Artificial Neural Network for Environmental Air Emissions Prediction Systems

Artificial neural network ANN is an appropriate tool for predestining the different relationships across many scientific researches. Air emissions prediction is an effective method of securing public health by revealing the imminent danger of air pollutants. So far, the existing methods of air emissions concentration prediction became useless on long-term dependencies, and most neglect spatial correlations. In this study, an artificial neural network model, which also takes into account the spatial-temporal variable, is proposed for prediction of air emission. The ANN was used in order to take into account the historical data, auxiliary data such as environmental quality and weather conditions. Evaluation of the results revealed that the developed ANN model appears to be an appropriate tool in predicting environmental air emissions. The data were collected from 12 air quality-monitoring stations from a random county in Romania. The proposed model performed well and presented a relative error varies from 0 to 4.7%.