Near-infrared spectroscopy combined with deep convolutional generative adversarial network for prediction of component content in melt-cast explosive-Reference-Cited by-同舟云学术

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Near-infrared spectroscopy combined with deep convolutional generative adversarial network for prediction of component content in melt-cast explosive

Published:2024-04 Issue:4 Volume:52 Page:100379
ISSN:1872-2040
Container-title:Chinese Journal of Analytical Chemistry
language:en
Short-container-title:Chinese Journal of Analytical Chemistry

Author:

LIU Qiang,ZHAO Jiajing,DAN Baosong,SU Pengfei,ZHANG Gao

Publisher

Elsevier BV

Reference22 articles.

1. Direct observation of frictional ignition in dropped HMX-based polymer-bonded explosives;Parker;Combust Flame,2020

2. Review on melt-cast carrier explosives;Chen;Chin J Energ Mater,2020

3. Rapid determination of luteolin by a near-infrared spectroscopic method with ionic liquid adsorbent enrichment and CARS variable screening;He;J Instrumental Anal,2020

4. Fast detection of volatile fatty acids in biogas slurry using NIR spectroscopy combined with feature wavelength selection;Xu;Sci Total Environ,2023

5. Quantitative detection of components in polymer-bonded explosives through near-infrared spectroscopy with partial least square regression;Su;Acs Omega,2021

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