Multiple Ensemble Neural Network Models with Fuzzy Response Aggregation for Predicting COVID-19 Time Series: The Case of Mexico.

Patricia Melin,Oscar Castillo,Julio Cesar Monica,Daniela Sanchez

doi:10.3390/healthcare8020181

Patricia Melin, Oscar Castillo + Show 2 more

Open Access

https://doi.org/10.3390/healthcare8020181

Copy DOI

Journal: Healthcare	Publication Date: Jun 19, 2020
Citations: 139	License type: CC BY 4.0

Affiliation: Instituto Tecnológico de Tijuana

Abstract

In this paper, a multiple ensemble neural network model with fuzzy response aggregation for the COVID-19 time series is presented. Ensemble neural networks are composed of a set of modules, which are used to produce several predictions under different conditions. The modules are simple neural networks. Fuzzy logic is then used to aggregate the responses of several predictor modules, in this way, improving the final prediction by combining the outputs of the modules in an intelligent way. Fuzzy logic handles the uncertainty in the process of making a final decision about the prediction. The complete model was tested for the case of predicting the COVID-19 time series in Mexico, at the level of the states and the whole country. The simulation results of the multiple ensemble neural network models with fuzzy response integration show very good predicted values in the validation data set. In fact, the prediction errors of the multiple ensemble neural networks are significantly lower than using traditional monolithic neural networks, in this way showing the advantages of the proposed approach.

Highlights

We noticed the rapid propagation of the COVID-19 Coronavirus around the world, appearing initially in China and spreading to neighbor countries, like Thailand, Korea, and Japan, and after that to Europe, America, and later Africa
Fuzzy logic was used to aggregate the responses of several predictor modules, in this way, improving the final prediction by combining, in a proper way, the outputs of the modules
The complete model was tested for the case of predicting the COVID-19 time series in Mexico, at the level of the states and the whole country

Summary

Introduction

We noticed the rapid propagation of the COVID-19 Coronavirus around the world, appearing initially in China and spreading to neighbor countries, like Thailand, Korea, and Japan, and after that to Europe, America, and later Africa. Europe, Italy, Spain, France, the United Kingdom, and Germany have been hit hard with the propagation of the COVID-19 virus, having to this moment many confirmed cases and deaths. The virus spread to the American continent, and the United States and Canada which were hit hard with the spread of the COVID-19 virus. 50,000 confirmed cases as of 18 May 2020. In relation to COVID-19 prediction, we can mention the following work. In Chen et al [1], the authors outline the prediction of the SARS-CoV-2 (2019-nCoV) 3C-as a protease structure

Methods

Results

Conclusion