Proceedings of the First International Conference on Information Sciences, Machinery, Materials and Energy

Ventilation system reliability evaluation based on PNN neural network

Authors
Biao Wu, Yueping Qin
Corresponding Author
Biao Wu
Available Online July 2015.
DOI
10.2991/icismme-15.2015.150How to use a DOI?
Keywords
Ventilation system reliability; Probabilistic neural network (PNN); Evaluation method.
Abstract

In order to accurately and quickly identify the level of ventilation system reliability of coal mines, a new evaluation method based on Probabilistic neural network (PNN) was proposed in this paper. The design of structure of network, the rationale of evaluation algorithm and the performance of proposed method were discussed in detail. The case analysis indicated that the application of proposed method is feasible and reasonable and this evaluation method is easier and more practical. The research of this evaluation method could provide a new way of thinking for reliability judgment of the mine ventilation system.

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 First International Conference on Information Sciences, Machinery, Materials and Energy
Series
Advances in Intelligent Systems Research
Publication Date
July 2015
ISBN
978-94-62520-67-7
ISSN
1951-6851
DOI
10.2991/icismme-15.2015.150How 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  - Biao Wu
AU  - Yueping Qin
PY  - 2015/07
DA  - 2015/07
TI  - Ventilation system reliability evaluation based on PNN neural network
BT  - Proceedings of the First International Conference on Information Sciences, Machinery, Materials and Energy
PB  - Atlantis Press
SP  - 724
EP  - 728
SN  - 1951-6851
UR  - https://doi.org/10.2991/icismme-15.2015.150
DO  - 10.2991/icismme-15.2015.150
ID  - Wu2015/07
ER  -