@article {64860,
	title = {Design of a Selective Smart Gas Sensor Based on ANN-FL Hybrid Modeling, ISSN e-ISSN 2077-6772 / 2306-4277},
	journal = {Journal of Nano- and Electronic PhysicsJournal of Nano- and Electronic Physics},
	volume = {volume 10},
	year = {2018},
	month = {2018},
	pages = {pp 06011-06016},
	abstract = {The selectivity is one of the main challenges to develop a gas sensor, the good chemical species detection in a gaseous mixture decreasing the missed detections. The present paper proposes a new solution for gas sensor selectivity based on artificial neural networks (ANNs) and fuzzy logic (FL) algorithm. We first use ANNs to develop a gas sensor model in order to accurately express its behavior. In a second step, the FL and Matlab environment are used to create a database for a selective model, where the response of this one only depends on one chemical species. Analytical models for the gas sensor and its selective model are implemented into a Performance Simulation Program with Integrated Circuit Emphasis (PSPICE) simulator as an electrical circuit in order to prove the similarity of the analytical model output with that of the MQ-9 gas sensor where the output of the selective model only depends on one gas. Our results indicate the capability of the ANN-FL hybrid modeling for an accurate sensing analysis.},
	author = {Kouda, S. and Dendouga Abdelghani and Barra, S. and T. Bendib}
}
