Softζ-Rough Set and Its Applications in Decision Making of Coronavirus

In this paper,we present a proposed method for generating a soft rough approximation as a modification and generalization of Zhaowen et al.approach.Comparisons were obtained between our approach and the previous study and also.Eventually,an application on Coronavirus(COVID-19)has been presented,illustrated using our proposed concept,and some influencing results for symptoms of Coronavirus patients have been deduced.Moreover,following these concepts,we construct an algorithm and apply it to a decision-making problem to demonstrate the applicability of our proposed approach.Finally,a proposed approach that competes with others has been obtained,as well as realistic results for patients with Coronavirus.Moreover,we used MATLAB programming to obtain the results;these results are consistent with those of theWorld Health Organization and an accurate proposal competing with the method of Zhaowen et al.has been studied.Therefore,it is recommended that our proposed concept be used in future decision making.

Decision Making on Fuzzy Soft Simply Continuous of Fuzzy Soft Multi-Function

Real world applications are dealing now with a huge amount of data,especially in the area of high dimensional features.In this article,we depict the simplyupper,the simplylower continuous,we get several characteristics and other properties with respect to upper and lower simply-continuous soft multifunctions.We also investigate the relationship between soft-continuous,simply-continuous multifunction.We also implement fuzzy soft multifunction between fuzzy soft topological spaces which is Akdag’s generation of the notion.We are introducing a new class of soft open sets,namely soft simplyopen set deduce from soft topology,and we are using it to implement the new approximation space called soft multi-function approach space.Simplyspace for approximation based on a simplyopen set.The world must adopt modern studies in order to confront epidemics.Accordingly,we presented a new decision proposal in this article,compared our proposed approach to the soft relationship introduced by approximation of Xueyou,and concluded that our approach is better.We also used our proposal in the medical application that was studied in this paper.

On Soft Pre-Rough Approximation Space with Applications in Decision Making

A soft,rough set model is a distinctive mathematical model that can be used to relate a variety of real-life data.In the present work,we introduce new concepts of rough set based on soft pre-lower and soft pre-upper approximation space.These concepts are soft pre-rough equality,soft pre-rough inclusion,soft pre-rough belonging,soft predefinability,soft pre-internal lower,and soft pre-external lower.We study the properties of these concepts.Finally,we use the soft pre-rough approximation to illustrate the importance of our method in decision-making for Chikungunya medical illnesses.In reality,the impact factors of Chikungunya’s medical infection were determined.Moreover,we develop two new algorithms to address Chikungunya virus issues.Our proposed approach is sensible and effective.

SutteARIMA:A Novel Method for Forecasting the Infant Mortality Rate in Indonesia

This study focuses on the novel forecasting method(SutteARIMA)and its application in predicting Infant Mortality Rate data in Indonesia.It undertakes a comparison of the most popular andwidely used four forecasting methods:ARIMA,Neural Networks Time Series(NNAR),Holt-Winters,and SutteARIMA.The data used were obtained from the website of the World Bank.The data consisted of the annual infant mortality rate(per 1000 live births)from 1991 to 2019.To determine a suitable and best method for predicting InfantMortality rate,the forecasting results of these four methods were compared based on the mean absolute percentage error(MAPE)and mean squared error(MSE).The results of the study showed that the accuracy level of SutteARIMA method(MAPE:0.83%andMSE:0.046)in predicting InfantMortality rate in Indonesia was smaller than the other three forecasting methods,specifically the ARIMA(0.2.2)with a MAPE of 1.21%and a MSE of 0.146;the NNAR with a MAPE of 7.95%and a MSE of 3.90;and the Holt-Winters with aMAPE of 1.03%and aMSE:of 0.083.