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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Quanmin Guo Junjie Dai Jian Wang |
| Copyright Year | 2010 |
| Abstract | 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. |
| Starting Page | 1 |
| Ending Page | 4 |
| File Size | 341777 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424458721 |
| e-ISBN | 9781424458745 |
| DOI | 10.1109/IWISA.2010.5473248 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-05-22 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Analytical models Intelligent networks Design methodology Neural networks Fires Fuzzy neural networks Mathematical model Signal detection Testing Fuzzy systems |
| Content Type | Text |
| Resource Type | Article |
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