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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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