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2006 Special issue: Neural network forecasts of the tropical Pacific sea surface temperatures

Published: 01 March 2006 Publication History

Abstract

A nonlinear forecast system for the sea surface temperature (SST) anomalies over the whole tropical Pacific has been developed using a multi-layer perceptron neural network approach, where sea level pressure and SST anomalies were used as predictors to predict the five leading SST principal components at lead times from 3 to 15 months. Relative to the linear regression (LR) models, the nonlinear (NL) models showed higher correlation skills and lower root mean square errors over most areas of the domain, especially over the far western Pacific (west of 155^oE) and the eastern equatorial Pacific off Peru at lead times longer than 3 months, with correlation skills enhanced by 0.10-0.14. Seasonal and decadal changes in the prediction skills in the NL and LR models were also studied.

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  • (2023)The CNN-GRU model with frequency analysis module for sea surface temperature predictionSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-023-08172-227:13(8711-8720)Online publication date: 1-Jul-2023
  • (2016)Forecasting Monthly Rainfall in the Bowen Basin of Queensland, Australia, Using Neural Networks with Niño IndicesAI 2016: Advances in Artificial Intelligence10.1007/978-3-319-50127-7_7(88-100)Online publication date: 5-Dec-2016
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Information & Contributors

Information

Published In

cover image Neural Networks
Neural Networks  Volume 19, Issue 2
2006 special issue: Earth sciences and environmental applications of computational intelligence
March 2006
140 pages

Publisher

Elsevier Science Ltd.

United Kingdom

Publication History

Published: 01 March 2006

Author Tags

  1. ENSO
  2. El Niño
  3. Forecast
  4. Neural network
  5. Nonlinear
  6. Sea surface temperature
  7. Tropical Pacific

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View all
  • (2023)HiGRN: A Hierarchical Graph Recurrent Network for Global Sea Surface Temperature PredictionACM Transactions on Intelligent Systems and Technology10.1145/359793714:4(1-19)Online publication date: 21-Jul-2023
  • (2023)The CNN-GRU model with frequency analysis module for sea surface temperature predictionSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-023-08172-227:13(8711-8720)Online publication date: 1-Jul-2023
  • (2016)Forecasting Monthly Rainfall in the Bowen Basin of Queensland, Australia, Using Neural Networks with Niño IndicesAI 2016: Advances in Artificial Intelligence10.1007/978-3-319-50127-7_7(88-100)Online publication date: 5-Dec-2016
  • (2013)Prediction of sea surface temperature in the tropical Atlantic by support vector machinesComputational Statistics & Data Analysis10.5555/2749480.274961661:C(187-198)Online publication date: 1-May-2013
  • (2011)Using artificial neural networks to predict direct solar irradiationAdvances in Artificial Neural Systems10.1155/2011/1420542011(12-12)Online publication date: 1-Jan-2011
  • (2009)An Adaptive Recursive Least Square Algorithm for Feed Forward Neural Network and Its ApplicationProceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence10.1007/978-3-540-74205-0_35(315-323)Online publication date: 17-Nov-2009
  • (2007)An improved training algorithm of neural networks for time series forecastingProceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence10.5555/1775967.1776024(550-558)Online publication date: 4-Nov-2007

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