基于模糊神经网络的火灾信号处理设计

本文针对传统智能建筑中火灾报警系统功能简单、定位困难且存在误报和漏报等问题，设计了一种基于模糊控制理论、人工神经网络的火灾安全报警系统。该系统依靠模糊控制理论提高了灵敏度，减少了误报率，并结合神经网络具有自学习功能的特点，提高了整个系统的智能化水平。作者阐述了火灾报警系统的设计原理，对模糊理论和几种神经网络模型进行了分析，并使用MATLAB软件对设计的算法进行了仿真分析。该系统达到了比较理想的效果。

Design of Fire Hazard Signal Processing Based on Fuzzy Neural Network

In allusion to the shortcomings of function is simple, positioning is difficult, false alarms and missed alarms existed in the fire 8larm system of traditional intelligent building, a kind of security alarm system for fire accidents based on fuzzy control theory and artificial neural network is designed in this paper. The system relies on fuzzy control theory to improve the sensitivity, reduce the false alarm rate, and combines the neural network＇s characteristic of having self-learning function to enhance the intelligent level of the overall system. The author elaborates the design principle, analyzes the fuzzy theory and the several different styles of neural net- work models and also makes the simulation analysis for the designed algorithms by using MATLAB software. The system achieved an ideal effect.