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001446059 019__ $$a1311362544$$a1311465123$$a1311570584
001446059 020__ $$a9783031024627$$q(electronic bk.)
001446059 020__ $$a3031024621$$q(electronic bk.)
001446059 020__ $$z9783031024610
001446059 020__ $$z3031024613
001446059 0247_ $$a10.1007/978-3-031-02462-7$$2doi
001446059 035__ $$aSP(OCoLC)1311964319
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001446059 08204 $$a006.3/823$$223/eng/20220422
001446059 1112_ $$aEvoApplications (Conference)$$n(25th :$$d2022 :$$cMadrid, Spain)
001446059 24510 $$aApplications of evolutionary computation :$$b25th European Conference, EvoApplications 2022, held as part of EvoStar 2022, Madrid, Spain, April 20-22, 2022, proceedings /$$cJuan Luis Jiménez Laredo, J. Ignacio Hidalgo Perez, Kehinde Oluwatoyin Babaagba (Eds.).
001446059 264_1 $$aCham, Switzerland :$$bSpringer,$$c2022.
001446059 300__ $$a1 online resource (1 volume) :$$billustrations (black and white).
001446059 336__ $$atext$$btxt$$2rdacontent
001446059 337__ $$acomputer$$bc$$2rdamedia
001446059 338__ $$aonline resource$$bcr$$2rdacarrier
001446059 4901_ $$aLecture notes in computer science ;$$v13224
001446059 504__ $$aIncludes bibliographical references and author index.
001446059 5050_ $$aIntro -- Preface -- Organization -- Contents -- Applications of Evolutionary Computation -- An Enhanced Opposition-Based Evolutionary Feature Selection Approach -- 1 Introduction -- 2 Moth Flame Optimization -- 2.1 Binary Moth Flame Optimization -- 2.2 Binary Moth Flame Optimization for Feature Selection -- 3 The Proposed Approach -- 3.1 Initialization Using Opposition-Based Method -- 3.2 Retiring Flame -- 4 Experimental Setup and Results -- 5 Conclusions -- References -- A Methodology for Determining Ion Channels from Membrane Potential Neuronal Recordings -- 1 Introduction
001446059 5058_ $$a2 Conductance-Based Model Description -- 3 Defining a Benchmark with Known Types of Ion Channels -- 4 Methodology and Experimental Setup -- 5 Experimental Results -- 6 Conclusions -- A Mathematical Description of the Models -- B Experimental Setup and Parameter Ranges -- References -- Swarm Optimised Few-View Binary Tomography -- 1 Introduction -- 2 Binary Tomographic Reconstruction -- 3 Swarm Optimisation -- 4 Constrained Search in High Dimensions -- 5 Reconstructions -- 6 Results -- 7 Discussion -- 8 Conclusions -- References
001446059 5058_ $$aComparing Basin Hopping with Differential Evolution and Particle Swarm Optimization -- 1 Introduction -- 2 The Metaheuristics Studied -- 2.1 Basin Hopping -- 2.2 Differential Evolution -- 2.3 Particle Swarm Optimization -- 3 The Benchmarking Environment -- 4 Experimental Setup -- 5 Experimental Results -- 6 Conclusions -- References -- Combining the Properties of Random Forest with Grammatical Evolution to Construct Ensemble Models -- 1 Introduction -- 2 Methodology -- 2.1 Structured Grammatical Evolution -- 2.2 Random Structured Grammatical Evolution for Symbolic Regression Problems
001446059 5058_ $$a3 Experimental Setup -- 3.1 Study Problems -- 3.2 Configuration of the Algorithms -- 4 Results -- 5 Conclusions -- References -- EvoCC: An Open-Source Classification-Based Nature-Inspired Optimization Clustering Framework in Python -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 4 Framework Overview -- 4.1 Parameters -- 4.2 Datasets -- 4.3 Clustering with EvoCluster -- 4.4 Classification -- 4.5 Evaluation Measures -- 4.6 Results Management -- 5 Experiments and Visualizations -- 6 Conclusion and Future Works -- References -- Evolution of Acoustic Logic Gates in Granular Metamaterials
001446059 5058_ $$a1 Introduction -- 2 Problem Statement -- 3 Simulation Setup -- 3.1 2D Granular Simulator -- 3.2 Optimization Method -- 4 Results and Discussion -- 4.1 Evolution of an Acoustic Band Gap -- 4.2 Evolving an AND Gate -- 4.3 Evolving an XOR Gate -- 5 Conclusion and Future Work -- References -- Public-Private Partnership: Evolutionary Algorithms as a Solution to Information Asymmetry -- 1 Introduction -- 2 The Problem -- 3 Proposed Approach -- 3.1 The Model -- 3.2 Data -- 3.3 Adversarial Optimization -- 3.4 Operator (EA1) -- 3.5 Public Administration (EA2) -- 4 Experimental Evaluation
001446059 506__ $$aAccess limited to authorized users.
001446059 520__ $$aThis book constitutes the refereed proceedings of the 25th International Conference on Applications of Evolutionary Computation, EvoApplications 2022, held as part of Evo*2022, in April 2022, co-located with the Evo*2022 events EuroGP, EvoCOP, and EvoMUSART. The 46 revised full papers presented in this book were carefully reviewed and selected from 67 submissions. .
001446059 588__ $$aDescription based on print version record.
001446059 650_0 $$aEvolutionary computation$$vCongresses.
001446059 650_6 $$aRéseaux neuronaux à structure évolutive$$vCongrès.
001446059 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001446059 655_0 $$aElectronic books.
001446059 7001_ $$aLaredo, Juan Luis Jiménez,$$eeditor.
001446059 7001_ $$aPerez, J. Ignacio Hidalgo,$$eeditor.
001446059 7001_ $$aBabaagba, Kehinde Oluwatoyin,$$eeditor.
001446059 7112_ $$aEVOSTAR (Conference)$$d(2022 :$$cMadrid, Spain)
001446059 77608 $$iPrint version:$$aEvoApplications (Conference) (25th : 2022 : Madrid, Spain), creator.$$tApplications of evolutionary computation.$$dCham : Springer, 2022$$z9783031024610$$w(OCoLC)1308475608
001446059 830_0 $$aLecture notes in computer science ;$$v13224.
001446059 852__ $$bebk
001446059 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-02462-7$$zOnline Access$$91397441.1
001446059 909CO $$ooai:library.usi.edu:1446059$$pGLOBAL_SET
001446059 980__ $$aBIB
001446059 980__ $$aEBOOK
001446059 982__ $$aEbook
001446059 983__ $$aOnline
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