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中文摘要：
针对α能谱低能拖尾现象严重、采用数学函数拟合时参数意义模糊等问题，提出将BP神经网络方法应用于α能谱分析工作中。通过搭建基于MATLAB平台的BP神经网络模型，分别进行α谱线预测和元素种类判断。首先选取可以表征能谱信息的参数作为输入，利用网络强大非线性映射功能，实现对仅能谱的预测。其次以能谱全谱信息作为输入，通过对输人的数据信息进行归纳分类，判断出核素的种类。实验将预测谱线与原始能谱对比，其相关系数在0．99以上，残差范围在2％左右波动，能准确预测出α能谱。在核素种类的预测结果中，以低于1％的误差准确对实验中的两种核素进行判断。分析表明，神经网络具有准确、简单等优点，能较好地应用于仪能谱分析工作中。
英文摘要：
The trailing phenomenon of α low energy spectrum is serious, and parameters meaning with the mathematical function fitting method are fuzzy. In view of these problems,it is proposed that the BP neural networks is applied to the α spectrum analysis. The model of BP neural networks is built based on MATLAB so as to predict the ct spectral lines and estimate the element type respectively. Firstly, parameters that can represent the spectral information are selected as the input parameters for network training, and the ct spectrum is predicted by using the nonlinear mapping function. Secondly, taking the full spectrum information as input data, the nuclide species are estimated by classifying the input data. According to the experimental results from comparison on the predicted spectrum and the original spectrum, its correlation coefficient is above 0. 99, and the residual error range is around 2%. For the prediction results of nuclide types, the error for the prediction of two nuclides types is less than 1%. The research resuhs above show that, BP neural networks method is accurate and simple, and is competent to do the α spectrum analysis work.
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