Title
Performance Analysis Of Neuro Genetic Algorithm Applied On Detecting Proportion Of Components In Manhole Gas Mixture
Abstract
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.
Year
DOI
Venue
2012
10.5121/ijaia.2012.3406
International Journal of Artificial Intelligence & Applications
Field
DocType
Volume
Computer science,Sensor array,Methane,Artificial intelligence,Artificial neural network,Pattern recognition problem,Carbon monoxide,Multiple sensors,Genetic algorithm,Machine learning
Journal
abs/1209.1048
Citations 
PageRank 
References 
4
0.52
1
Authors
3
Name
Order
Citations
PageRank
Varun Kumar Ojha1329.25
Paramartha Dutta210020.77
H. Saha3468.61