Nonlinear time series prediction of O-3 concentration in Istanbul

In this study, local prediction method is used to predict O-3 concentration over Istanbul City at different stations. Observed single-variable time se ries data are used to reconstruct the attractor in the multidimensional spa ce. Subsequently, the dynamic model to generate the attractor is estimated and the change of the trajectory is predicted by a polynomial approximation . In other words, the dynamics of system are described step by step locally in the phase space. Parameters needed to reconstruct the phase space are d elay time and embedding dimension. The delay time is chosen as the lag time at which the autocorrelation function first reaches to zero. The embedding dimension is obtained from the plot of correlation coefficient vs. embeddi ng dimension. This embedding dimension corresponds to minimum relative erro r between observed and predicted values. The relative error between model o utputs and observations is within the practically acceptable limits pointin g out that O-3 concentration is governed by a deterministic chaotic system. (C) 2000 Elsevier Science Ltd. All rights reserved.