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Preliminary results of investigations into the use of artificial neural networks for discriminating gas chromatograph mass spectra of remote samples

机译：研究使用人工神经网络鉴别远程样品的气相色谱质谱的初步结果

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Neural networks trained using mass spectra data from the National Institute of Standards and Technology (NIST) are studied. The investigations also included sample data from the gas chromatograph mass spectrometer (GCMS) instrument aboard the Viking Lander, obtained from the National Space Science Data Center. The work performed to data and the preliminary results from the training and testing of neural networks are described. These preliminary results are presented for the purpose of determining the viability of applying artificial neural networks in discriminating mass spectra samples from remote instrumentation such as the Mars Rover Sample Return Mission and the Cassini Probe.

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作者
Geller, Harold A.; Norris, Eugene; Warnock, Archibald, III;
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年度 1991
页码 1-10
总页数 10
原文格式 PDF
正文语种 eng
中图分类工业技术;
关键词
ARTIFICIAL INTELLIGENCE; DISCRIMINATION; GAS CHROMATOGRAPHY; MASS SPECTRA; NEURAL NETS; PATTERN RECOGNITION; CASSINI MISSION; MARINER MARK 2 SPACECRAFT; MARS SAMPLE RETURN MISSIONS; SPACE PROBES; SPECTRUM ANALYSIS; VIKING LANDER SPACECRAFT;

机译：人工智能;歧视;气相色谱法;质量光谱;神经网络;模式识别; CassINI mIssION; maRINER maRK 2 spaCECRaFT; maRs sampLE返回任务;空间探测器;光谱分析; VIKING LaNDER spaCECRaFT;

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Preliminary results of investigations into the use of artificial neural networks for discriminating gas chromatograph mass spectra of remote samples

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