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Communication Analysis of Network-Centric Warfare via Transformation of System of Systems Model into Integrated System Model Using Neural Network

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  • Bong Gu Kang
  • Kyung-Min Seo
  • Tag Gon Kim

Abstract

Communication system in the network-centric warfare (NCW) has been analyzed from the perspective of the system of systems (SoS), which consists of a combat system and a network system so that the two reflect each other’s effects. However, this paradoxically causes a prolonged execution time. To solve this problem, this paper proposes an advanced integrated modeling method for the communication analysis in the NCW via the transformation of the SoS, which reduces the simulation execution time while ensuring the accuracy of the communication effects. The proposed models mainly cover interentity traffic and intraentity mobility developed in the form of feed-forward neural networks to guarantee two-way interactions between the combat system and the network system. Because they are characterized as discrete events, the proposed models are designed with the discrete-event system specification (DEVS) formalism. The experimental results show that the proposed transformation reduced an error by 6.40% compared to the existing method and reduced the execution time 3.78-fold compared to the SoS-based NCW simulation.

Suggested Citation

  • Bong Gu Kang & Kyung-Min Seo & Tag Gon Kim, 2018. "Communication Analysis of Network-Centric Warfare via Transformation of System of Systems Model into Integrated System Model Using Neural Network," Complexity, Hindawi, vol. 2018, pages 1-16, June.
    • Handle: RePEc:hin:complx:6201356
    DOI: 10.1155/2018/6201356
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    References listed on IDEAS

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    1. Zhong Xiao & Lingxi Peng & Yi Chen & Haohuai Liu & Jiaqing Wang & Yangang Nie, 2017. "The Dissolved Oxygen Prediction Method Based on Neural Network," Complexity, Hindawi, vol. 2017, pages 1-6, October.
    2. Carmody K. McCalley & Ben J. Woodcroft & Suzanne B. Hodgkins & Richard A. Wehr & Eun-Hae Kim & Rhiannon Mondav & Patrick M. Crill & Jeffrey P. Chanton & Virginia I. Rich & Gene W. Tyson & Scott R. Sal, 2014. "Methane dynamics regulated by microbial community response to permafrost thaw," Nature, Nature, vol. 514(7523), pages 478-481, October.
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