Modeling and interpretation of responses from e-noses in the detection of gases in air (Contributo in atti di convegno)

Type

• Contributo in atti di convegno (Classe)
• Prodotto della ricerca (Classe)

Label

• Modeling and interpretation of responses from e-noses in the detection of gases in air (Contributo in atti di convegno) (literal)

Anno

• 2006-01-01T00:00:00+01:00 (literal)

Alternative label

• E. Ferrari, A. Ridi, M. Muselli (2006)
  Modeling and interpretation of responses from e-noses in the detection of gases in air
  in 11th International Meeting on Chemical Sensors (IMCS 11), Brescia, Italy, 16-19 July 2006
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• E. Ferrari, A. Ridi, M. Muselli (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url

• http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.134.1334&rep=rep1&type=pdf (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume

• Proceedings of the 11th International Meeting on Chemical Sensors (IMCS 11) (literal)

Note

• Google Scholar (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

• E. Ferrari, M. Muselli: CNR-IEIIT, Genova, Italy; A. Ridi: Horizon, Srl (literal)

Titolo

• Modeling and interpretation of responses from e-noses in the detection of gases in air (literal)

Abstract

• A new method, called Shadow Clustering (SC), to build an e-nose net is proposed. The method, which is very appropriate to monitoring applications due its cheapness and low consumption, is applied to an array of sensors composed by a TiO2 thin film. A model describing the e-nose behavior is built and it is used to simulate the detection process of a mixture of Ethanol, Methanol and Propanol. The results obtained by the new method are compared with those obtained by other wellknown learning techniques: Neural Networks and Regression Trees. (literal)

Prodotto di

• Machine Learning Techniques for Modeling and Growing up (ICT.P11.008.001) (Modulo)
• Institute of Electronics, Computer and Telecommunication Engineering (IEIIT) (Istituto)

Autore CNR

• ENRICO FERRARI (Persona)
• MARCO MUSELLI (Unità di personale interno)

Incoming links:

Prodotto

• Institute of Electronics, Computer and Telecommunication Engineering (IEIIT) (Istituto)
• Machine Learning Techniques for Modeling and Growing up (ICT.P11.008.001) (Modulo)

Autore CNR di

• MARCO MUSELLI (Unità di personale interno)
• ENRICO FERRARI (Persona)