An improved artificial bee colony algorithm based on balance-evolution strategy for unmanned combat aerial vehicle path planning.
Unmanned combat aerial vehicles (UCAVs) have been of great interest to military organizations throughout the world due to their outstanding capabilities to operate in dangerous or hazardous environments. UCAV path planning aims to obtain an optimal flight route with the threats and constraints in th...
| Publicado en: | Scientific World Journal pp. 232704 - 232705 |
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| Autores principales: | , , |
| Formato: | research Journal Article |
| Publicado: |
Wiley-Blackwell
2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=103821218&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 103821218 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1537744X 1BX5 jtl: Scientific World Journal issn: 1537744X maglogo: N pubinfo: dt: 2014 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 103821218 103821218 NLM24790555 2012570834 10.1155/2014/232704 NLM24790555 PMC3980870 103821218 ppf: 232704 ppct: 1 formats: tig: atl: An improved artificial bee colony algorithm based on balance-evolution strategy for unmanned combat aerial vehicle path planning. aug: au: Li, Bai Gong, Li-Gang Yang, Wen-Lun affil: School of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China. sug: subj: Algorithms Models, Theoretical ab: Unmanned combat aerial vehicles (UCAVs) have been of great interest to military organizations throughout the world due to their outstanding capabilities to operate in dangerous or hazardous environments. UCAV path planning aims to obtain an optimal flight route with the threats and constraints in the combat field well considered. In this work, a novel artificial bee colony (ABC) algorithm improved by a balance-evolution strategy (BES) is applied in this optimization scheme. In this new algorithm, convergence information during the iteration is fully utilized to manipulate the exploration/exploitation accuracy and to pursue a balance between local exploitation and global exploration capabilities. Simulation results confirm that BE-ABC algorithm is more competent for the UCAV path planning scheme than the conventional ABC algorithm and two other state-of-the-art modified ABC algorithms. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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