摘要
本文利用干扰效应并采用模拟退火 误差反向传播人工神经网络算法辅助原子吸收分光光度法在单波长下对粮谷中痕量镉和砷的同时测定时行了研究 ,取得了满意结果。标准加入法的回收率分别为 91%～98%和 87%～ 92 % ,7次平行测定结果的相对标准偏差均小于 4%。该法快速。
Simultaneous determination of two components in single wavelength using interferencing effect and atomic absorption spectrophotometry assisted by simulated annealing back propagation of error artificial neural networks algorithm was realized,and simultaneous determination of trace cadmium and arsenic in grains was studied.The results obtained are satisfactory.The recoveries found by standard addition method are 91%—98% and 87%—92% respectively.Relative standard deviations for 7 times of determinations are all less than 4%.This method is fast and simple.
出处
《光谱学与光谱分析》
SCIE
EI
CAS
CSCD
北大核心
2001年第3期387-390,共4页
Spectroscopy and Spectral Analysis
基金
国家商检局科学基金资助课题!(K980 1 )
关键词
砷
镉
模拟退火算法
人工神经网络算法
原子吸收分光光度法
粮谷
痕量分析
Cadmium, Arsenic, Simulated annealing algorithm, Artificial neural networks algorithm, Atomic absorption spectrophotometry
