空军工程大学学报（自然科学版）2012，Vol.13Issue(5)：40-44,5.DOI:10.3969/j.issn.1009-3516.2012.05.009
基于BP神经网络的TBM拦截效果评估
TBM Intercepting Effect Assessment Based on BP Neural Network
摘要
Abstract
TBM intercepting effect assessment is an important and complex job in the TBMD. In order to comprehensively consider the influence of various factors on the intercepting effect assessment in TBM intercepting combat, the assessment system is analyzed based on infrared imaging, ISAR imaging and maneuvering target tracking methods. In view of Neural Network' advantage in dealing with the complex problems, an assessment model with BP Neural Network is built, and the building process is discussed in detail. The standard BP algorithm with the problems that the convergence speed is slow and local minimum points are easily formed, is improved through adding momentum top and adjusting factors timely. Finally, the improved BP algorithm is simulated through living example and analyzed, the result shows that the improved algorithm is better in convergence speed and accuracy, and simultaneously verifies the validity and reliability of the model in TBM intercepting effect assessment.关键词
弹道导弹防御/TBM拦截效果/评估模型/BP算法Key words
TBMD/TBM intercepting effect/ assessment model/ BP algorithm分类
信息技术与安全科学引用本文复制引用
胡晓伟,胡国平,田野,王宇晨..基于BP神经网络的TBM拦截效果评估[J].空军工程大学学报（自然科学版）,2012,13(5):40-44,5.基金项目
陕西省自然科学基础研究计划资助项目(2012JM8020) （2012JM8020）
