Title :
Pattern recognition of gases of petroleum based on RBF model
Author :
Barbosa, Maria Silva Santos ; Ludermir, Teresa B. ; Santos, Francisco Luiz dos ; Dos Santos, Fernando Leandro ; De Souza, Jose Edson Gomes ; De Melo, Celso Pinto
Author_Institution :
UESB, Bahia, Brazil
Abstract :
In the case of aerial accident spreading out dangerous gases into the atmosphere, an instrument called electronic nose can warn about the beginning of petroleum derived leaks. In this paper we present the architecture of the neural network for pattern recognition of gases of petroleum based on an RBF model. With this model we analyzed the pattern recognition of five gases: ethane, methane, propane, butane and carbon monoxide, separated in three classes of problems.
Keywords :
computerised monitoring; gas sensors; leak detection; pattern recognition; petroleum industry; radial basis function networks; RBF neural network; butane; carbon monoxide; electronic nose; ethane; gas leakage detection; methane; pattern recognition; petroleum gas recognition; petroleum industry; propane; Accidents; Atmosphere; Atmospheric modeling; Electronic noses; Gases; Instruments; Neural networks; Pattern analysis; Pattern recognition; Petroleum;
Conference_Titel :
Neural Networks, 2002. SBRN 2002. Proceedings. VII Brazilian Symposium on
Print_ISBN :
0-7695-1709-9
DOI :
10.1109/SBRN.2002.1181445
