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An agent-based algorithm resembles behaviour of tree-dwelling bats under fission-fusion dynamics
Title An agent-based algorithm resembles behaviour of tree-dwelling bats under fission-fusion dynamics Author Zelenka Ján 1983 SAVINFO - Ústav informatiky SAV SCOPUS RID ORCID Co-authors Kasanický Tomáš 1978- SAVINFO - Ústav informatiky SAV SCOPUS RID ORCID Budinská Ivana 1964- SAVINFO - Ústav informatiky SAV SCOPUS RID ORCID Kaňuch Peter 1977 SAVEKLES - Ústav ekológie lesa SAV ORCID Source document Scientific Reports. Vol. 10 (2020), art. no. 16793 Language eng - English URL URL link Document kind rozpis článkov z periodík (rbx) Citations PERONY, Nicolas - KERTH, Gerald - SCHWEITZER, Frank. Data-driven modelling of group formation in the fission-fusion dynamics of Bechstein's bats. In JOURNAL OF THE ROYAL SOCIETY INTERFACE, 2022, vol. 19, no. 190, pp. ISSN 1742-5689. Dostupné na: https://doi.org/10.1098/rsif.2022.0170. Zhang, XR; Ding, WR; Wang, YF; Luo, YZ; Zhang, ZH; Xiao, J. Bio-Inspired Self-Organized Fission-Fusion Control Algorithm for UAV Swarm. In AEROSPACE. eISSN 2226-4310, 2022, vol. 9, iss. 11, art. nu. 714. DOI10.3390/aerospace9110714 ZHANG, Xiaorong - WANG, Yufeng - DING, Wenrui - WANG, Qing - ZHANG, Zhilan - JIA, Jun. Bio-Inspired Fission-Fusion Control and Planning of Unmanned Aerial Vehicles Swarm Systems via Reinforcement Learning. In APPLIED SCIENCES-BASEL, 2024, vol. 14, no. 3, pp. Category ADCA - Scientific papers in foreign journals registered in Current Contents Connect with IF (impacted) Category of document (from 2022) V3 - Vedecký výstup publikačnej činnosti z časopisu Type of document článok Year 2020 Registered in WOS Registered in SCOPUS Registered in CCC DOI 10.1038/s41598-020-72999-0 article
File name Access Size Downloaded Type License An agent-based algorithm resembles behaviour of tree-dwelling bats under fission-fusion dynamics.pdf available 1.8 MB 1 Publisher's version rok CC IF IF Q (best) JCR Av Jour IF Perc SJR SJR Q (best) CiteScore A rok vydania rok metriky IF IF Q (best) SJR SJR Q (best) 2020 2019 3.998 Q1 1.341 Q1
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