基于模糊神经网络的火灾探测模型研究

Quanmin Guo, J. Dai, Jian Wang
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引用次数: 9

摘要

火灾信号探测是非结构性问题,难以用数学模型精确描述,增加了火灾探测的难度。针对火灾信号探测等特殊类型的信号探测技术,提出了一种基于模糊神经网络的火灾探测模型。本文描述了模型的设计方法,以及模型的学习算法。在标准的火灾试验室内,对中国国家标准试验火灾的阴燃火灾SH1和燃烧火灾SH3进行了模拟实验,该模型能够做出正确的判断。理论分析和仿真研究表明,该模型结合了模糊系统和神经网络的优点,提高了火灾探测的智能化,具有较强的环境适应能力。有效地解决了火灾报警中的误报和故障问题,提高了火灾探测的灵敏度。
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Study on Fire Detection Model Based on Fuzzy Neural Network
The fire signal detection is a non-structural problem and difficult to be precise described by mathematical model, which increase the difficulty of fire detection. According to the special type of signal detection technique such as fire signal detection, a fire detection model based on fuzzy-neural network is presented. This paper described the design method of the model, as well as its learning algorithm. In standard fire test rooms, simulation experiments were carried out for smoldering fire SH1 and flaming fire SH3 of the china national standard test fires, the model can make right judgment. Theory analysis and simulation study show that the model combines the advantages of fuzzy system and neural network, and improves the intelligence of fire detection, has a stronger ability to adapt the environment. It effectively solves the problems of mistake and failure in the fire alarm, and improves the sensibility of fire detection.
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