Proceedings of the 3rd International Conference on Advances in Energy and Environmental Science 2015

The evaluation system of green mining based on quantum immune algorithm and neural network

Authors
Dongwang Zhong, Linna Li
Corresponding Author
Dongwang Zhong
Available Online July 2015.
DOI
https://doi.org/10.2991/icaees-15.2015.73How to use a DOI?
Keywords
green mine; quantum algorithms; immune algorithm; neural network
Abstract

The construction of green mine represents the development and utilization level of mineral resources and the sustainable development potential. In view of the characteristics of the large index system and complex evaluation process of green mining, a kind of BP neural network algorithm based on quantum immune apply to green mining evaluation.Because the algorithm combines the space search advantages of immune optimization and those of quantum optimization ,it can make the convergence of the neural network training faster, and avoid falling into local optimum.

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 3rd International Conference on Advances in Energy and Environmental Science 2015
Series
Advances in Engineering Research
Publication Date
July 2015
ISBN
978-94-6252-130-8
ISSN
2352-5401
DOI
https://doi.org/10.2991/icaees-15.2015.73How 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  - Dongwang Zhong
AU  - Linna Li
PY  - 2015/07
DA  - 2015/07
TI  - The evaluation system of green mining based on quantum immune algorithm and neural network
BT  - Proceedings of the 3rd International Conference on Advances in Energy and Environmental Science 2015
PB  - Atlantis Press
SP  - 389
EP  - 394
SN  - 2352-5401
UR  - https://doi.org/10.2991/icaees-15.2015.73
DO  - https://doi.org/10.2991/icaees-15.2015.73
ID  - Zhong2015/07
ER  -