Neural network powered COVID-19 spread forecasting model

Wieczorek, Michał; Siłka, Jakub; Woźniak, Marcin

doi:10.1016/j.chaos.2020.110203

Cited by 139 publications

(98 citation statements)

References 18 publications

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“…Since this virus is spreading very fast, we require more strict policies and plans; thus, proper techniques are needed to foresee confirmed cases in upcoming days to make proper protection strategy. Here, prediction models play a key role to understand the duration of the epidemic [ 6 – 8 ]. Thus a highly accurate forecasting model is very much important to forecast the number of confirmed cases in upcoming days.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Model based on mBA-ANFIS for COVID-19 Confirmed Cases Prediction and Forecast

Saif

Das

Biswas

2021

J. Inst. Eng. India Ser. B

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In India, the first confirmed case of novel corona virus (COVID-19) was discovered on January 30, 2020. The number of confirmed cases is increasing day by day, and it crossed 21,53,010 on August 9, 2020. In this paper, a hybrid forecasting model has been proposed to determine the number of confirmed cases for upcoming 10 days based on the earlier confirmed cases found in India. The proposed model is based on adaptive neuro-fuzzy inference system (ANFIS) and mutation-based Bees Algorithm (mBA). The meta-heuristic Bees Algorithm (BA) has been modified applying 4 types of mutation, and mutation-based Bees Algorithm (mBA) is applied to enhance the performance of ANFIS by optimizing its parameters. Proposed mBA-ANFIS model has been assessed using COVID-19 outbreak dataset for India and USA, and the number of confirmed cases in the next 10 days in India has been forecasted. Proposed mBA-ANFIS model has been compared to standard ANFIS model as well as other hybrid models such as GA-ANFIS, DE-ANFIS, HS-ANFIS, TLBO-ANFIS, FF-ANFIS, PSO-ANFIS and BA-ANFIS. All these models have been implemented using Matlab 2015 with 10 iterations each. Experimental results show that the proposed model has achieved better performance in terms of Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean absolute error (MAE) and Normalized Root Mean Square Error (NRMSE). It has obtained RMSE of 1280.24, MAE of 685.68, MAPE of 6.24 and NRMSE of 0.000673 for India Data. Similarly, for USA the values are 4468.72, 3082.07, 6.1, and 0.000952 for RMSE, MAE, MAPE, and NRMSE, respectively. Keywords Mutation-based Bees Algorithm (mBA) Á Adaptive neuro-fuzzy inference system (ANFIS) Á COVID-19 Á Forecast Á RMSE Á MAE Á MAPE Á NRMSE Á India & Suparna Biswas

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Section: Introductionmentioning

confidence: 99%

A Hybrid Model based on mBA-ANFIS for COVID-19 Confirmed Cases Prediction and Forecast

Saif

Das

Biswas

2021

J. Inst. Eng. India Ser. B

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“…Its rapid spreading is an indication that this virus has been transmitted from person to person. In order to prevent the spreading of further Covid-19 virus, countries have blocked international exits [ [8] , [9] , [10] , [11] ]. At the same time, curfews have been announced within many countries.…”

Section: Introductionmentioning

confidence: 99%

A novel Covid-19 and pneumonia classification method based on F-transform

Tuncer

Özyurt

Doğan

et al. 2021

Chemometrics and Intelligent Laboratory Systems

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“…In this context, the reader may have a wrong impression of the fact that the remaining percentage of papers appeared in the journals associated with the population dynamics and the growth curve models, but this is not the fact. Most of these papers have a background with networking [18] , [24] , [74] , statistical distributions [2] , [5] , [67] , [78] , and many other mechanistic models. These all domains of research work will fall into category (iv) of our classification.…”

Section: Introductionmentioning

confidence: 99%