| Highlight paper
23 Jul 2018
Research article | Highlight paper | 23 Jul 2018
Using network theory and machine learning to predict El Niño
Peter D. Nooteboom et al.
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26 citations as recorded by crossref.
- Probabilistic Forecasting of El Niño Using Neural Network Models P. Petersik & H. Dijkstra 10.1029/2019GL086423
- El Niño Index Prediction Using Deep Learning with Ensemble Empirical Mode Decomposition Y. Guo et al. 10.3390/sym12060893
- A novel deep neural network model approach to predict Indian Ocean dipole and Equatorial Indian Ocean oscillation indices P. Sarkar et al. 10.1016/j.dynatmoce.2021.101266
- Forecasting El Niño and La Niña events using decision tree classifier K. Silva et al. 10.1007/s00704-022-03999-5
- The Application of Machine Learning Techniques to Improve El Niño Prediction Skill H. Dijkstra et al. 10.3389/fphy.2019.00153
- Simple, low-cost and accurate data-driven geophysical forecasting with learned kernels B. Hamzi et al. 10.1098/rspa.2021.0326
- Opportunities and challenges for machine learning in weather and climate modelling: hard, medium and soft AI M. Chantry et al. 10.1098/rsta.2020.0083
- Reservoir Computing with Delayed Input for Fast and Easy Optimisation L. Jaurigue et al. 10.3390/e23121560
- Spatiotemporal Model Based on Deep Learning for ENSO Forecasts H. Geng & T. Wang 10.3390/atmos12070810
- Challenges and design choices for global weather and climate models based on machine learning P. Dueben & P. Bauer 10.5194/gmd-11-3999-2018
- Confronting Grand Challenges in environmental fluid mechanics T. Dauxois et al. 10.1103/PhysRevFluids.6.020501
- Complexity-based approach for El Niño magnitude forecasting before the spring predictability barrier J. Meng et al. 10.1073/pnas.1917007117
- Network-based forecasting of climate phenomena J. Ludescher et al. 10.1073/pnas.1922872118
- El Niño forecasting based on the global atmospheric oscillation I. Serykh & D. Sonechkin 10.1002/joc.6488
- Feature Selection and Spatial-Temporal Forecast of Oceanic Niño Index Using Deep Learning J. Jonnalagadda & M. Hashemi 10.1142/S0218194022500048
- Weather and climate forecasting with neural networks: using general circulation models (GCMs) with different complexity as a study ground S. Scher & G. Messori 10.5194/gmd-12-2797-2019
- Performance of backpropagation artificial neural network to predict el nino southern oscillation using several indexes as onset indicators B. Aprilia et al. 10.1088/1742-6596/1876/1/012004
- A Hybrid Neural Network Model for ENSO Prediction in Combination with Principal Oscillation Pattern Analyses L. Zhou & R. Zhang 10.1007/s00376-021-1368-4
- Ensemble Empirical Mode Decomposition with Adaptive Noise with Convolution Based Gated Recurrent Neural Network: A New Deep Learning Model for South Asian High Intensity Forecasting K. Peng et al. 10.3390/sym13060931
- Prediction of ENSO Beyond Spring Predictability Barrier Using Deep Convolutional LSTM Networks M. Gupta et al. 10.1109/LGRS.2020.3032353
- Bibliometric Analysis of Methods and Tools for Drought Monitoring and Prediction in Africa O. Adisa et al. 10.3390/su12166516
- Predicting clustered weather patterns: A test case for applications of convolutional neural networks to spatio-temporal climate data A. Chattopadhyay et al. 10.1038/s41598-020-57897-9
- Prediction of Synoptic-Scale Sea Level Pressure Over the Indian Monsoon Region Using Deep Learning A. Sinha et al. 10.1109/LGRS.2021.3100899
- A machine learning based prediction system for the Indian Ocean Dipole J. Ratnam et al. 10.1038/s41598-019-57162-8
- Temporal Convolutional Networks for the Advance Prediction of ENSO J. Yan et al. 10.1038/s41598-020-65070-5
- Machine Learning Models for the Seasonal Forecast of Winter Surface Air Temperature in North America Q. Qian et al. 10.1029/2020EA001140
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