基于典型特征参数的飞机货柜的火灾检测算法研究

Haibin Wang1,2, Hongjuan Ge1, Zhihui Zhang2

  • 1Civil Aviation College, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.

PubMed
概括

这项研究通过优化烟雾传感器的基因算法和使用PSO-LSTM的CO度补偿来提高飞机货物火灾检测的准确性. 改进的BP-AdaBoost模型在复杂的场景中实现高精度的火灾识别.

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