@article{ref1,
title="Research on fire-detection algorithm for airplane cargo compartment based on typical characteristic parameters",
journal="Sensors (Basel)",
year="2023",
author="Wang, Haibin and Ge, Hongjuan and Zhang, Zhihui and Bu, Zonghao",
volume="23",
number="21",
pages="e8797-e8797",
abstract="To clarify the reasons for inaccurate fire detection in aircraft cargo holds, this article depicts research from the perspective of a single type of sensor detection. In terms of fire smoke, we select dual-wavelength photoelectric smoke sensors for fire-data collection and a genetic algorithm to optimize the classification and detection of random forest fires. From the perspective of fire CO concentration, we use PSO-LSTM to train a CO concentration compensation model to reduce sensor measurement errors. Research is then conducted from the perspective of various types of sensor detection, using the improved BP-AdaBoost algorithm to train a fire-detection model and achieve the high-precision identification of complex environments and fire situations.<p /> <p>Language: en</p>",
language="en",
issn="1424-8220",
doi="10.3390/s23218797",
url="http://dx.doi.org/10.3390/s23218797"
}