| 基于Elman神经网络的252Cf源核系统随机中子脉冲信号识别方法 |
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| 引用本文： | 冯鹏,刘思远,米德伶.基于Elman神经网络的252Cf源核系统随机中子脉冲信号识别方法[J].强激光与粒子束,2011,23(8). |
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| 作者姓名： | 冯鹏 刘思远 米德伶 |
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| 作者单位： | 重庆大学 光电工程学院， 光电技术及系统教育部重点实验室, 重庆 400044 |
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| 基金项目： | 中央高校基本科研业务费基金项目(CDJZR11120006) |
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| 摘 要： | 针对252Cf自发裂变中子源构成的核信息系统，以实际所测随机中子脉冲数据的自相关函数为研究对象，借助仿真实验， 利用Elman神经网络对不同质量核材料进行识别。在实测数据的基础上，通过叠加随机抖动，模拟产生了不同质量核材料的相关函数样本，并将其用于神经网络的训练与测试，实验结果表明，训练过的Elman神经网络能够较好地识别相关函数的特征，分辨不同质量的核材料，平均识别率达到85%，综合平均误差为0.04，且具有较高的鲁棒性。
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| 关 键 词： | 252Cf源核信息系统 随机中子信号 Elman神经网络 核材料识别 |
| 收稿时间： | 1900-01-01; |
Identification of stochastic neutron pulse signal of ~(252)Cf nuclear system based on Elman neural network |
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| Feng Peng,Liu Siyuan,Mi Deling.Identification of stochastic neutron pulse signal of ~(252)Cf nuclear system based on Elman neural network[J].High Power Laser and Particle Beams,2011,23(8). |
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| Authors: | Feng Peng Liu Siyuan Mi Deling |
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| Institution: | (Key Laboratory of Opto-electronics Technology and System of Ministry of Education, College of Opto-Electronics Engineering, Chongqing University, Chongqing 400044, China) |
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| Abstract: | Correct and effective identification of nuclear material is a key part for nuclear weapon's verification.Based on the nuclear information system constructed with 252Cf spontaneous neutron source,the simulated autocorrelation functions are utilized for identification of different fissile mass with Elman neural network.The experimental results show the trained Elman neural network is able to distinguish the characteristics of autocorrelation function,identify different fissile mass,and the average identificat... |
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| Keywords: | nuclear information system of 252Cf source stochastic neutron signal Elman neural network nuclear material identification |
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