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001469864 001__ 1469864
001469864 003__ OCoLC
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001469864 019__ $$a1382691101
001469864 020__ $$a9783031347283$$q(electronic bk.)
001469864 020__ $$a3031347285$$q(electronic bk.)
001469864 020__ $$z9783031347276
001469864 020__ $$z3031347277
001469864 0247_ $$a10.1007/978-3-031-34728-3$$2doi
001469864 035__ $$aSP(OCoLC)1384459943
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001469864 049__ $$aISEA
001469864 050_4 $$aTA636
001469864 08204 $$a624.1$$223/eng/20230621
001469864 24500 $$aHybrid metaheuristics in structural engineering :$$bincluding machine learning applications /$$cGebrail Bekdaş, Sinan Melih Nigdeli, editors.
001469864 264_1 $$aCham :$$bSpringer,$$c[2023]
001469864 264_4 $$c©2023
001469864 300__ $$a1 online resource (viii, 305 pages) :$$billustrations (some color).
001469864 336__ $$atext$$btxt$$2rdacontent
001469864 337__ $$acomputer$$bc$$2rdamedia
001469864 338__ $$aonline resource$$bcr$$2rdacarrier
001469864 4901_ $$aStudies in systems, decision and control,$$x2198-4190 ;$$vvolume 480
001469864 5050_ $$aIntroduction and Overview: Hybrid Metaheuristics in Structural Engineering - Including Machine Learning Applications -- The Development of Hybrid Metaheuristics in Structural Engineering -- Optimum Design of Reinforced Concrete Columns in Case of Fire -- Hybrid Social Network Search and Material Generation Algorithm for Shape and Size Optimization of Truss Structures -- Development of a Hybrid Algorithm for Optimum Design of a Large-Scale Truss Structure.
001469864 506__ $$aAccess limited to authorized users.
001469864 520__ $$aFrom the start of life, people used their brains to make something better in design in ordinary works. Due to that, metaheuristics are essential to living things, and several inspirations from life have been used in the generation of new algorithms. These algorithms have unique features, but the usage of different features of different algorithms may give more effective optimum results in means of precision in optimum results, computational effort, and convergence. This book is a timely book to summarize the latest developments in the optimization of structural engineering systems covering all classical approaches and new trends including hybrids metaheuristic algorithms. Also, artificial intelligence and machine learning methods are included to predict optimum results by skipping long optimization processes. The main objective of this book is to introduce the fundamentals and current development of methods and their applications in structural engineering. .
001469864 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed June 21, 2023).
001469864 650_0 $$aStructural engineering$$xData processing.
001469864 650_0 $$aArtificial intelligence$$xEngineering applications.
001469864 650_0 $$aMetaheuristics.
001469864 655_0 $$aElectronic books.
001469864 7001_ $$aBekdas, Gebrail,$$d1980-$$eeditor.
001469864 7001_ $$aNigdeli, Sinan Melih,$$d1982-$$eeditor.
001469864 77608 $$iPrint version: $$z3031347277$$z9783031347276$$w(OCoLC)1378288426
001469864 830_0 $$aStudies in systems, decision and control ;$$vv. 480.$$x2198-4190
001469864 852__ $$bebk
001469864 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-34728-3$$zOnline Access$$91397441.1
001469864 909CO $$ooai:library.usi.edu:1469864$$pGLOBAL_SET
001469864 980__ $$aBIB
001469864 980__ $$aEBOOK
001469864 982__ $$aEbook
001469864 983__ $$aOnline
001469864 994__ $$a92$$bISE