• Electronics Optics & Control
  • Vol. 25, Issue 5, 64 (2018)
CHEN Xia and HU Naikuan
Author Affiliations
  • [in Chinese]
  • show less
    DOI: 10.3969/j.issn.1671-637x.2018.05.013 Cite this Article
    CHEN Xia, HU Naikuan. Operational Effectiveness Assessment for Electronic Warfare UAVs Based on Improved WNN[J]. Electronics Optics & Control, 2018, 25(5): 64 Copy Citation Text show less

    Abstract

    Wavelet Neural Network (WNN) uses the gradient descent method to adjust the connecting weight and the scales for expanding/contracting and translating, which has the shortcomings of slow convergence speed and the local extremum. A method for assessing the operational effectiveness of electronic warfare UAVs based on Genetic Algorithm WNN (GA-WNN) is proposed. Based on WNN, the evaluation model uses GA to find the initial optimal WNN connecting weights, scaling parameters, and translating parameters. It avoids the blindness of artificial parameter setting. Simulation results show that this model can accurately and effectively assess the operational effectiveness of electronic warfare UAVs.
    CHEN Xia, HU Naikuan. Operational Effectiveness Assessment for Electronic Warfare UAVs Based on Improved WNN[J]. Electronics Optics & Control, 2018, 25(5): 64
    Download Citation