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| BP神经网络在效能评估中的样本训练 | |
| 引用本文： | 史彦斌,高运泉,张安.BP神经网络在效能评估中的样本训练[J].火力与指挥控制,2007,32(4):120-122. |
| 作者姓名： | 史彦斌 高运泉 张安 |
| 作者单位： | 1. 西北工业大学,陕西,西安,710072;空军航空大学,吉林,长春,130022 2. 空军航空大学,吉林,长春,130022 3. 西北工业大学,陕西,西安,710072 |
| 摘 要： | 根据WSEIAC模型建立了地面防空导弹武器系统效能评估的指标体系,并依此模型建立与之对应的三层BP神经网络.简要分析了BP算法的实现过程,利用专家打分法和模糊层次法相结合的方式取得该神经网络应用于地面防空导弹武器系统效能评估时的训练样本,并对此神经网络进行学习训练,直至达到精度要求.经验证,该网络在评价地面防空导弹武器系统效能时减少了评估中的人因影响,使评估结果更为科学. |
| 关 键 词： | BP神经网络 效能评估 样本训练 神经网络 武器系统效能评估 样本训练 Efficiency Evaluation BP Neural Network Training Sample 科学 评估结果 影响 评价 验证 精度要求 学习 训练样本 网络应用 结合 模糊层次法 专家打分法 利用 |
| 文章编号： | 1002-0640(2007)04-0120-03 |
| 修稿时间： | 2006年6月18日 |
Research on Sample Training of BP Neural Network in Efficiency Evaluation |
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| SHI Yan-bin,GAO Yun-quan,ZHANG An.Research on Sample Training of BP Neural Network in Efficiency Evaluation[J].Fire Control & Command Control,2007,32(4):120-122. | |
| Authors: | SHI Yan-bin GAO Yun-quan ZHANG An |
| Abstract: | According to the WSEIAC model,an index hierarchy of ground antiaircraft missile armament system's efficiency has been developed,and its corresponding three BP nerve network was established.It is briefly concerned with the analysis of the BP algorithm,then through Delphi technique and the fuzzy analytical hierarchy process,several groups of training samples are chosen to train the BP neural networks until the precision meets requirements.It is shown that this BP neural network limits the artificial factors when it was been used to evaluate the ground antiaircraft missile armament system's efficiency.And it was concluded that this method is scientific and creditable. |
| Keywords: | BP neural network efficiency evaluation sample training |
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