Proceedings of the 2014 International Conference on Mechatronics, Control and Electronic Engineering

Towards a Fire Alarm Model Based on Variable Learning Rate Algorithm with Weight Factor

Authors
Wei Wang, Liping Yang, Lei Xu
Corresponding Author
Wei Wang
Available Online March 2014.
DOI
https://doi.org/10.2991/mce-14.2014.22How to use a DOI?
Keywords
fire alarm; neural network; variable learning rate; weight factor
Abstract
Fire alarm with Neural Network (NN) can learn knowledge from multiple sensor data fusion. By adjusting network weight, more stable fire alarm can be achieved. Classic BP NN is likely to fall into local minimum. To address this problem, a Variable Learning Rate Algorithm with Weight Factor (VLRA-BP) was proposed and introduced into automatic intelligent decision in fire alarm. The model with VLRA-BP algorithm uses temperature and smoke sensors to perform intelligent information transformation, so as to achieve target of timely alarming and decrease system false alarm rate. Simulation experiment result shows that system accuracy and average error can effectively monitor simulated fire scene and forecast fire.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
2014 International Conference on Mechatronics, Control and Electronic Engineering (MCE-14)
Part of series
Advances in Intelligent Systems Research
Publication Date
March 2014
ISBN
978-94-62520-31-8
ISSN
1951-6851
DOI
https://doi.org/10.2991/mce-14.2014.22How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Wei Wang
AU  - Liping Yang
AU  - Lei Xu
PY  - 2014/03
DA  - 2014/03
TI  - Towards a Fire Alarm Model Based on Variable Learning Rate Algorithm with Weight Factor
BT  - 2014 International Conference on Mechatronics, Control and Electronic Engineering (MCE-14)
PB  - Atlantis Press
SP  - 103
EP  - 106
SN  - 1951-6851
UR  - https://doi.org/10.2991/mce-14.2014.22
DO  - https://doi.org/10.2991/mce-14.2014.22
ID  - Wang2014/03
ER  -