X荧光谱与人工神经网络相结合对陶片产地识别的研究

Study of recognition of production areas for ceramic fragments by X-fluorescence spectrum combined with artificial neural network

本文采用X射线荧光分析技术测量考古陶片中的微量元素,利用样品的元素种类和含量的不同对考古样本的产地进行智能化识别。针对多元素共存、计数率低等谱分析困难,采用人工神经网络方法对所测X荧光谱进行学习和识别。样本总数为48片,来自8个省份、20个采集地。用两种不同的网络结构分别对两类地域划分的陶片学习和识别,对准确产地分类的样本,产地识别率为100%;对其余样本,识别率大于60%。本方法的产地识别结果是可行的。

The X-fluorescence analysis technique was introduced to measure the trace elements in archeological ceramic fragment samples. Production areas of the samples were expected to be properly and intelligently identified according to the differences in both element＇s types and contents in samples. Aiming at the difficulties in spectrum analysis of the multi-element co-existence samples and in low count rates, the method of artificial neural network （ANN） was adopted to learn and identify the X-fluorescence spectra of samples. The total number of samples is 48 from 8 provinces and 20 gathering areas. Two kinds of structures of ANN are introduced to train and identify ceramic fragments in two classes of area domain, respectively. The correct rate of recognition was up to 100% for the samples whose production areas were accurately classified, while the rate was more than 60% for others. The recognition results of the method are satisfying.