Prediction and evaluation of tropospheric ozone concentration in Istanbul using artificial neural network modeling according to time parameter

In this paper, lower tropospheric ozone concentration was modeled using artificial neural networks (ANNs) according to 1 day, 3 days and 7 days time periods to determine best prediction period. In model formation, data that was taken from ozone measuring stations and Government Meteorology Works Office was daily averages of last 6 months of 2003 and first 6 months of 2004. Air pollutant parameters (6) and meteorological parameters (8) were used in ANN architecture for Anatolian and European sides of Istanbul separately. Correlation factor was determined to examine model effectiveness for each time period. Weekly average prediction model has been observed with highest correlation factor and three day's correlation factor was higher than daily's.