| 基于神经网络同时测定UF_6中钼、钛和钨的研究 |
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| 引用本文： | 李海燕,蒋永锋,王关平. 基于神经网络同时测定UF_6中钼、钛和钨的研究[J]. 新技术新工艺, 2008, 0(12) |
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| 作者姓名： | 李海燕 蒋永锋 王关平 |
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| 作者单位： | 1. 甘肃农业大学,工学院,甘肃,兰州,730070
2. 河海大学,机电工程学院,江苏,常州,213022 |
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| 摘 要： | 运用神经网络与分光光度结合的方法,提出了同时分析六氟化铀中Mo、Ti和W 3种杂质元素的技术.训练网络确定的最佳训练参数为学习速率为0.60,动量项为0.85.检测集测定的六氟化铀中Mo、Ti和W 3种元素的回收率均在90%～110%之间,方法精密度分别为3.3%、3.9%、4.3%,对实际样品进行测定,并与ICP-AES法结果相比较,两者间相对偏差均小于10%.
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| 关 键 词： | 神经网络 分光光度法 同时测定 |
Determining Molybdenum,Titanium and Tungsten in Radium Hexafluoride Based on Neural Networks Tool |
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| LI Haiyan,JIANG Yongfeng,WANG Guanping. Determining Molybdenum,Titanium and Tungsten in Radium Hexafluoride Based on Neural Networks Tool[J]. New Technology & New Process, 2008, 0(12) |
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| Authors: | LI Haiyan JIANG Yongfeng WANG Guanping |
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| Affiliation: | LI Haiyan1,JIANG Yongfeng2,WANG Guanping1(1.Institute of Technology,Gansu Agricultural University,Lanzhou 730070,China,2.College of Electrical , Mechanical Engineering,Hehai University,Changzhou 213022,China) |
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| Abstract: | A method of combination neural networks tool and spectrophotometry method simultaneously determining three impurities molybdenum,titanium and tungsten in uranium hexafluoride is established in this paper.The best parameters are selected by training the artificial neural networks:learning rate is 0.60,momentum is 0.85.By estimating the inspecting set,the recoveries are from 90% to 110% and the precisions are 3.3%,3.9% and 4.3% respectively for molybdenum,titanium and tungsten.By determining the samples of ur... |
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| Keywords: | neural network spectrophotometry simultaneous determination |
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