Recognition of gasoline in fire debris using machine learning: Part I, application of random forest, gradient boosting, support vector machine, and naïve bayes-Reference-Cited by-同舟云学术

Recognition of gasoline in fire debris using machine learning: Part I, application of random forest, gradient boosting, support vector machine, and naïve bayes

Published:2022-02 Issue: Volume:331 Page:111146
ISSN:0379-0738
Container-title:Forensic Science International
language:en
Short-container-title:Forensic Science International

Author:

Bogdal C.,Schellenberg R.,Höpli O.,Bovens M.,Lory M.

Publisher

Elsevier BV

Subject

Pathology and Forensic Medicine,Law

Reference20 articles.

1. Analysis and Interpretation of Fire Scene Evidence;Almirall,2016

2. Identifying Ignitable Liquids in Fire Debris: A Guideline for Forensic Experts;Hendrikse,2016

3. E1618-19, ASTM. Standard test method for ignitable liquid residues in extracts from fire debris samples by gas chromatography - mass spectrometry, 2019. 〈https://www.astm.org/Standards/E1618.htm〉.

4. Chemometrics in forensic chemistry — part I: Implications to the forensic workflow;Bovens;Forensic Sci. Int.,2019

5. Chemometrics in forensic chemistry – Part II: Standardized applications – three examples involving illicit drugs;Salonen;Forensic Sci. Int.,2020

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