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008			210204s2021 gw | s |||| 0|eng d
020			_a9783030660079
024	7		_a10.1007/978-3-030-66007-9 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _erda _dES-MaUEC
050		4	_aT57.84 _b2021 EB
100	1		_aCuevas, Erik _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _944351
245	1	0	_aRecent Metaheuristic Computation Schemes in Engineering _cby Erik Cuevas, Alma Rodríguez, Avelina Alejo-Reyes, Carolina Del-Valle-Soto.
250			_aFirst edition 2021
264		1	_aCham _bSpringer International Pulishing _c2021
300			_a1 recurso en línea (XI, 277 páginas) _b79 ilustraciones, 36 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF _2
490	0		_aStudies in Computational Intelligence _x1860-949X _v948
490	0		_aIntelligent Technologies and Robotics (SpringerNature-42732)
490	0		_aIntelligent Technologies and Robotics (R0) (SpringerNature-43728)
505	0		_aIntroductory Concepts of Metaheuristic Computation -- A Metaheuristic Scheme Based on the Hunting Model of Yellow Saddle Goatfish -- Metaheuristic Algorithm Based on Hybridization of Invasive Weed Optimization and Estimation Distribution Methods -- Corner Detection Algorithm Based on Cellular Neural Networks (CNN) and Differential Evolution (DE) -- Blood Vessel Segmentation Using Differential Evolution Algorithm -- Clustering Model Based on the Human Visual System -- Metaheuristic Algorithms for Wireless Sensor Networks -- Metaheuristic Algorithms Applied to the Inventory Problem.
520	3		_aThis book includes two objectives. The first goal is to present advances and developments which have proved to be effective in their application to several complex problems. The second objective is to present the performance comparison of various metaheuristic techniques when they face complex optimization problems. The material has been compiled from a teaching perspective. Most of the problems in science, engineering, economics, and other areas can be translated as an optimization or a search problem. According to their characteristics, some problems can be simple that can be solved by traditional optimization methods based on mathematical analysis. However, most of the problems of practical importance in engineering represent complex scenarios so that they are very hard to be solved by using traditional approaches. Under such circumstances, metaheuristic has emerged as the best alternative to solve this kind of complex formulations. This book is primarily intended for undergraduate and postgraduate students. Engineers and application developers can also benefit from the book contents since it has been structured so that each chapter can be read independently from the others, and therefore, only potential interesting information can be quickly available for solving an industrial problem at hand.
988			_aSpringer_Robotics_2021
650		7	_aProgramación metaheurística _2embne _9467159
650		7	_aOptimización matemática _2embne _9145705
650		7	_aInteligencia artificial _2embne _9413115
700	1		_aRodriguez, Maria Alma _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _994560
700	1		_aAlejo-Reyes, Avelina _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9677850
700	1		_aDel-Valle-Soto, Carolina _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9677851
776	0	8	_iPrinted edition: _z9783030660062
776	0	8	_iPrinted edition: _z9783030660086
776	0	8	_iPrinted edition: _z9783030660093
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-66007-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE _n0
998			_b03/2021 _dz _eo _zSI