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Present  paper  endeavors  to develop ,predictive  artificial  neural network ,model for  forecasting  the mean monthly total ozone  concentration  over  Arosa,  Switzerland.  Single  hidden  layer  neural network  models  with variable number,of nodes have been developed and their performances,have been evaluated using the method,of least squares and error estimation. Their performances have been compared with multiple linear regression model. Ultimately, single-hidden-layer  model with  8  hidden  nodes have  been  identified as the ,best predictive model. Key words: Arosa, total ozone, single-hidden-layer, artificial neural network, multiple linear regression, forecast

Single hidden layer artificial neural network models versus multiple linear regression model in forecasting the time series of total ozone