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001443978 001__ 1443978
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001443978 020__ $$a9789811680823$$q(electronic bk.)
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001443978 0247_ $$a10.1007/978-981-16-8082-3$$2doi
001443978 035__ $$aSP(OCoLC)1294216805
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001443978 049__ $$aISEA
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001443978 08204 $$a515/.35$$223
001443978 24500 $$aDifferential evolution :$$bfrom theory to practice /$$cB. Vinoth Kumar, Diego Oliva, P. N. Suganthan, editors.
001443978 260__ $$aSingapore :$$bSpringer,$$c2022.
001443978 300__ $$a1 online resource
001443978 336__ $$atext$$btxt$$2rdacontent
001443978 337__ $$acomputer$$bc$$2rdamedia
001443978 338__ $$aonline resource$$bcr$$2rdacarrier
001443978 347__ $$atext file$$bPDF$$2rda
001443978 4901_ $$aStudies in computational intelligence,$$x1860-9503 ;$$vvolume 1009
001443978 5050_ $$aAnalysis of Structural Bias in Differential Evolution Configurations -- Spherical Model of Population Dynamics in Differential Evolution -- Reinforcement Learning-based Differential Evolution for Global Optimization -- Analytical Study on the Role of Scale Factor Parameter of Differential Evolution Algorithm on its Convergence Nature -- The Trap of Sisyphus Work in Differential Evolution and How to Avoid It -- Investigations on Distributed Differential Evolution Framework with Fault Tolerance Mechanisms -- Differential Evolution for Water Management Problems -- Sobol Sequence Based MOSADE Algorithm for Multi-Objective Design of Water Distribution Networks -- A Comparative Study on Parameter Estimation of Covid Epidemiological Models using Differential Evolution Algorithm -- Applications of Differential Evolution in Electric Power Systems -- Detection of Heavy Sandstorm Regions using Composite Differential Evolution Algorithm -- A Hybrid Artificial Differential Evolution Gorilla Troops Optimizer for High Dimensional Optimization Problems.
001443978 506__ $$aAccess limited to authorized users.
001443978 520__ $$aThis book addresses and disseminates state-of-the-art research and development of differential evolution (DE) and its recent advances, such as the development of adaptive, self-adaptive and hybrid techniques. Differential evolution is a population-based meta-heuristic technique for global optimization capable of handling non-differentiable, non-linear and multi-modal objective functions. Many advances have been made recently in differential evolution, from theory to applications. This book comprises contributions which include theoretical developments in DE, performance comparisons of DE, hybrid DE approaches, parallel and distributed DE for multi-objective optimization, software implementations, and real-world applications. The book is useful for researchers, practitioners, and students in disciplines such as optimization, heuristics, operations research and natural computing.
001443978 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed February 3, 2022).
001443978 650_0 $$aEvolution equations.
001443978 650_6 $$aÉquations d'évolution.
001443978 655_0 $$aElectronic books.
001443978 7001_ $$aKumar, B. Vinoth,$$eeditor.
001443978 7001_ $$aOliva, Diego,$$eeditor.
001443978 7001_ $$aSuganthan, Ponnuthurai Nagaratnam,$$eeditor.
001443978 77608 $$iPrint version: $$z9811680817$$z9789811680816$$w(OCoLC)1280389158
001443978 830_0 $$aStudies in computational intelligence ;$$vv. 1009.$$x1860-9503
001443978 852__ $$bebk
001443978 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-16-8082-3$$zOnline Access$$91397441.1
001443978 909CO $$ooai:library.usi.edu:1443978$$pGLOBAL_SET
001443978 980__ $$aBIB
001443978 980__ $$aEBOOK
001443978 982__ $$aEbook
001443978 983__ $$aOnline
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