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2004

Adaptive Wavelet Neural Network for Prediction of Hourly NOx and NO2 Concentrations

9 years 19 days ago
Adaptive Wavelet Neural Network for Prediction of Hourly NOx and NO2 Concentrations
Adaptive neural network is a powerful tool for prediction of air pollution abatement scenarios. But it is often difficult to avoid overfit during the training of adaptive neural network. In this paper, based on the wavelet theory, a new algorithm is proposed to improve the generalization of adaptive neural network during on-line learning. The new algorithm trains adaptive wavelet neural network to model hourly NOx and NO2 concentrations of variance of emission sources. Results show that the new algorithm improves the generalization and the convergence velocity of adaptive wavelet neural network during on-line learning. The simulations also illustrate that adaptive wavelet neural network is capable of resolving variance of emission sources.
Zhiguo Zhang, Ye San
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2004
Where WSC
Authors Zhiguo Zhang, Ye San
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