Simulation and Optimization of Genetic Algorithm-Artificial Neural Network Based Air Quality Estimator

shirish PANDEY


In this work an intelligent model for estimation of the concentration of carbon monoxide in a polluted environment is developed. The results are validated using data collected from repository linked to University of California. The data records are over the duration of one year using E nose sensor placed in main city of Italy. The records are rectified and segmented at different length to extract the Base and Divergence Values features. An Artificial Neural Network Model (ANN) and another optimized Genetic Algorithm –Artificial Neural Network  based air quality estimation model is developed to get a best performance network.


Artificial Neural Network Genetic Algorithm



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