Prediction of Ozone Formation Based on Neural Network and Stochastic Method 


Vol. 7,  No. 2, pp. 119-126, Jun.  2001


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  Abstract

The prediction of ozone formation was studied using the neural network and the stochastic method. Parameter estimation method and artificial neural network(ANN) method were employed in the stochastic scheme. In the parameter estimation method, extended least squares(ELS) method and recursive maximum likelihood(RML) were used to achieve the real time parameter estimation. Autoregressive moving average model with external input(ARMAX) was used as the ozone formation model for the parameter estimation method. ANN with 3 layers was also tested to predict the ozone formation. To demonstrate the performance of the ozone formation prediction schemes used in this work, the prediction results of ozone formation were compared with the real data. From the comparison it was found that the prediction schemes based on the parameter estimation method and ANN method show an acceptable accuracy with limited prediction horizon.

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  Cite this article

[IEEE Style]

O. SC and Y. YK, "Prediction of Ozone Formation Based on Neural Network and Stochastic Method," Clean Technology, vol. 7, no. 2, pp. 119-126, 2001. DOI: .

[ACM Style]

Oh SC and Yeo YK. 2001. Prediction of Ozone Formation Based on Neural Network and Stochastic Method. Clean Technology, 7, 2, (2001), 119-126. DOI: .

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pISSN : 1598 - 9712
eISSN : 2288 - 0690

한국연구재단 등재학술지