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A neurocomputing approach to the forecasting of monthly maximum temperature over Kolkata, India using total ozone concentration as predictor
S S DE, G CHATTOPADHYAY, B BANDYOPADHYAY, S PAUL
Published in ELSEVIER FRANCE-EDITIONS SCIENTIFIQUES MEDICALES ELSEVIER
2011
Volume: 343
   
Issue: 10
Pages: 664 - 676
Abstract
The association between the monthly total ozone concentration and monthly maximum temperature over Kolkata (22.56°N, 88.30° E), India, has been explored in this paper. For this, the predictability of monthly maximum temperature based on the total ozone as predictor is investigated using Artificial Neural Network. The presence of persistence and similar cyclic patterns are revealed through autocorrelation and cross-correlation coefficients. Common cycles of length 12 and 6 have been identified through periodogram. Hence, a predictive model has been generated by Artificial Neural Network in the form of Multi Layer Perceptron (MLP) using scaled conjugate gradient learning with sigmoid non-linearity. After training and testing the network, an MLP with total ozone of month n as predictor and maximum temperature of month (n+. 1) as the target output is found as the best model. Performance of the model has been judged statistically. Finally, the MLP model has been compared with linear and non-linear regressions and the efficiency of MLP has been established over the regression models. © 2011.
About the journal
JournalData powered by TypesetComptes Rendus - Geoscience
PublisherData powered by TypesetELSEVIER FRANCE-EDITIONS SCIENTIFIQUES MEDICALES ELSEVIER
ISSN1631-0713