Skip to Main content Skip to Navigation
Journal articles

Predicting the impact sensitivity of explosive molecules using neuromimetic networks

Abstract : 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.
Document type :
Journal articles
Complete list of metadatas

https://hal-ineris.archives-ouvertes.fr/ineris-00962536
Contributor : Gestionnaire Civs <>
Submitted on : Friday, March 21, 2014 - 1:26:38 PM
Last modification on : Friday, March 21, 2014 - 1:26:38 PM

Identifiers

Collections

Citation

H. Nefati, B. Diawara, J.J. Legendre. Predicting the impact sensitivity of explosive molecules using neuromimetic networks. SAR and QSAR in Environmental Research, Taylor & Francis, 1993, 1 (2-3), pp.131-136. ⟨ineris-00962536⟩

Share

Metrics

Record views

96