@article{CHENG2011, 
author = {Caixia CHENG and Fuchun SUN and Xinquan ZHOU},
title = {One Fire Detection Method Using Neural Networks},
year = {2011},
journal = {Tsinghua Science and Technology},
volume = {16},
number = {1},
pages = {31-35},
keywords = {fire detection, neural network, multi-sensor information fusion, simulation},
url = {https://www.sciopen.com/article/10.1016/S1007-0214(11)70005-0},
doi = {10.1016/S1007-0214(11)70005-0},
abstract = {A neural network fire detection method was developed using detection information for temperature, smoke density, and CO concentration to determine the probability of three representative fire conditions. The method overcomes the shortcomings of domestic fire alarm systems using single sensor information. Test results show that the identification error rates for fires, smoldering fires, and no fire are less than 5%, which greatly reduces leak-check rates and false alarms. This neural network fire alarm system can fuse a variety of sensor data and improve the ability of systems to adapt in the environment and accurately predict fires, which has great significance for life and property safety.}
}