Applied multivariate statistical analysis
Applied multivariate statistical analysis
Accelerating neural network training using weight extrapolations
Neural Networks
Understanding Neural Networks and Fuzzy Logic: Basic Concepts and Applications
Understanding Neural Networks and Fuzzy Logic: Basic Concepts and Applications
Neuro-Fuzzy Pattern Recognition: Methods in Soft Computing
Neuro-Fuzzy Pattern Recognition: Methods in Soft Computing
Prediction of mean monthly total ozone time series-application of radial basis function network
International Journal of Remote Sensing
A comparison between neural-network forecasting techniques-case study: river flow forecasting
IEEE Transactions on Neural Networks
Spatio-temporal modelling and analysis of urban heat islands by using Landsat TM and ETM+ imagery
International Journal of Remote Sensing
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The present paper develops three predictive models for daily total ozone concentration over Arosa, Switzerland. The models are artificial neural network, multiple linear regression, and persistence forecast. Each model was judged for their predictive ability using analysis of variance, Pearson correlation study, and scatterplot analysis. Prediction errors were computed for each model. After painstaking analysis it was established that artificial neural network produces better forecasts than the statistical approaches like multiple linear regression and persistence forecast models.