Fuzzy Soft Topology Research Articles

Novel categories of spaces in the frame of fuzzy soft topologies

<abstract><p>In the present paper, we introduce and discuss a new set of separation properties in fuzzy soft topological spaces called $ FS\delta $-separation and $ FS\delta $-regularity axioms by using fuzzy soft $ \delta $-open sets and the quasi-coincident relation. We provide a comprehensive study of their properties with some supporting examples. Our analysis includes more characterizations, results, and theorems related to these notions, which contributes to a deeper understanding of fuzzy soft separability properties. We show that the $ FS\delta $-separation and $ FS\delta $-regularity axioms are harmonic and heredity property. Additionally, we examine the connections between $ FS{\delta }^* $-compactness and $ FS\delta $-separation axioms and explore the relationships between them. Overall, this work offers a new perspective on the theory of separation properties in fuzzy soft topological spaces, as well as provides a robust foundation for further research in the transmission of properties from fuzzy soft topologies to fuzzy and soft topologies and vice-versa by swapping between the membership function and characteristic function in the case of fuzzy topology and the set of parameters and a singleton set in the case of soft topology.</p></abstract>

Intuitionistic Fuzzy Soft Topology via Neighborhood

In this paper, we bring out some properties of intuitionistic fuzzy soft topology by using the concept of neighborhood. Firstly, we introduce the concept of intuitionistic fuzzy soft point differently from the previous published papers which is related to intuitonistic fuzzy soft point and study some of its basic properties. We also generate an intuitonistic fuzzy soft topology by using the systems of neighborhood and discuss certain properties of intuitonistic fuzzy soft topology including continuous mapping.

A note on strong form of fuzzy soft pre-continuity

We adapt strong θ−pre-continuity into fuzzy soft topology and investigate its properties. Also, the relations with the other types of continuities in fuzzy soft topological spaces are analized. Moreover, we give some new definitions.

Bipolar Spherical Fuzzy Soft Topology with Applications to Multi-Criteria Group Decision-Making in Buildings Risk Assessment

A generalized soft set model that is more accurate, useful, and realistic is the bipolar spherical fuzzy soft set (BSFSs). It is a more developed variant of current fuzzy soft set models that may be applied to characterize erroneous data in practical applications. Bipolar spherical fuzzy soft sets and bipolar spherical fuzzy soft topology are novel ideas that are intended to be introduced in this work. Bipolar spherical fuzzy soft intersection, bipolar spherical fuzzy soft null set, spherical fuzzy soft absolute set, and other operations on bipolar spherical fuzzy soft sets are some of the fundamental ideas defined in this work. The bipolar spherical fuzzy soft open set, the bipolar spherical fuzzy soft close set, the bipolar spherical fuzzy soft closure, and the spherical fuzzy soft interior are also defined. Additionally, the characteristics of this specified set are covered and described using pertinent instances. The innovative notion of BSFSs makes it easier to describe the symmetry of two or more objects. Moreover, a group decision-making algorithm based on the TOPSIS (Technique of Order Preference by Similarity to an Ideal Solution) approach to problem-solving is described. We analyze the symmetry of the optimal decision and ranking of feasible alternatives. A numerical example is used to show how the suggested approach may be used. The extensive benefits of the proposed work over the existing techniques have been listed.

Spherical Fuzzy Soft Topology and Its Application in Group Decision-Making Problems

The spherical fuzzy soft set is a generalized soft set model, which is more realistic, practical, and accurate. It is an extended version of existing fuzzy soft set models that can be used to describe imprecise data in real-world scenarios. The paper seeks to introduce the new concept of spherical fuzzy soft topology defined on spherical fuzzy soft sets. In this work, we define some basic concepts including spherical fuzzy soft basis, spherical fuzzy soft subspace, spherical fuzzy soft interior, spherical fuzzy soft closure, and spherical fuzzy soft boundary. The properties of these defined set are also discussed and explained with an appropriate examples. Also, we establish certain important results and introduce spherical fuzzy soft separation axioms, spherical fuzzy soft regular space, and spherical fuzzy soft normal space. Furthermore, as an application, a group decision-making algorithm is presented based on the TOPSIS (Technique of Order Preference by Similarity to an Ideal Solution) method for solving the decision-making problems. The applicability of the proposed method is demonstrated through a numerical example. The comprehensive advantages of the proposed work have been stated over the existing methods.

The Relationship Between Fuzzy Soft and Soft Topologies

This paper attempts to forward both soft topology and fuzzy soft topology with a pioneering analysis of their mutual relationships. With each soft topology we associate a parameterized family of fuzzy soft topologies called its t-pushes. And each fuzzy soft topology defines a parameterized family of soft topologies called its t-throwbacks. Different soft topologies produce different t-pushes. But we prove by example that not all fuzzy soft topologies are characterized by their t-throwbacks. The import of these constructions is that some properties stated in one setting can be investigated in the other setting. Our conclusions should fuel future research on both fuzzy soft topology and soft topology.

