人工神经网络用于光度法同时测定铜和镉

Application of Artificial Neural Network to SimultaneousSpetrophotometric Determination of Cu, Cd

采用PAR-Cu、Cd显色体系,应用L-M优化BP神经网络原理,对吸收光谱严重重叠的两组分金属配合物体系同时进行各含量测定,获得较为满意的结果。实验表明,该方法具有学习速度快、预测结果准确度高等特点,是多组分分析的较好方法之一。

By means of artifical neural network and back-propagation algorithm, the two-component metal coordinate compounds of PAR-Cu, Cd were determined simultaneously, in which the spectra overlapped. The experiment results show that the determination is accurate, and the method has good performance.