Application of Real Valued Neuro Genetic Algorithm in Detection of Components Present in Manhole Gas Mixture

  • Varun Kumar Ojha
  • Paramarta Dutta
  • Hiranmay Saha
  • Sugato Ghosh
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 166)


The article deals with the implementation of an Intelligent System for detection of components present in manhole gas mixture. The detection of manhole gas is important because the manhole gas mixture contain many poisonous gases namely Hydrogen Sulfide (H 2 S), Ammonia (NH 3), Methane (CH 4), Carbon Dioxide (CO 2), Nitrogen Oxide (NO x ), and Carbon Monoxide (CO). A short exposure to any of these components with human beings endangers their lives. A gas sensor array is used for recognition of multiple gases simultaneously. At an instance the manhole gas mixture may contain many hazardous gas components. So it is wise to use specific gas sensor for each gas component in the gas sensor array. Use of multiple gas sensors and presence of multiple gases together result a cross-sensitivity. We implement a real valued neuro genetic algorithm to unravel the multiple gas detection issue.


Cross-Sensitivity Gas Sensor Array Real Value Neuro Genetic Algorithm 


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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  • Varun Kumar Ojha
    • 1
  • Paramarta Dutta
    • 1
  • Hiranmay Saha
    • 2
  • Sugato Ghosh
    • 2
  1. 1.Department of Computer & System SciencesVisva BharatiSantiniketanIndia
  2. 2.Centre of Excellence for Green Energy & Sensors SystemBengal Engineering & Science UniversityHowrahIndia

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