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CHEN Jun, Wang Ru-hang. Evaluation of Anti-Torpedo Operational Effectiveness for Acoustic Decoy Based on LMBP Neural Network[J]. Journal of Unmanned Undersea Systems, 2008, 16(5): 055-59. doi: 10.11993/j.issn.1673-1948.2008.05.015
Citation: CHEN Jun, Wang Ru-hang. Evaluation of Anti-Torpedo Operational Effectiveness for Acoustic Decoy Based on LMBP Neural Network[J]. Journal of Unmanned Undersea Systems, 2008, 16(5): 055-59. doi: 10.11993/j.issn.1673-1948.2008.05.015

Evaluation of Anti-Torpedo Operational Effectiveness for Acoustic Decoy Based on LMBP Neural Network

doi: 10.11993/j.issn.1673-1948.2008.05.015
  • Received Date: 2008-01-02
  • Rev Recd Date: 2008-01-23
  • Publish Date: 2008-10-30
  • To better evaluate anti-torpedo operational effectiveness for various acoustic decoys some effectiveness evaluation factors are presented and analyzed according to the actual condition. Combining Delphi and simulation experiment, back propagation(BP) artificial neural network based on Levenberg-Marquardt (LM) algorithm is applied to evaluate anti-torpedo operational effectiveness for acoustic decoys. Traingdx algorithm and LM algorithm are compared and analyzed, and the latter shows faster training speed and smaller errors. By comparing the counterwork effects of two kinds of acoustic decoys, the evaluation method based on BP neural network is proved to be more feasible.

     

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