Artificial Neural Network to predict mean monthly total ozone in Arosa, Switzerland

Details Artificial Neural Network to predict mean monthly total ozone in Arosa, Switzerland Artificial Neural Network to predict mean monthly total ozone in Arosa, Switzerland

2006-08-17

arxiv.org/abs/nlin/0608043v1

Nonlinear Sciences

Adaptation and Self-Organizing Systems

22 pages, 14 figures

Scientific paper

10.1080/01431160701250440

Present study deals with the mean monthly total ozone time series over Arosa, Switzerland. The study period is 1932-1971. First of all, the total ozone time series has been identified as a complex system and then Artificial Neural Networks models in the form of Multilayer Perceptron with back propagation learning have been developed. The models are Single-hidden-layer and Two-hidden-layer Perceptrons with sigmoid activation function. After sequential learning with learning rate 0.9 the peak total ozone period (February-May) concentrations of mean monthly total ozone have been predicted by the two neural net models. After training and validation, both of the models are found skillful. But, Two-hidden-layer Perceptron is found to be more adroit in predicting the mean monthly total ozone concentrations over the aforesaid period.

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