Predicting the Impact Sensitivity of Explosive Molecules Using Neuromimetic Networks
作者:
H. Nefati,
B. Diawara,
J.J. Legendre,
期刊:
SAR and QSAR in Environmental Research
(Taylor Available online 1993)
卷期:
Volume 1,
issue 2-3
页码: 131-136
ISSN:1062-936X
年代: 1993
DOI:10.1080/10629369308028824
出版商: Taylor & Francis Group
关键词: explosives;sensitivity;impact prediction;neural networks
数据来源: Taylor
摘要:
A new method for predicting the impact sensitivity of explosive molecules is presented. This method makes use of a network of formal neurons. The experiment uses 124 molecules belonging to different families. The molecular descriptors taken into account are the molecule's oxygen balance and the enumeration of certain groups. The results obtained are satisfactory: 80% of the molecules are correctly classed on a scale of four sensitivities. Comparison with a multivariate linear regression analysis gives a slight advantage to the neural network method.
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