Proceedings of the 2015 International Conference on Electrical, Electronics and Mechatronics

Prediction of Explosion Heat of Aluminized Explosive Based on Artificial Neural Network

Authors
Xin Tian, Yonggang Liu, Yueqiang Jiang
Corresponding Author
Xin Tian
Available Online December 2015.
DOI
10.2991/iceem-15.2015.20How to use a DOI?
Keywords
aluminized explosive; explosion heat; artificial neural network
Abstract

In this study, a three-layer artificial neural network(ANN) model was constructed to predict the explosion heat (Q) of aluminized explosive. Elemental composition was employed as input descriptors and explosion heat was used as output. The dataset of 24 aluminized explosives was randomly divided into a training set (17) and a prediction set (7). After optimized by adjusting various parameters, the optimal condition of the neural network was obtained. Simulated with the final optimum neural network, calculated explosion heat shows good agreement with experimental values. It is shown here ANN is able to produce accurate predictions of the explosion heat of aluminized explosive.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2015 International Conference on Electrical, Electronics and Mechatronics
Series
Advances in Engineering Research
Publication Date
December 2015
ISBN
10.2991/iceem-15.2015.20
ISSN
2352-5401
DOI
10.2991/iceem-15.2015.20How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Xin Tian
AU  - Yonggang Liu
AU  - Yueqiang Jiang
PY  - 2015/12
DA  - 2015/12
TI  - Prediction of Explosion Heat of Aluminized Explosive Based on Artificial Neural Network
BT  - Proceedings of the 2015 International Conference on Electrical, Electronics and Mechatronics
PB  - Atlantis Press
SP  - 80
EP  - 82
SN  - 2352-5401
UR  - https://doi.org/10.2991/iceem-15.2015.20
DO  - 10.2991/iceem-15.2015.20
ID  - Tian2015/12
ER  -