Classification and identification of soot source with principal component analysis and back-propagation neural network-Reference-Cited by-同舟云学术

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Classification and identification of soot source with principal component analysis and back-propagation neural network

Published:2013-07-10 Issue:2 Volume:46 Page:224-233
ISSN:0045-0618
Container-title:Australian Journal of Forensic Sciences
language:en
Short-container-title:Australian Journal of Forensic Sciences

Author:

Zong Ruowen¹²,Zhi Youran¹,Yao Bin¹,Gao Jiaxin¹,Stec Anna A.³

Affiliation:

1. University of Science and Technology of China, State Key Laboratory of Fire Science,, Hefei, China.

2. Suzhou Institute for Advanced Study, University of Science and Technology of China, Suzhou Key Laboratory of Urban Public Safety,, Suzhou, China.

3. University of Central Lancashire, Preston, Lancashire, UK.

Publisher

Informa UK Limited

Subject

Pathology and Forensic Medicine

Link

https://www.tandfonline.com/doi/pdf/10.1080/00450618.2013.818711

Reference16 articles.

1. Soot volume fraction measurement in low-pressure methane flames by combining laser-induced incandescence and cavity ring-down spectroscopy: Effect of pressure on soot formation

2. Fire investigation and ignitable liquid residue analysis—A review: 2001–2007

3. ASTM standards for fire debris analysis: a review

4. Soot as an Indicator in Fire Investigations: Physical and Chemical Analyses

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