For example, in the case of Mexico, right now the time series show an increasing trend, which is presented in this paper, but eventually, there is be a turning point, and the series will decrease, but the model will not have any problem.
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Multiple Ensemble Neural Network Models with Fuzzy Response Aggregation for Predicting COVID-19 Time Series: The Case of Mexico.
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This is because once we have new data with a decreasing trend, we will train the simple neural networks again and use the same architecture of multiple ensembles and fuzzy aggregators to produce the new predictions in a decreasing fashion.