001447475 000__ 03147cam\a2200493Ii\4500
001447475 001__ 1447475
001447475 003__ OCoLC
001447475 005__ 20230310004119.0
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001447475 007__ cr\un\nnnunnun
001447475 008__ 220614s2022\\\\sz\a\\\\ob\\\\001\0\eng\d
001447475 020__ $$a9783030969172$$q(electronic bk.)
001447475 020__ $$a3030969177$$q(electronic bk.)
001447475 020__ $$z9783030969165$$q(print)
001447475 0247_ $$a10.1007/978-3-030-96917-2$$2doi
001447475 035__ $$aSP(OCoLC)1329438023
001447475 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dEBLCP$$dOCLCF$$dOCLCQ
001447475 049__ $$aISEA
001447475 050_4 $$aQA76.9.A43
001447475 08204 $$a005.13$$223/eng/20220614
001447475 1001_ $$aEftimov, Tome,$$eauthor.
001447475 24510 $$aDeep statistical comparison for meta-heuristic stochastic optimization algorithms /$$cTome Eftimov, Peter Korošec.
001447475 264_1 $$aCham :$$bSpringer,$$c2022.
001447475 300__ $$a1 online resource (xvii, 133 pages) :$$billustrations (some color).
001447475 336__ $$atext$$btxt$$2rdacontent
001447475 337__ $$acomputer$$bc$$2rdamedia
001447475 338__ $$aonline resource$$bcr$$2rdacarrier
001447475 4901_ $$aNatural computing deries
001447475 504__ $$aIncludes bibliographical references and index.
001447475 5050_ $$aIntroduction -- Metaheuristic Stochastic Optimization -- Benchmarking Theory -- Introduction to Statistical Analysis -- Approaches to Statistical Comparisons -- Deep Statistical Comparison in Single-Objective Optimization -- Deep Statistical Comparison in Multiobjective Optimization -- DSCTool: A Web-Service-Based E-Learning Tool -- Summary.
001447475 506__ $$aAccess limited to authorized users.
001447475 520__ $$aFocusing on comprehensive comparisons of the performance of stochastic optimization algorithms, this book provides an overview of the current approaches used to analyze algorithm performance in a range of common scenarios, while also addressing issues that are often overlooked. In turn, it shows how these issues can be easily avoided by applying the principles that have produced Deep Statistical Comparison and its variants. The focus is on statistical analyses performed using single-objective and multi-objective optimization data. At the end of the book, examples from a recently developed web-service-based e-learning tool (DSCTool) are presented. The tool provides users with all the functionalities needed to make robust statistical comparison analyses in various statistical scenarios. The book is intended for newcomers to the field and experienced researchers alike. For newcomers, it covers the basics of optimization and statistical analysis, familiarizing them with the subject matter before introducing the Deep Statistical Comparison approach.
001447475 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed June 14, 2022).
001447475 650_0 $$aMetaheuristics.
001447475 650_0 $$aMathematical optimization.
001447475 655_0 $$aElectronic books.
001447475 7001_ $$aKorošec, Peter,$$d1977-$$eauthor.
001447475 830_0 $$aNatural computing series.
001447475 852__ $$bebk
001447475 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-96917-2$$zOnline Access$$91397441.1
001447475 909CO $$ooai:library.usi.edu:1447475$$pGLOBAL_SET
001447475 980__ $$aBIB
001447475 980__ $$aEBOOK
001447475 982__ $$aEbook
001447475 983__ $$aOnline
001447475 994__ $$a92$$bISE