Machine Learning Applied to the Sensitivity of Explosives

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  • Presentation type: Apresentação de Pôster / Poster Communications
  • Track: Computational Chemistry
  • Keywords: Explosives; Machine Learning;

Authors:

  • 1 Instituto Militar de Engenharia

Machine Learning Applied to the Sensitivity of Explosives

Rômulo Dias da Rocha

Instituto Militar de Engenharia

Abstract

Reduced time and risk by experimenting with explosives

Sensitivity values of nitroaromatic explosives were determined using Machine
Learning algorithms

The sensitivity values were predicted with a mean square error (RMSE) of 28.9 cm and 29.6 cm for the Random Forest and Extra Trees algorithms, respectively.

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Author

Itamar Borges

Obrigado Guilherme ! Seu comentário é totalmente pertinente assim com a descrição do processo mecânico envolvido  - um provável passo além. O que fizemos aqui foi nos fixar apenas em propriedades moleculares oriundas da partição de densidade molecular de carga descritas por multipolos elétricos centrados nos átomos. Obrigado pela sugestão, um grande abraço