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Time-series prediction with BEMCA approach: Application to short rainfall series., , , , , and . LA-CCI, page 1-6. IEEE, (2017)A Feed-Forward Neural Networks-Based Nonlinear Autoregressive Model for Forecasting Time Series., , , , , and . Computación y Sistemas, (2011)Analysis of a Gaussian process and feed-forward neural networks based filter for forecasting short rainfall time series., , , , , and . IJCNN, page 1-6. IEEE, (2013)Short-term rainfall time series prediction with incomplete data., , and . IJCNN, page 1-6. IEEE, (2015)An Approach for Time Series Forecasting by Simulating Stochastic Processes Through Time Lagged Feed-forward Neural Network., , , , and . DMIN, page 287-293. CSREA Press, (2010)Traditional vs. Machine-Learning Methods for Forecasting Sandy Shoreline Evolution Using Historic Satellite-Derived Shorelines., , , , and . Remote. Sens., 13 (5): 934 (2021)Short-Term Rainfall Forecasting with E-LSTM Recurrent Neural Networks Using Small Datasets., , , , , and . ICIC (3), volume 12465 of Lecture Notes in Computer Science, page 258-270. Springer, (2020)Aspect-Based Sentiment Analysis of Social Media Data With Pre-Trained Language Models., , , , , and . NLPIR, page 8-17. ACM, (2021)Noisy chaotic time series forecast approximated by combining Reny's entropy with energy associated to series method: Application to rainfall series., , , , , and . LA-CCI, page 1-6. IEEE, (2016)Energy Associated Tuning Method for Short-Term Series Forecasting by Complete and Incomplete Datasets., , , , and . J. Artif. Intell. Soft Comput. Res., 7 (1): 5 (2017)