Neural Network Model for Short Term Prediction of PM10 Pollution in Ahvaz City

Air pollution of cities is one of the most intricate environment al hazaeds that is a serious threat for health, hygiene and environment. Extensive studies show the potential effects of air pollution on human health, was including increased mortality, increased hospital treatments, especially changes in cardiopulmonary function- vascular. Particulate is one of six polluter that is very dangerous and have irreparable damage to the human body. This polluter are formed of substances such as acids, metals and dust.PM10 is one of the matter particulate which could cause severe air pollution. PM10 are known to particulate 10 microns and are formed from combination of nitrogen oxide and sulfur dioxide in the atmosphere. According to World Health Organization, Ahwaz with an annual average of 372 μg/m^3 of PM10 has acquired the most polluted city in first place in 1100 the city in the world. Therefore in this study with using data from the maximum pollution PM10 in series 24 hourly, were used for the to predict this polluter. A network with time delay and LMS learning algorithm is designed and were predicted the polluter concentrations for October 2011.