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.

A Model for Selecting a Biomass Furnace Supplier Based on Qualitative and Quantitative Factors

In developing countries,solar energy is the largest source of energy,accounting for 35%–45%of the total energy supply.This energy resource plays a vital role in meeting the energy needs of the world,especially in Vietnam.Vietnam has favorable natural conditions for this energy production.Because it is hot and humid,and it has much rainfall and fertile soil,biomass develops very quickly.Therefore,byproducts from agriculture and forestry are abundant and continuously increasing.However,byproducts that are considered natural waste have become the cause of environmental pollution;these include burning forests,straw,and sawdust in the North;and rice husks dumped into rivers and canals in the Mekong Delta region.Biomass energy is provided in a short cycle,is environmentally safe to use and is encouraged by organizations that support sustainable development.Taking advantage of this energy source provides energy for economic development and ensures environmental protection.Due to the abovementioned favorable conditions,many biomass energy plants are being built in Vietnam.Like other renewable energy investment projects,the selection of the construction contractor,the selection of equipment for the installation of the power plant,and the choice of construction site are complex multi-criteria decisions.In this case,decisionmakers must evaluate many qualitative and quantitative factors.These factors interact with each other and it is difficult to use personal experience to choose the optimal solution for such complex decision-making problems,especially in a fuzzy decision-making environment.Therefore,in this study,the authors use a Multi-Criteria Decision-Making(MCDM)model that uses a Fuzzy Analytic Hierarchy Process(FAHP)model and the Combined Compromise Solution(CoCoSo)algorithm to select biomass furnace suppliers utilizing both qualitative and quantitative factors.Furthermore,the results of this work will provide the first look at a hybrid CoCoSo/FAHP method that decision-makers in other fields can use to find the best supplier.

Prediction of BRIC Stock Price Using ARIMA,SutteARIMA,and Holt-Winters

The novel coronavirus has played a disastrous role in many countries worldwide.The outbreak became a major epidemic,engulfing the entire world in lockdown and it is now speculated that its economic impact might be worse than economic deceleration and decline.This paper identifies two different models to capture the trend of closing stock prices in Brazil(BVSP),Russia(IMOEX.ME),India(BSESN),and China(SSE),i.e.,(BRIC)countries.We predict the stock prices for three daily time periods,so appropriate preparations can be undertaken to solve these issues.First,we compared the ARIMA,SutteARIMA and Holt-Winters(H-W)methods to determine the most effective model for predicting data.The stock closing price of BRIC country data was obtained from Yahoo Finance.That data dates from 01 November 2019 to 11 December 2020,then divided into two categories-training data and test data.Training data covers 01 November 2019 to 02 December 2020.Seven days(03December 2020 to 11December 2020)of datawas tested to determine the accuracy of the models using training data as a reference.To measure the accuracy of the models,we obtained the means absolute percentage error(MAPE)and mean square error(MSE).Prediction model Holt-Winters was found to be the most suitable for forecasting the Brazil stock price(BVSP)while MAPE(0.50)and MSE(579272.65)with Holt-Winters(smaller than ARIMA and SutteARIMA),model SutteARIMA was found most appropriate to predict the stock prices of Russia(IMOEX.ME),India(BSESN),and China(SSE)when compared to ARIMA and Holt-Winters.MAPE andMSE with SutteARIMA:Russia(MAPE:0.7;MSE:940.20),India(MAPE:0.90;MSE:207271.16),and China(MAPE:0.72;MSE:786.28).Finally,Holt-Winters predicted the daily forecast values for the Brazil stock price(BVSP)(12 December to 14 December 2020 i.e.,115757.6,116150.9 and 116544.1),while SutteARIMA predicted the daily forecast values of Russia stock prices(IMOEX.ME)(12 December to 14 December 2020 i.e.,3238.06,3241.54 and 3245.01),India stock price(BSESN)(12 December to 14 December 2020 i.e.,.45709.38,45828.71 and 45948.05),and China stock price(SSE)(11 December to 13 December 2020 i.e.,3397.56,3390.59 and 3383.61)for the three time periods.

Generalized Normalized Euclidean Distance Based Fuzzy Soft Set Similarity for Data Classification

Classification is one of the data mining processes used to predict predetermined target classes with data learning accurately.This study discusses data classification using a fuzzy soft set method to predict target classes accurately.This study aims to form a data classification algorithm using the fuzzy soft set method.In this study,the fuzzy soft set was calculated based on the normalized Hamming distance.Each parameter in this method is mapped to a power set from a subset of the fuzzy set using a fuzzy approximation function.In the classification step,a generalized normalized Euclidean distance is used to determine the similarity between two sets of fuzzy soft sets.The experiments used the University of California(UCI)Machine Learning dataset to assess the accuracy of the proposed data classification method.The dataset samples were divided into training(75%of samples)and test(25%of samples)sets.Experiments were performed in MATLAB R2010a software.The experiments showed that:(1)The fastest sequence is matching function,distance measure,similarity,normalized Euclidean distance,(2)the proposed approach can improve accuracy and recall by up to 10.3436%and 6.9723%,respectively,compared with baseline techniques.Hence,the fuzzy soft set method is appropriate for classifying data.

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.

Dazed and Confused:The Impact of Multinational Firms on Local Labor Markets

In this high-speed globalization era,the opportunities for multinational companies(MNCs)have become vast.In such situation,these companies can obtain maximum profit only if they know how to use workforce properly.This paper aims at analyzing how these MNCs can use international workforce without violating ethics,universal labor rights,and human resource rules.For this purpose,two most favored countries i.e.,China and Indonesia have been taken and compared throughout the paper.The first part of this paper deals with the introduction of the profile of above mentioned two countries and opportunities to the MNCs.The second part deals with the roles of institutions in dealing with labor workforce.The third part indicates divergent paths and the convergence of the globalization with its impact over host countries.The final part concludes the entire discussion in a few paragraphs.The entire paper has been developed keeping the scholarly work,journal articles and critical analysis factor under consideration.

Tongkonan Ke’te‘Kesu’as a Traditional Architectural Tourist Attrac­tion in Tana Toraja

This research aims to know the function of Traditional House of Toraja and Typology,as a unique traditional architectural tourist attraction in Ke'te'Kesu'.The research is qualitative research.Data collection is done by observation,interview,and documentation.The research variables consist of:Function of Traditional House(Tongkonan),and it’s Typology.The data analysis technique used is descriptive qualitative analysis,which is analyzing each variable descriptive,with the following steps:1)selecting,reducing or simplifying data,2)data display or data presentation which is the stage of qualitative data analysis techniques,3)draw conclusions and data verification which is the last stage in qualitative data analysis techniques.The results show that:In general,the main function of traditional Toraja house(Tongkonan)and its built environment is as a container of human activities supporting Toraja culture,consisting of Rambu Solo’that is the customary ceremony associated with death,and Rambu Tuka’or all things good lifestyle as well ceremonies related to daily life.Then typology can be viewed from aspects of Layout,Spatial,Shape,Structure and Construction,and Ornaments.