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001436717 001__ 1436717
001436717 003__ OCoLC
001436717 005__ 20230309004109.0
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001436717 019__ $$a1252706067$$a1284937651
001436717 020__ $$a9789811606625$$q(electronic bk.)
001436717 020__ $$a9811606625$$q(electronic bk.)
001436717 020__ $$z9789811606618
001436717 020__ $$z9811606617
001436717 0247_ $$a10.1007/978-981-16-0662-5$$2doi
001436717 035__ $$aSP(OCoLC)1252423190
001436717 040__ $$aEBLCP$$beng$$erda$$epn$$cEBLCP$$dGW5XE$$dYDX$$dOCLCO$$dOCLCF$$dUKAHL$$dOCLCO$$dOCLCQ$$dCOM$$dOCLCQ
001436717 049__ $$aISEA
001436717 050_4 $$aQ337.3
001436717 08204 $$a006.3/824$$223
001436717 24500 $$aApplied optimization and swarm intelligence /$$cEneko Osaba, Xin-She Yang, editors.
001436717 264_1 $$aSingapore :$$bSpringer,$$c[2021]
001436717 264_4 $$c©2021
001436717 300__ $$a1 online resource (236 pages)
001436717 336__ $$atext$$btxt$$2rdacontent
001436717 337__ $$acomputer$$bc$$2rdamedia
001436717 338__ $$aonline resource$$bcr$$2rdacarrier
001436717 4901_ $$aSpringer tracts in nature-inspired computing
001436717 5050_ $$aApplied Optimization and Swarm Intelligence: A Systematic Review and Prospect Opportunities -- A Review on Ensemble Methods and their Applications to Optimization Problems -- A Brief Overview of Swarm Intelligence-Based Algorithms for Numerical Association Rule Mining -- Review of Swarm Intelligence for Improving Time Series Forecasting -- Soccer-Inspired Metaheuristics: Systematic Review of Recent Research and Applications -- Formal Cognitive Modeling of Swarm Intelligence for Decision-Making Optimization Problems -- Nature-Inspired Optimization Algorithms for Path Planning and Fuzzy Tracking Control of Mobile Robots -- A Hardware Architecture and Physical Prototype for General-Purpose Swarm Minirobotics: Proteus II -- Evolving a Multi-Objective Optimization Framework -- Swarm Intelligence Based Optimum Design of Deep Excavation System.
001436717 506__ $$aAccess limited to authorized users.
001436717 520__ $$aThis book gravitates on the prominent theories and recent developments of swarm intelligence methods, and their application in both synthetic and real-world optimization problems. The special interest will be placed in those algorithmic variants where biological processes observed in nature have underpinned the core operators underlying their search mechanisms. In other words, the book centers its attention on swarm intelligence and nature-inspired methods for efficient optimization and problem solving. The content of this book unleashes a great opportunity for researchers, lecturers and practitioners interested in swarm intelligence, optimization problems and artificial intelligence.
001436717 588__ $$aDescription based on print version record.
001436717 650_0 $$aSwarm intelligence.
001436717 650_0 $$aMathematical optimization.
001436717 650_6 $$aOptimisation mathématique.
001436717 655_0 $$aElectronic books.
001436717 7001_ $$aOsaba, Eneko,$$eeditor.
001436717 7001_ $$aYang, Xin-She,$$eeditor.
001436717 77608 $$iPrint version:$$aOsaba, Eneko.$$tApplied Optimization and Swarm Intelligence.$$dSingapore : Springer Singapore Pte. Limited, ©2021$$z9789811606618
001436717 830_0 $$aSpringer tracts in nature-inspired computing.
001436717 852__ $$bebk
001436717 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-16-0662-5$$zOnline Access$$91397441.1
001436717 909CO $$ooai:library.usi.edu:1436717$$pGLOBAL_SET
001436717 980__ $$aBIB
001436717 980__ $$aEBOOK
001436717 982__ $$aEbook
001436717 983__ $$aOnline
001436717 994__ $$a92$$bISE