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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 554-556Detection of High Energy Materials Using Support...

Detection of High Energy Materials Using Support Vector Classification

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Abstract:

Based on the element contents of N, O, H and C of objects detected by γ-ray resonance, support vector classification (SVC) method was used to construct the model for distinguishing high energy materials (HEMs) from ordinary ones. It was found that the accuracy of prediction was 95.9% based on the leave-one-out cross validation (LOOCV) test. The results indicated that the performance of SVC model is good enough to detect HEMs in the presence of ordinary materials for the purpose of security checking.

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Advances in Chemistry Research II

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Periodical:

Advanced Materials Research (Volumes 554-556)

Pages:

1628-1631

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.554-556.1628

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Online since:

July 2012

Authors:

Tian Hong Gu, Wei Lv, Xia Shao, Wen Cong Lu

Keywords:

High Energy Materials, Pattern Recognition, Security Check, Support Vector Classification

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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