007/978-3-319-51109-2$$2doi
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000778837 049__ $$aISEA
000778837 050_4 $$aTA347.E96
000778837 08204 $$a006.3/823$$223
000778837 1001_ $$aCuevas, Erik.
000778837 24510 $$aEvolutionary computation techniques :$$ba comparative perspective /$$cErik Cuevas, Valentín Osuna, Diego Oliva.
000778837 260__ $$aCham :$$bSpringer,$$c2017.
000778837 300__ $$a1 online resource.
000778837 336__ $$atext$$btxt$$2rdacontent
000778837 337__ $$acomputer$$bc$$2rdamedia
000778837 338__ $$aonline resource$$bcr$$2rdacarrier
000778837 347__ $$atext file$$bPDF$$2rda
000778837 4901_ $$aStudies in computational intelligence ;$$vvolume 686
000778837 504__ $$aIncludes bibliographical references.
000778837 5050_ $$aPreface -- Introduction -- Multilevel segmentation in digital images -- Multi-Circle detection on images -- Template matching -- Motion estimation -- Photovoltaic cell design -- Parameter identification of induction motors -- White blood cells Detection in images -- Estimation of view transformations in images -- Filter Design.
000778837 506__ $$aAccess limited to authorized users.
000778837 520__ $$aThis book compares the performance of various evolutionary computation (EC) techniques when they are faced with complex optimization problems extracted from different engineering domains. Particularly focusing on recently developed algorithms, it is designed so that each chapter can be read independently. Several comparisons among EC techniques have been reported in the literature, however, they all suffer from one limitation: their conclusions are based on the performance of popular evolutionary approaches over a set of synthetic functions with exact solutions and well-known behaviors, without considering the application context or including recent developments. In each chapter, a complex engineering optimization problem is posed, and then a particular EC technique is presented as the best choice, according to its search characteristics. Lastly, a set of experiments is conducted in order to compare its performance to other popular EC methods.
000778837 650_0 $$aEvolutionary computation.
000778837 7001_ $$aOsuna, Valentín.
000778837 7001_ $$aOliva, Diego.
000778837 77608 $$iPrint version:$$aCuevas, Erik.$$tEvolutionary computation techniques.$$dCham : Springer, 2017$$z9783319511085$$z3319511084$$w(OCoLC)963914243
000778837 830_0 $$aStudies in computational intelligence ;$$vv. 686.
000778837 852__ $$bebk
000778837 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-51109-2$$zOnline Access$$91397441.1
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