文章基本信息

标题：MODELING OF AMBIENT FOR SOx AND NOx POLLUTANTS THROUGH ARTIFICAL NEURAL NETWORK IN INDUSTRIAL AREA OF UJJAIN CITY
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作者：PRIYANKA YADAV ; ALKA SHRIVASTAVA ; ASHOK .K.SHARMA 等
期刊名称：Journal of Industrial Pollution Control
印刷版ISSN：0970-2083
出版年度：2014
卷号：30
期号：1
页码：49-52
语种：English
出版社：Research and Reviews
摘要：The aim of this study was the modeling of ambient air pollutants through ANN in industrial area of Ujjain city in India and the study was carried out on modeling of air pollutants like SOx and NOx, using Artificial Neural Network. The ANN system was run by giving the inputs of meteriological datas and giving the outputs of concentration of various pollutants and accordingly the estimation of Errors was done by this study. The monthly datas in year from 2009 -2012 of meteorological like Temperature, Humidity, wind pressure and rainfall and the pollutants concentration were collected from the State Pollution Control Board. The ANN system used as shown in Figure 1 analyse all these datas and find the error coming during the experiment. The study estimated the Mean Square Error(MSE) from the inputs and outputs which were given to ANN in the industrial area of Ujjain City in India was found satisfactory as in the range of 0.001-0.003. The results shown here are indications that the neural network techniques can be useful tool in the hands of practitioners of air quality management and prediction. The models studied in this study are easily implemented, and they can deliver prediction in real time, unlike other modeling techniques.
关键词：Artificial neural network; Sulfur oxides; Nitrogen oxides; Mean square error