Marine Predators Algorithm for Forecasting Confirmed Cases of COVID-19 in Italy, USA, Iran and Korea
The current pandemic of the new coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), or COVID-19, has received wide attention by scholars and researchers. The vast increase in infected people is a significant challenge for each country and the international community in general...
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doaj-3ef15053697b4ff1bf8798f3f30dac582020-11-25T02:56:48ZengMDPI AGInternational Journal of Environmental Research and Public Health1661-78271660-46012020-05-01173520352010.3390/ijerph17103520Marine Predators Algorithm for Forecasting Confirmed Cases of COVID-19 in Italy, USA, Iran and KoreaMohammed A. A. Al-qaness0Ahmed A. Ewees1Hong Fan2Laith Abualigah3Mohamed Abd Elaziz4State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, ChinaDepartment of e-Systems, University of Bisha, Bisha 61922, Saudi ArabiaState Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, ChinaFaculty of Computer Sciences and Informatics, Amman Arab University, Amman 11953, JordanDepartment of Mathematics, Faculty of Science, Zagazig University, Zagazig 44519, EgyptThe current pandemic of the new coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), or COVID-19, has received wide attention by scholars and researchers. The vast increase in infected people is a significant challenge for each country and the international community in general. The prediction and forecasting of the number of infected people (so-called confirmed cases) is a critical issue that helps in understanding the fast spread of COVID-19. Therefore, in this article, we present an improved version of the ANFIS (adaptive neuro-fuzzy inference system) model to forecast the number of infected people in four countries, Italy, Iran, Korea, and the USA. The improved version of ANFIS is based on a new nature-inspired optimizer, called the marine predators algorithm (MPA). The MPA is utilized to optimize the ANFIS parameters, enhancing its forecasting performance. Official datasets of the four countries are used to evaluate the proposed MPA-ANFIS. Moreover, we compare MPA-ANFIS to several previous methods to evaluate its forecasting performance. Overall, the outcomes show that MPA-ANFIS outperforms all compared methods in almost all performance measures, such as Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Root Mean Squared Relative Error (RMSRE), and Coefficient of Determination(<inline-formula> <math display="inline"> <semantics> <msup> <mi>R</mi> <mn>2</mn> </msup> </semantics> </math> </inline-formula>). For instance, according to the results of the testing set, the <inline-formula> <math display="inline"> <semantics> <msup> <mi>R</mi> <mn>2</mn> </msup> </semantics> </math> </inline-formula> of the proposed model is 96.48%, 98.59%, 98.74%, and 95.95% for Korea, Italy, Iran, and the USA, respectively. More so, the MAE is 60.31, 3951.94, 217.27, and 12,979, for Korea, Italy, Iran, and the USA, respectively.https://www.mdpi.com/1660-4601/17/10/3520COVID-19ANFISSARS-CoV-2forecastingmarine predators algorithm (MPA) |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Mohammed A. A. Al-qaness Ahmed A. Ewees Hong Fan Laith Abualigah Mohamed Abd Elaziz |
spellingShingle |
Mohammed A. A. Al-qaness Ahmed A. Ewees Hong Fan Laith Abualigah Mohamed Abd Elaziz Marine Predators Algorithm for Forecasting Confirmed Cases of COVID-19 in Italy, USA, Iran and Korea International Journal of Environmental Research and Public Health COVID-19 ANFIS SARS-CoV-2 forecasting marine predators algorithm (MPA) |
author_facet |
Mohammed A. A. Al-qaness Ahmed A. Ewees Hong Fan Laith Abualigah Mohamed Abd Elaziz |
author_sort |
Mohammed A. A. Al-qaness |
title |
Marine Predators Algorithm for Forecasting Confirmed Cases of COVID-19 in Italy, USA, Iran and Korea |
title_short |
Marine Predators Algorithm for Forecasting Confirmed Cases of COVID-19 in Italy, USA, Iran and Korea |
title_full |
Marine Predators Algorithm for Forecasting Confirmed Cases of COVID-19 in Italy, USA, Iran and Korea |
title_fullStr |
Marine Predators Algorithm for Forecasting Confirmed Cases of COVID-19 in Italy, USA, Iran and Korea |
title_full_unstemmed |
Marine Predators Algorithm for Forecasting Confirmed Cases of COVID-19 in Italy, USA, Iran and Korea |
title_sort |
marine predators algorithm for forecasting confirmed cases of covid-19 in italy, usa, iran and korea |
publisher |
MDPI AG |
series |
International Journal of Environmental Research and Public Health |
issn |
1661-7827 1660-4601 |
publishDate |
2020-05-01 |
description |
The current pandemic of the new coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), or COVID-19, has received wide attention by scholars and researchers. The vast increase in infected people is a significant challenge for each country and the international community in general. The prediction and forecasting of the number of infected people (so-called confirmed cases) is a critical issue that helps in understanding the fast spread of COVID-19. Therefore, in this article, we present an improved version of the ANFIS (adaptive neuro-fuzzy inference system) model to forecast the number of infected people in four countries, Italy, Iran, Korea, and the USA. The improved version of ANFIS is based on a new nature-inspired optimizer, called the marine predators algorithm (MPA). The MPA is utilized to optimize the ANFIS parameters, enhancing its forecasting performance. Official datasets of the four countries are used to evaluate the proposed MPA-ANFIS. Moreover, we compare MPA-ANFIS to several previous methods to evaluate its forecasting performance. Overall, the outcomes show that MPA-ANFIS outperforms all compared methods in almost all performance measures, such as Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Root Mean Squared Relative Error (RMSRE), and Coefficient of Determination(<inline-formula> <math display="inline"> <semantics> <msup> <mi>R</mi> <mn>2</mn> </msup> </semantics> </math> </inline-formula>). For instance, according to the results of the testing set, the <inline-formula> <math display="inline"> <semantics> <msup> <mi>R</mi> <mn>2</mn> </msup> </semantics> </math> </inline-formula> of the proposed model is 96.48%, 98.59%, 98.74%, and 95.95% for Korea, Italy, Iran, and the USA, respectively. More so, the MAE is 60.31, 3951.94, 217.27, and 12,979, for Korea, Italy, Iran, and the USA, respectively. |
topic |
COVID-19 ANFIS SARS-CoV-2 forecasting marine predators algorithm (MPA) |
url |
https://www.mdpi.com/1660-4601/17/10/3520 |
work_keys_str_mv |
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