The article presents performance analysis of a real valued neuro genetic
algorithm applied for the detection of proportion of the gases found in manhole
gas mixture. The neural network (NN) trained using genetic algorithm (GA) leads
to concept of neuro genetic algorithm, which is used for implementing an
intelligent sensory system for the detection of component gases present in
manhole gas mixture Usually a manhole gas mixture contains several toxic gases
like Hydrogen Sulfide, Ammonia, Methane, Carbon Dioxide, Nitrogen Oxide, and
Carbon Monoxide. A semiconductor based gas sensor array used for sensing
manhole gas components is an integral part of the proposed intelligent system.
It consists of many sensor elements, where each sensor element is responsible
for sensing particular gas component. Multiple sensors of different gases used
for detecting gas mixture of multiple gases, results in cross-sensitivity. The
cross-sensitivity is a major issue and the problem is viewed as pattern
recognition problem. The objective of this article is to present performance
analysis of the real valued neuro genetic algorithm which is applied for
multiple gas detection.Comment: 16 pages,11 figure