Title :
Self-learning fuzzy neural network and its application to fire auto-detecting in fire protection systems
Author :
Shuangye, Chen ; Jikai, Yi ; Yingyan, Zhao
Author_Institution :
Dept. of Autom., Beijing Polytech. Univ., China
Abstract :
A fuzzy-neuro network architecture is proposed. An initial fuzzy knowledge base can be built by means of self-adaptive learning from historical data, fuzzy rules and system parameters can be optimized by online learning of the FNN via real-time data, which make the system possess distinguished adaptive features and self-learning capability. Taking fire auto-detecting in a fire protection system as application background, a series of experimental research has been carried out. Experimental results demonstrate the feasibility of the neuro-fuzzy system
Keywords :
fires; fuzzy neural nets; protection; unsupervised learning; adaptive features; fire auto-detecting; fire protection systems; fuzzy knowledge base; fuzzy-neuro network architecture; historical data; online learning; self-learning fuzzy neural network; Adaptive systems; Design automation; Fires; Fuzzy neural networks; Fuzzy systems; Intelligent networks; Logic; Neural networks; Protection; Real time systems;
Conference_Titel :
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Conference_Location :
Hefei
Print_ISBN :
0-7803-5995-X
DOI :
10.1109/WCICA.2000.862774