A New Approach to Vague Soft Bi-Topological Spaces

Fuzzy soft topology considers only membership value. It has nothing to do with the non-membership value. So an extension was needed in this direction. Vague soft topology addresses both membership and non-membership values simultaneously. Sometimes vague soft topology (single structure) is unable to address some complex structures. So an extension to vague soft bi-topology (double structure) was needed in this direction. To make this situation more meaningful, a new concept of vague soft bi-topological space is introduced and its structural characteristics are attempted with a new definition. In this article, new concept of vague soft bi-topological space (VSBTS) is initiated and its structural behaviors are attempted. This approach is based on generalized vague soft open sets, known as vague soft open sets. An ample of examples are given to understand the structures. For the non-validity of some results, counter examples are provided to pay the price. Pair-wise vague soft open and pair-wise vague soft close sets are also addressed with examples in (VSBTS). Vague soft separation axioms are initiated in (VSBTS) concerning soft points of the space. Other separation axioms are also addressed relative to soft points of the space. Vague soft bi-topological properties are studied with the application of vague soft open sets with respect to soft points of the spaces. The characterization of vague soft close as well as vague soft open sets, characteristics of Bolzano Weirstrass property, vague soft compactness and its marriage with sequences, interconnection between sequential compactness and countable compactness in (VSBTS) with respect to soft open sets are addressed.

A lifesaving tool for covid patients using BPF soft topology: decision making in oxygen concentrator

In this paper, we introduced the notion of bipolar Pythagorean fuzzy soft topology and proved some of its basic properties. We defined bipolar Pythagorean fuzzy regular generalized soft sets. We presented some basic operations on bipolar Pythagorean fuzzy soft topology. We gave an application of bipolar Pythagorean fuzzy soft open sets which are bipolar Pythagorean fuzzy regular generalized closed sets taken from bipolar Pythagorean fuzzy topology into a decision-making problem.

On Interval-Valued Fuzzy Soft Preordered Sets and Associated Applications in Decision-Making

Recently, using interval-valued fuzzy soft sets to rank alternatives has become an important research area in decision-making because it provides decision-makers with the best option in a vague and uncertain environment. The present study aims to give an extensive insight into decision-making processes relying on a preference relationship of interval-valued fuzzy soft sets. Firstly, interval-valued fuzzy soft preorderings and an interval-valued fuzzy soft equivalence are established based on the interval-valued fuzzy soft topology. Then, two crisp preordering sets, namely lower crisp and upper crisp preordering sets, are proposed. Next, a score function depending on comparison matrices is expressed in solving multi-group decision-making problems. Finally, a numerical example is given to illustrate the validity and efficacy of the proposed method.

Fuzzy Soft Topology Based on Generalized Intersection and Generalized Union of Fuzzy Soft Sets

In this study, the generalized intersection and union operations of fuzzy soft set (FSS) are established on the basis of traditional FSS operations, which overcome the shortcomings of traditional FSS operations that do not meet De Morgan’s law, and a series of properties of generalized intersection and union operations of FSS are obtained. The fuzzy soft topology under generalized intersection and generalized union operation of FSSs is established. Finally, the topological construction of weak FSS and strong FSS is discussed, and the relationship between them and the topological construction of traditional FSS is obtained.

Application of Induced Preorderings in Score Function-Based Method for Solving Decision-Making with Interval-Valued Fuzzy Soft Information

Ranking interval-valued fuzzy soft sets is an increasingly important research issue in decision making, and provides support for decision makers in order to select the optimal alternative under an uncertain environment. Currently, there are three interval-valued fuzzy soft set-based decision-making algorithms in the literature. However, these algorithms are not able to overcome the issue of comparable alternatives and, in fact, might be ignored due to the lack of a comprehensive priority approach. In order to provide a partial solution to this problem, we present a group decision-making solution which is based on a preference relationship of interval-valued fuzzy soft information. Further, corresponding to each parameter, two crisp topological spaces, namely, lower topology and upper topology, are introduced based on the interval-valued fuzzy soft topology. Then, using the preorder relation on a topological space, a score function-based ranking system is also defined to design an adjustable multi-steps algorithm. Finally, some illustrative examples are given to compare the effectiveness of the present approach with some existing methods.

Application of Intuitionistic Fuzzy Soft Set to Topology

A new topology on a set can be generated by a basis. In this paper, we construct an intuitionistic fuzzy soft basis for an intuitionistic fuzzy soft topology. Furthermore, we define the intuitionistic fuzzy soft topology generated by basis and establish some important theorem. Also, some concepts of intuitionistic fuzzy soft basis and subbasis are introduced here.

On bipolar fuzzy soft topology with decision-making

In this paper, we bring out the idea of bipolar fuzzy soft topology (BFS-topology) based on bipolar fuzzy soft set (BFS-set). BFS-topology is the generalization of the crisp topology. We discuss certain properties of BFS-topology including, BFS-closure, BFS-interior, BFS-exterior and BFS-frontier by utilizing BFS-points. We study the concept of BFS-subspace, BFS-neighbourhoods and BFS-base for BFS-topology with the help of detailed examples. Furthermore, we use BFS-topology in decision-making by applying an algorithm to deal with unpredictability.

