基于DBN效能拟合的舰艇编队作战效能敏感性分析

Translated title of the contribution: Sensitivity analysis of ship formation operational effectiveness based on DBN effectiveness fitting

Bo Li, Haoran Luo, Linyu Tian, Yuanxun Wang

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Aiming at the problem of insufficient data utilization and high requirements for data integrity in the traditional ship formation combat effectiveness analysis analysis method, this paper proposes a performance analysis fitting model based on deep belief network. Start with the most representative sensitivity analysis method-Sobol index method, and then take characteristic learning ability of deep learning, constructing a effectiveness fitting network based on Deep Belief Network(DBN), with network training and parameter optimization combined with unsupervised pre-training and supervised tuning. Finally, the experiments are simulated and analyzed based on the formation of air defense combat. Simulation results verify the applicability and effectiveness of the model.

Translated title of the contributionSensitivity analysis of ship formation operational effectiveness based on DBN effectiveness fitting
Original languageChinese (Traditional)
Article number323214
JournalHangkong Xuebao/Acta Aeronautica et Astronautica Sinica
Volume40
Issue number12
DOIs
StatePublished - 25 Dec 2019

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