Buch, Englisch, 105 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1883 g
Buch, Englisch, 105 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1883 g
Reihe: SpringerBriefs in Computational Intelligence
ISBN: 978-3-319-70850-8
Verlag: Springer
Proposes a methodology for parameter adaptation in meta-heuristic optimization methods
Uses three different optimization methods: PSO (Particle Swarm Optimization), ACO (Ant Colony Optimization) and GSA (Gravitational Search Algorithm), to verify the improvement of the proposed methodology
Demonstrates the advantage of the methodology by using various simulations
Uses three different optimization methods: PSO (Particle Swarm Optimization), ACO (Ant Colony Optimization) and GSA (Gravitational Search Algorithm), to verify the improvement of the proposed methodology
Demonstrates the advantage of the methodology by using various simulations
Olivas / Valdez / Castillo
Dynamic Parameter Adaptation for Meta-Heuristic Optimization Algorithms Through Type-2 Fuzzy Logic jetzt bestellen!
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Introduction.- Theory and Background.- Problems Statement.- Methodology.- Simulation Results.- Statistical Analysis and Comparison of Results.
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