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A GIS-Based Optimization of ACO in UAV Network

  • Weifeng SunEmail author
  • Yuanxun Xing
  • Guangqun Ma
  • Shumiao Yu
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 834)

Abstract

UAVs can carry out rescue work in the disaster area. The ant colony algorithm is used to search and rescue work in the disaster area based on GIS. Considering regional priority, an algorithm named priority-PAACO is proposed. Simulations and analysis show the effective of this algorithm.

Keywords

UAV GIS Priority-PAACO Parameter adjustment 

References

  1. 1.
    Yao, P., Wang, H.: Dynamic adaptive ant lion optimizer applied to route planning for unmanned aerial vehicle. Soft. Comput. 21(18), 5475–5488 (2017)CrossRefGoogle Scholar
  2. 2.
    Wang, S., Anselin, L., Bhaduri, B., et al.: CyberGIS software: a synthetic review and integration roadmap. Int. J. Geogr. Inf. Sci. 27(11), 2122–2145 (2013)CrossRefGoogle Scholar
  3. 3.
    Sun, W., Ji, Z., Sun, J., et al.: SAACO: a self adaptive ant colony optimization in cloudcomputing. In: 2015 IEEE Fifth International Conference on Big Data and Cloud Computing (BDCloud), pp. 148–153. IEEE (2015)Google Scholar
  4. 4.
    Sun, W., Xing, Y., Zhou, C., et al.: QSACO: A QoS-Based self-adapted ant colony optimization. In: 2017 5th IEEE International Conference on Mobile Cloud Computing, Services and Engineering (Mobile Cloud), pp. 157–160. IEEE (2017)Google Scholar
  5. 5.
    Tang, Z., Qi, L., Cheng, Z., et al.: An energy-efficient task scheduling algorithm in DVFS-enabled cloud environment. J. Grid Comput. 14(1), 55–74 (2016)CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Weifeng Sun
    • 1
    Email author
  • Yuanxun Xing
    • 1
  • Guangqun Ma
    • 1
  • Shumiao Yu
    • 1
  1. 1.School of SoftwareDalian University of TechnologyDalianChina

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