Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)

Compound Fire Detection Algorithm Based on Fuzzy Neural Network

Authors
Feng Yang, Na Qu, Chao Li
Corresponding Author
Feng Yang
Available Online June 2016.
DOI
10.2991/mecs-17.2017.133How to use a DOI?
Keywords
fire detection; fuzzy neural network; MATLAB simulation; fire parameters
Abstract

This paper proposes a fuzzy neural network fire detection algorithm to improve the accuracy of fire detection. Taking the temperature, smoke concentration and CO concentration as the input of the system, the fuzzy neural network is used to analyze the multi input signals. Fuzzy neural network combines the advantages of neural network in finding the optimal solution at high speed and fuzzy system in dealing with fuzzy information and using existing knowledge. The effectiveness of the algorithm is proved by simulation with MATLAB toolbox.

Copyright
© 2017, 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 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)
Series
Advances in Engineering Research
Publication Date
June 2016
ISBN
10.2991/mecs-17.2017.133
ISSN
2352-5401
DOI
10.2991/mecs-17.2017.133How to use a DOI?
Copyright
© 2017, 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  - Feng Yang
AU  - Na Qu
AU  - Chao Li
PY  - 2016/06
DA  - 2016/06
TI  - Compound Fire Detection Algorithm Based on Fuzzy Neural Network
BT  - Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017)
PB  - Atlantis Press
SP  - 187
EP  - 191
SN  - 2352-5401
UR  - https://doi.org/10.2991/mecs-17.2017.133
DO  - 10.2991/mecs-17.2017.133
ID  - Yang2016/06
ER  -