Buch, Englisch, 639 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1003 g
9th International Conference, ICSI 2018, Shanghai, China, June 17-22, 2018, Proceedings, Part I
Buch, Englisch, 639 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1003 g
Reihe: Theoretical Computer Science and General Issues
ISBN: 978-3-319-93814-1
Verlag: Springer International Publishing
The two-volume set of LNCS 10941 and 10942 constitutes the proceedings of the 9th International Conference on Advances in Swarm Intelligence, ICSI 2018, held in Shanghai, China, in June 2018. The total of 113 papers presented in these volumes was carefully reviewed and selected from 197 submissions. The papers were organized in topical sections as follows: theories and models of swarm intelligence; ant colony optimization; particle swarm optimization; artificial bee colony algorithms; genetic algorithms; differential evolution; fireworks algorithms; bacterial foraging optimization; artificial immune system; hydrologic cycle optimization; other swarm-based optimization algorithms; hybrid optimization algorithms; multi-objective optimization; large-scale global optimization; multi-agent systems; swarm robotics; fuzzy logic approaches; planning and routing problems; recommendation in social media; prediction, classification; finding patterns; image enhancement; deep learning.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Software Engineering
- Mathematik | Informatik EDV | Informatik Angewandte Informatik
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Datenbankdesign & Datenbanktheorie
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
- Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik
- Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung
Weitere Infos & Material
Theories and models of swarm intelligence.- ant colony optimization; particle swarm optimization.- artificial bee colony algorithms.- genetic algorithms.- differential evolution.- fireworks algorithms.- bacterial foraging optimization.- artificial immune system.- hydrologic cycle optimization.- other swarm-based optimization algorithms.- hybrid optimization algorithms.- multi-objective optimization.- large-scale global optimization.- multi-agent systems.- swarm robotics; fuzzy logic approaches.- planning and routing problems.- recommendation in social media.- prediction.- classification.- finding patterns.- image enhancement.- deep learning.
