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@article{Singh_Dewangan_2014, title={Use of artificial neuralnetwork for modeling of pollutent}, volume={6}, url={https://www.updatepublishing.com/journal/index.php/rrst/article/view/1159}, abstractNote={ <p class="MsoNormal" style="text-align: justify;">Artificial Neural Networks (ANN) is implemented for predicting air quality. The models, in general, could predict air quality patterns with modest accuracy However, ANNM model performed extremely well in comparison to other models for predicting annual data as well as daily data. Industry emits small amounts of nitrogen oxides to the environment. As the regulatory authorities demand the reduction of the resulting air pollution, existing plants are looking for economical ways to comply with this demand. Several Artificial Neural Networks models were trained from several months of operating plant data to predict the NOx concentration in the tail gas, and their total amount emitted the environment. This paper describes the development of artificial neural network-based vehicular exhaust emission &amp; industrial models for predicting carbon monoxide concentrations at air quality control regions in the city of Raipur, India, viz. a typical traffic intersection.Which can work with limited number of data sets and are robust enough to handle data with noise and errors.The Artificial Neural Networks models gave small errors, 0.6% relative error on the nitrogen oxides concentration prediction. Thenitrogen oxides emission rate, especially the beneficial effect of cooling the absorbed gas and reticulating liquids in the absorption towers.</p> }, number={1}, journal={Recent Research in Science and Technology}, author={Singh, Monica and Dewangan, Vaibhav}, year={2014}, month={Aug.} }