10 citations as recorded by crossref.

1. Predicting Global Solar Radiation Using an Artificial Neural Network Single‐Parameter Model K. Angela et al. https://doi.org/10.1155/2011/751908
2. Nonparametric functional data estimation applied to ozone data: Prediction and extreme value analysis A. Quintela-del-Rı´o & M. Francisco-Fernández https://doi.org/10.1016/j.chemosphere.2010.11.025
3. Prediction of mean monthly total ozone time series – application of radial basis function network S. Chattopadhyay https://doi.org/10.1080/01431160701227695
4. Improving the prediction of average total ozone in column over the Iberian Peninsula using neural networks banks S. Salcedo-Sanz et al. https://doi.org/10.1016/j.neucom.2011.01.003
5. Artificial neural network with backpropagation learning to predict mean monthly total ozone in Arosa, Switzerland S. Chattopadhyay & G. Bandyopadhyay https://doi.org/10.1080/01431160701250440
6. Bayesian neural network modeling of tree-ring temperature variability record from the Western Himalayas R. Tiwari & S. Maiti https://doi.org/10.5194/npg-18-515-2011
7. Identification of the best architecture of a multilayer perceptron in modeling daily total ozone concentration over Kolkata, India S. De et al. https://doi.org/10.2478/s11600-010-0047-0
8. Forecasting daily total ozone concentration—a comparison between neurocomputing and statistical approaches S. Chattopadhyay & G. Chattopadhyay‐Bandyopadhyay https://doi.org/10.1080/01431160701373770
9. Novel deseasonalizing models for improving the prediction of total ozone in column using evolutionary programming and neural networks S. Salcedo-Sanz et al. https://doi.org/10.1016/j.jastp.2010.09.021
10. Assessment of Spatio-temporal Climatological trends of ozone over the Indian region using Machine Learning M. Pathakoti et al. https://doi.org/10.1016/j.spasta.2021.100513