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Artificial Neural Network Approach for Evaluation of Gas Sensor Array Responses

  • Iwona Rutkowska
  • Barbara Flisowska-Wiercik
  • Przemysław M. Szecówka
  • Andrzej Szczurek
Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 95)

Abstract

Neural processing was applied for evaluation of gas sensors responses. Thin layer type gas sensors based on TiO2 sensing film were fabricated using sol-gel technology. Several variants of these devices were obtained by different technology parameters. They were characterized by exposition to air containing various volatile organic compounds. Neural processing was applied for classification of compounds according to the chemical function group and number of carbon atoms in molecules. Different statistics of correct classification obtained for the two variants deliver significant knowledge about sensing mechanisms and quality of information that may be extracted from sensor responses.

Keywords

Sensor Array Neural Processing Neural Network Approach Diaphragm Pump Sensor Reaction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Iwona Rutkowska
    • 1
  • Barbara Flisowska-Wiercik
    • 2
  • Przemysław M. Szecówka
    • 3
  • Andrzej Szczurek
    • 2
  1. 1.Faculty of ChemistryWrocław University of TechnologyWrocławPoland
  2. 2.Faculty of Environmental EngineeringWrocław University of TechnologyWrocławPoland
  3. 3.Faculty of Microsystem Electronics and PhotonicsWrocław University of TechnologyWrocławPoland

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