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Introduction: The soft set theory has drawn the attention of many researchers, particularly for dealing with uncertainty in decision-making problems. Despite its remarkable advantages, the soft set theory has only been used to tackle decision-making problems that aim to choose the best option. However, there exist different forms of decision-making problems that involve different forms of uncertainty. Methods: In this study, we present various algorithms based on the soft set theory in order to handle the cases where one has different uncertainty forms in decision-making problems. Some new concepts such as object code, personal object code, parameter significance weight and new distance measures have been introduced to the literature for the construction of these algorithms. Furthermore, we show the application results of those algorithms and provide several examples. Results and Conclusions: As a result, a comparison among the application results of the algorithms implies that the best objects might not always yield the most efficient outcomes. [ABSTRACT FROM AUTHOR]

Complex data analysis should be done in the most accurate way in order to express the uncertain environments in the most ideal way. In addition, mathematical models that can best express the membership degrees that represent the objects are preferred for these data analyses. Taking these situations into account, this study proposes the concept of single-valued neutrosophic fuzzy soft set, which can be expressed with four different membership degrees of each object that provides a parameter, with the contribution of the parameterisation tool. Some important results are obtained by examining some single-valued neutrosophic fuzzy soft set-based theoretical operations. In addition, distance measures between two single-valued neutrosophic fuzzy soft sets. Then, similarity measurements based on these distance measurements are studied. In this way, a determination has been made for the analysis of the decision-making processes for the determination of the interaction between two single-valued neutrosophic fuzzy soft sets. [ABSTRACT FROM AUTHOR]

Coronavirus disease (Covid-19) is a novel pandemic disease. Covid-19 originates from SARS-COV2 and represents the cause of a potentially fatal disease as a global public health problem. However, we have to renew our knowledge about the symptoms of this disease day by day. If we look generally, although the main symptoms seen in this epidemic are fever, cough and shortness of breath, cases without symptoms are also reported. Moreover, in severe cases, pneumonia, severe respiratory failure, kidney failure and death may develop. In this paper, it is suggested that all the different symptoms that may occur in various regions of the world should be taken into consideration and each region should be evaluated within itself. Moreover, in order to have an idea of the general situation, it was taken into account in the average case. For this, two algorithms were built by using soft set theory. The first of the algorithms focuses on the analysis of the relationships between the symptoms and aims to measure a possible effect of the symptoms on each other. The second one aims to identify the most dominant symptom. The results obtained by utilizing both algorithms argue that it is more useful to examine different regions in order to better manage the epidemic. Moreover, some consistent results have been obtained as to which parameters a person should show first in order to Covid test. [ABSTRACT FROM AUTHOR]

In this paper, it is aimed to express more accurately the intuitionistic fuzzy values expressed by the decision-makers for intuitionistic fuzzy parameterized intuitionistic fuzzy soft sets. For this purpose, virtual intuitionistic fuzzy parameterized intuitionistic fuzzy soft sets are proposed by defining the concepts of virtual lower and upper intuitionistic fuzzy approaches. Moreover, the basic set operations for this hybrid set type are examined together with their associated properties. In addition, a decision-making algorithm focusing on virtual intuitionistic fuzzy parameterized intuitionistic fuzzy soft sets is constructed. Finally, an analysis of the obtained results was made. [ABSTRACT FROM AUTHOR]

In this study, we have introduced the bipolar fuzzy soft (D-)metric space which is based on bipolar fuzzy soft point of bipolar fuzzy soft sets and give some of their properties. Also, the bipolar fuzzy soft sequences and bipolar fuzzy soft cauchy sequences concepts have been studied with the help of defined metric spaces and some of their properties have been investigated. In addition to all this, many examples are given in order to better understand the concepts and features studied and contribute to a better understanding of the paper. [ABSTRACT FROM AUTHOR]

In this paper, we intro duce soft lo cally b-closed sets in soft top ological spaces which are defined over an initial universe with a fixed set of parameters and study some of their properties. We investigate their relationships with different types of subsets of soft topological spaces with the help of counterexamples. Also, the concept of soft locally b-continuous functions is presented. Finally, a decomposition of soft continuity is obtained. [ABSTRACT FROM AUTHOR]