Decision-making to limit epidemics spread based on fuzzy-soft and topological spaces

Real-world applications process enormous amounts of data, especially in the area of large-dimension features. This work aims to present new classes of functions based on SM*-open sets that are a modification of simply open sets;namely, SM*-continuous, SM*-irresolute, proper continuous, SM*-open, SM*-closed, strongly SM*-irresolute, Pre SM*-irresolute, Pre SM*-open, super SM*-open and completely irresolute. The idea of fuzzy soft multifunction between fuzzy soft topological spaces, developed by Metin, is frequently used. Our current research project uses our suggested idea to introduce coronavirus application and infer the most important causal symptoms of coronavirus patients. Furthermore, we created an algorithm to demonstrate the applicability of our proposed technique based on the presented concept. Additionally, the results obtained using MATLAB programming. Finally, realistic WHO-compliant results were achieved for the most serious symptoms of coronavirus patients, as well as a suggested strategy that is competitive. Therefore, decision-making in the future needs to consider our suggestion. In order to promote the long-term wellbeing of both nature and humanity. Our proposed approach is reasonable and effective. The results showed that the methodology we used was reliable as it was consistent with World Health Organization publications.

Coronavirus Decision-Making Based on a Locally S-M* alpha-Generalized Closed Set

Real-world applications now deal with a massive amount of data, and information about the world is inaccurate, incomplete, or uncertain. Therefore, we present in our paper a proposed model for solving problems. This model is based on the class of locally generalized closed sets, namely, locally simply* alpha generalized closed* sets and locally simply* alpha generalized closed** sets (briefly, L S-M*alpha GC*-sets and L S-M*alpha GC**-sets), based on simply* alpha open set. We also introduce various concepts of their properties and their relationship with other types, and we are studying several of their properties. Finally, we apply the concept of the simply* alpha open set to illustrate the importance of our method in decision-making for information systems about the infections of Coronavirus in humans. In fact, we were able to decide the impact factors of Coronavirus infection. The results were also programmed using the MATLAB program. Therefore, it is recommended that our proposed concept be used in future decision-making.

Soft ζ-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 the World 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. © 2021 Tech Science Press. All rights reserved.

Decision Making Based on Fuzzy Soft Sets and Its Application in COVID-19

Real-world applications are now dealing with a huge amount of data, especially in the area of high-dimensional features. Trait reduction is one of the major steps in decision making problems. It refers to the determination of a minimum subset of attributes which preserves the final decision based on the entire set of attributes. Unfortunately, most of the current features are irrelevant or redundant, which makes these systems unreliable and imprecise. This paper proposes a new paradigm based on fuzzy soft relationship and level fuzzy soft relationship, called Union - Intersection decision making method. Using these new principles, the decision-making strategy is structured to choose a fuzzy set of optimal elements from the alternatives on the basis of a fuzzy soft set. Finally, we used our proposed method in medical application to make the decision to diagnose COVID-19. Moreover, we used MATLAB programming to obtain the results;this has coincided with the announcement by the World Health Organization and an accurate proposal was examined, which competes with that of the method of Zhao.

Association between Temperature and Relative Humidity in Relation to COVID-19

The aim of this study is to determine the association between temperature and humidity in relation to COVID-19 above 3 degrees C. This was carried out in the cities of Bandung and Surabaya which have temperatures of about 22 degrees C to 31 degrees C. Data was analyzed using descriptive analysis and the Pearson and Spearman correlation for normally and abnormally distributed data. The results showed that there was no association between people under monitoring (ODP)/close contact, patients under surveillance (PDP)/suspect, and COVID-19 confirmed cases in relation to the temperature and humidity in Bandung and Surabaya. Furthermore, there was no relationship between temperature and humidity with ODP, PDP, and COVID-19 Confirmed cases in both cities, because they had a comfortably wet category (RH > 70%). This results are expected to provide information to the government that weather cases in Indonesia (temperatures around 26 degrees C-30 degrees C with humidity > 60%) do not affect the spread of COVID-19. In addition, it is expected that further studies would be carried out on other factors that influence the spread of COVID-19 in Indonesia, for example, how the level of alternating flow in and/ or out of the population into an area.

Topological approach for decision-making of covid-19 infection via a nano-topology model

The conditions of the equivalence relation limit the application fields of the methodology of Pawlak’s rough sets. So, to expand the application areas of this theory, it is generalized to any binary relation. Neighborhoods induced from the relations represent a core bridge between rough sets and application since it represents easy tools for dealing with daily-life problems. Accordingly, the first core objective of the current research is to propose a novel neighborhood (so-called an initial-neighborhood) generated from any binary relation. Based on this neighborhood, we suggest a new generalization to Pawlak rough sets and some of their extensions. The proposed approaches satisfy all properties of classical rough sets without adding any extra restrictions and hence we can apply them in any real-life problem. The second aim is to generalize the notion of nano-topology into any binary relation to extend the applications of this concept. Properties of the suggested methods are introduced with many counter-examples. Comparisons between the suggested techniques and the others studies published in the literature are examined. We proved that the proposed techniques are extra precise than the earlier approaches. Finally, the medical application of COVID-19 is provided to illustrate the significance of our approaches in deciding the impact factors for COVID-19 infection. The proposed application is based on a reflexive relation, so Pawlak rough sets and some of its generalizations couldn’t be applied to solve this problem. Accordingly, we have successes in solving this problem using the suggested techniques. Hence, we write an algorithm to be a useful tool that may help the doctor in diagnosing the infection of COVID-19. © 2021 the Author(s), licensee AIMS Press.