Fuzzy neural networks for gas sensing

Vlachos, D; Avaritsiotis, J

dc.contributor.author	Vlachos, D	en
dc.contributor.author	Avaritsiotis, J	en
dc.date.accessioned	2014-03-01T01:11:58Z
dc.date.available	2014-03-01T01:11:58Z
dc.date.issued	1996	en
dc.identifier.issn	0925-4005	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/11894
dc.subject	Fuzzy neural network	en
dc.subject	Gas sensors	en
dc.subject.classification	Chemistry, Analytical	en
dc.subject.classification	Electrochemistry	en
dc.subject.classification	Instruments & Instrumentation	en
dc.title	Fuzzy neural networks for gas sensing	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/0925-4005(96)01917-X	en
heal.identifier.secondary	http://dx.doi.org/10.1016/0925-4005(96)01917-X	en
heal.language	English	en
heal.publicationDate	1996	en
heal.abstract	The implementation of a fuzzy neural network with an array of tin oxide based gas sensors for both quantitative and qualitative gas sensing is demonstrated. The architecture of the system is presented with some references to the general theory of fuzzy sets and fuzzy calculus. Experimental results are presented in the case of gas identification between CO, ethanol and methane and in the case of CO detection in different levels of relative humidity. Finally the effect of network parameters to the functionality of the system is discussed, especially in the case of functions evaluating the fuzzy AND and OR operations.	en
heal.publisher	ELSEVIER SCIENCE SA LAUSANNE	en
heal.journalName	Sensors and Actuators, B: Chemical	en
dc.identifier.doi	10.1016/0925-4005(96)01917-X	en
dc.identifier.isi	ISI:A1996VK20100014	en
dc.identifier.volume	33	en
dc.identifier.issue	1-3	en
dc.identifier.spage	77	en
dc.identifier.epage	82	en