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organic toxin
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     The main progress made in the past two years in the major project of NSFC entitled "Study on modern nuclear analysis techniques and their applications in some environmental problems" is outlined, including molecular activation analysis, scanning proton microscopy, high-performance X-ray analysis, accelerator mass-spectroscopy, quality assurance of nuclear analysis, catastrophic environment, rare earth element ecosystem, organic toxin and atmospheric environment.
     概述国家自然科学基金重大项目“现代核分析技术应用研究及其在若干环境问题中的应用研究”两年来的主要进展,包括分子活化分析、扫描质子微探针、高性能X射线分析、加速器质谱分析、核分析质控、灾变环境、稀土生态环境、有机毒物及大气环境。
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     ORGANIC FOOD
     有机食品,你吃过了吗?
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     Studies on Bioassay Methods for Aquatic Environmental Toxin Organic Pollutants
     水环境中有毒有机污染物的生物毒性测试方法研究
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     Phytopathogenic Toxin
     植物病原毒素
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     Organic Peroxides
     有机过氧化物
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     Cholera toxin
     霍乱毒素
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The main progress made in the past two years in the major project of NSFC entitled "Study on modern nuclear analysis techniques and their applications in some environmental problems" is outlined, including molecular activation analysis, scanning proton microscopy, high-performance X-ray analysis, accelerator mass-spectroscopy, quality assurance of nuclear analysis, catastrophic environment, rare earth element ecosystem, organic toxin and atmospheric environment.

概述国家自然科学基金重大项目“现代核分析技术应用研究及其在若干环境问题中的应用研究”两年来的主要进展,包括分子活化分析、扫描质子微探针、高性能X射线分析、加速器质谱分析、核分析质控、灾变环境、稀土生态环境、有机毒物及大气环境。

This article demonstrates the application of artficial neural network in multi component analysis.Parameters were obtained after the BP network was trained with large amount of simulated data.Five organic toxins whose FTIR spectra are strongly overlapped were used to make the multi component system.The relative standard deviation(RSD%),the percent standard error of prediction samples(SEP%) and the percent standard error of calibration samples(SEC%) were used for evaluating the ability of the neural network....

This article demonstrates the application of artficial neural network in multi component analysis.Parameters were obtained after the BP network was trained with large amount of simulated data.Five organic toxins whose FTIR spectra are strongly overlapped were used to make the multi component system.The relative standard deviation(RSD%),the percent standard error of prediction samples(SEP%) and the percent standard error of calibration samples(SEC%) were used for evaluating the ability of the neural network.

介绍了人工神经网络在非线性多组分校准中的应用。所用三层神经网络由反向传播算法来训练。采用大量模拟数据训练神经网络 ,得到了一系列优化参数。选择红外谱图严重重叠的五种大气有机毒物作为多组分体系。相对标准误差 (RSD % )、百分标准预测误差 (SEP % )和百分标准校准误差 (SEC % )被用于衡量神经网络的性能。

 
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