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

Volume

3

fYear

2000

fDate

2000

Firstpage

1754

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on

Conference_Location

Hefei

Print_ISBN

0-7803-5995-X

Type

conf

DOI

10.1109/WCICA.2000.862774

Filename

862774