DocumentCode :
2172811
Title :
Intelligent classification strategy for flammable-gases base on BP neural network
Author :
Zhang, Chenchen ; Qi, Jianling
Author_Institution :
Dept. of Inf. Eng., China Univ. Of Geosci. Beijng, Beijing, China
fYear :
2011
fDate :
9-11 Sept. 2011
Firstpage :
3776
Lastpage :
3779
Abstract :
In the chemical and industrial field, the technology of detecting flammable or poisonous gases had always been important for product-safety control. Since the most of the work environment is complex and the gas always is complicated mixture, the precision of detection is rather low. IF the advanced pattern recognition and classification technology can be used in this field, we can effectively improve the detection accuracy. This paper firstly introduce the basics knowledge of BP neural network, then use MATLAB neural network toolbox to build network models and used experimental data to train the net. The simulation results show the network´s performance is good.
Keywords :
backpropagation; chemical variables measurement; gas sensors; pattern classification; safety; sensor arrays; signal classification; BP neural network; MATLAB neural network toolbox; adaptive learning; catalytic combustion gas sensor array; chemical field; flammable gas detection; industrial field; intelligent classification strategy; network model; pattern classification; pattern recognition; poisonous gas detection; product-safety control; Artificial neural networks; Biological neural networks; Mathematical model; Neurons; Training; Transfer functions; Artificial Neural Networks Back Propagation Algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronics, Communications and Control (ICECC), 2011 International Conference on
Conference_Location :
Ningbo
Print_ISBN :
978-1-4577-0320-1
Type :
conf
DOI :
10.1109/ICECC.2011.6066460
Filename :
6066460
Link To Document :
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