Novel MCGDM with q-rung orthopair fuzzy soft sets and TOPSIS approach under q-Rung orthopair fuzzy soft topology

In this article, we study some concepts related to q-rung orthopair fuzzy soft sets (q-ROFS sets), together with their algebraic structure. We present operations on q-ROFSSs and their specific properties and elaborate them with real-life examples and tabular representations to develop influx of linguistic variables based on q-rung orthopair fuzzy soft (q-ROFS) information. We present an application of q-ROFS sets to multi-criteria group decision-making (MCGDM) process related to the university choice, accompanied by algorithm and flowchart. We develop q-ROFS TOPSIS method and q-ROFS VIKOR method as extensions of TOPSIS (a technique for ordering preference through the ideal solution) and VIKOR (Vlse Kriterijumska Optimizacija Kompromisno Resenje), respectively. Finally, we tackle a problem of construction business utilizing q-ROFS TOPSIS and q-ROFS VIKOR methods.

Hesitant fuzzy soft topology and its applications to multi-attribute group decision-making

The purpose of this research study is to extend the multi-attribute group decision-making (MAGDM) methods to hesitant fuzzy soft set (HFS-set), hesitant fuzzy soft topology (HFS-topology) and HFS-Hausdorff spaces in group decision-making environment, as HFS-set is more superior tool to capture vagueness, hesitancy and incompleteness in individual evaluations. In order to obtain optimal decisions in MAGDM, we present two algorithms based on hesitant fuzzy soft set and hesitant fuzzy soft topology. Lastly, we present MAGDM method by using HFS-Hausdorff space to deal with hesitancy and uncertainty. The developed methods have the ability to solve MADGM problems in which the assessment information on available alternatives, provided by the experts, is presented by hesitant fuzzy soft sets. Furthermore, the efficiency of proposed algorithms is shown by applying them to the real-world problems. We use reduct, optimum reduct, aggregate HFS-sets and weight vector according of given alternatives, priority of the attributes and customer demand for best MAGDM in the selection of car.

English

English

Separation Axioms of Interval-Valued Fuzzy Soft Topology via Quasi-Neighborhood Structure

In this study, we present the concept of the interval-valued fuzzy soft point and then introduce the notions of its neighborhood and quasi-neighborhood in interval-valued fuzzy soft topological spaces. Separation axioms in an interval-valued fuzzy soft topology, so-called q- T i for i = 0 , 1 , 2 , 3 , 4 , are introduced, and some of their basic properties are also studied.

Multi-criteria group decision making with Pythagorean fuzzy soft topology

Pythagorean fuzzy set (PFS) introduced by Yager (2013) is the extension of intuitionistic fuzzy set (IFS) introduced by Atanassov (1983). PFS is also known as IFS of type-2. Pythagorean fuzzy soft set (PFSS), introduced by Peng et al. (2015) and later studied by Guleria and Bajaj (2019) and Naeem et al. (2019), are very helpful in representing vague information that occurs in real world circumstances. In this article, we introduce the notion of Pythagorean fuzzy soft topology (PFS-topology) defined on Pythagorean fuzzy soft set (PFSS). We define PFS-basis, PFS-subspace, PFS-interior, PFS-closure and boundary of PFSS. We introduce Pythagorean fuzzy soft separation axioms, Pythagorean fuzzy soft regular and normal spaces. Furthermore, we present an application of PFSSs to multiple criteria group decision making (MCGDM) using choice value method in the real world problems which yields the optimum results for investment in the stock exchange. We also render an application of PFS-topology in medical diagnosis using TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution). The applications are accompanied by Algorithms, flow charts and statistical diagrams.

Generalized closed fuzzy soft sets in Čech fuzzy soft closure spaces

In this paper, we present the concept of generalized closed fuzzy soft sets in the Čech fuzzy soft closure spaces, termed g-closed fss’s, and investigate their basic properties. By using g-closed fss’s, we define a new fuzzy soft closure operator which is generates a new fuzzy soft topology finer than that induced from the Čech fuzzy soft closure operator. In addition, we define generalized Čech fuzzy soft continuous (respectively, irresolute) mapping by means of g-closed fss’s. As application of these sets, -Čech fuzzy soft closure spaces are introduced and discuses.

Bulanık Esnek Ditopolojiler Üzerine Bir Çalışma

In this study, we define fuzzy soft ditopological spaces as the generalization of soft ditopological spaces defined by Simsekler et. al. (2016). Fuzzy soft ditopological space is a combination of fuzzy soft topological and fuzzy soft cotopological spaces which are defined by two independent structures fuzzy soft open and fuzzy soft closed sets. Also we give fuzzy soft -continuity in fuzzy soft topology , fuzzy soft -continuity in fuzzy soft cotopology and by using these two types of continuity we finally define the fuzzy soft continuity in a fuzzy soft ditopology.