食品中铜铅镉锌同时测定的神经网络方法研究

食品中金属元素快速、简便的测试方法研究是有现实意义的。本文在（pH=1．5）硝酸钾-硝酸溶液环境中，借助于方波溶出伏安法对铜、钳、镉、锌4种金属离子的混合溶液进行了组分测定，并用人工神经网络对测定结果进行处理，建立了4种金属离子同时测定的神经网络测试模型。实例表明，该神经网络测试模型能够较好地解决金属离子之间的相互作用和伏安信号干扰问题，测量结果比较准确，具有一定的应用和研究价值。

Study on the Simultaneous Determination of Copper, Lead, Cadmium and Zinc in Food by Means of Artificial Neural Network

It is practically significant for studying on analysis methods for rapidly and easily determining trace metals in food. In this paper the stripping voltammetric responses were obtained in the solutions containing varying concentrations of Cu , Pb , Cd , and Zn by Square Wave Stripping Voltammetry in supporting electrolytes of KNO3 & HNO3(pH1.5). A feed-forward neural network was utilized to cope with the analysis results and trained to model the relationship between responses and concentrations in the situation of simultaneous determination of the four heavy metals. The results of the sample show that neural network can be used to solve the problems of significant complications due to interaction of metal cations. Based on comparatively accurate testing results, this method has practical applications and research values.