摘要
尝试将模糊神经网络(FNN)应用到消防系统中,利用FNN对火灾信号进行处理,使其不仅能有效降低消防系统的漏报警、误报警率,而且还可以适应各种不同的环境和工作条件,从而真正实现消防系统的自适应。该方法结合了神经网络和模糊逻辑的优点,弥补不足,优势互补,具有很大的优越性。将此算法转化为C语言代码应用到测试系统中,系统在降低误报警、漏报警方面有着明显改善。
This article attempts to apply FNN to the fire detection system,using the FNN to deal with the signal of fire,so that it can not only reduce the missing alarm rate and the false alarm rate,but also adapt to the different environments,different working conditions,and get the goal of Self-Adaptive of the fire fighting system truly.This method owns the advantages of both neural networks and fuzzy logic,and let them complement the deficiency of each other,so it has great superiority.Experimental results show that using this algorithm to the testing system after it is translated into C code,and the system has been obviously improved in reducing false-alarm and missing-alarm.
出处
《西南科技大学学报》
CAS
2011年第1期64-67,共4页
Journal of Southwest University of Science and Technology
基金
西南科技大学研究生创新基金(项目编号:09ycjj10)
关键词
神经网络
模糊逻辑
自适应
消防系统
Neural network
Fuzzy logic
Self-Adaptive
Fire fighting system
