Souhil KOUDA
| dc.contributor.author | Souhil, KOUDA | |
| dc.date.accessioned | 2019-06-25T09:04:35Z | |
| dc.date.available | 2019-06-25T09:04:35Z | |
| dc.date.issued | 2018 | |
| dc.description.abstract | In this paper, we propose the modeling of an industrial gas sensor “MQ-9”, where our modeling is based on ANNs “artificial neural networks”. The gas sensor model, obtained, operated under a dynamic environment and expresses accurately the MQ-9 gas sensor behavior. Accordingly, it takes into account the nonlinearity and the cross sensitivity in gas selectivity, temperature and humidity. This model is implemented into PSPICE “performance simulation program with integrated circuit emphasis” simulator as an electrical circuit in order to prove the similarity of the analytical model output with that of the MQ-9 gas sensor. | en_US |
| dc.identifier.uri | http://dspace.univ-msila.dz:8080//xmlui/handle/123456789/14469 | |
| dc.language.iso | en | en_US |
| dc.publisher | Université de M'sila | en_US |
| dc.subject | Analytical model, artificial neural networks, cross sensitivity, gas sensor, PSPIC | en_US |
| dc.title | Souhil KOUDA | en_US |
| dc.type | Article | en_US |