Fuzzy Soft Set Theory Research Articles

ALGORITHMS AND OPTIMAL CHOICE FOR POWER PLANTS BASED ON M-POLAR FUZZY SOFT SET DECISION MAKING CRITERIONS

Aim: The countries run to the energy, in this work we will put a suitable power plant. Therefore, we will develop a knowledge-based system in power plant to helps designers to find ways to improve the performance of a system in a many way. Methods: We extend the fuzzy soft set theory to fuzzy soft expert system and using FORTRAN program to put models to state suitable power plants stations. The way, (1) a fuzzication in which we transform real-valued inputs into fuzzy sets (2) take the reality values of Fossil power plant station, Nuclear power plant station, Wind power plant station, Solar power plant station, Hydro power plant station, Wave power plant station, Tidal range power plant, Biogas power plant, Coal under effective Renewable, Visual impact, Capital cost, Maintenance cost, Environmental impact, Green gas emissions, Implementation time, Cost Cent/Kwh, Danger of series accidents and Waste problem by use 𝑚-polar fuzzy soft set by using a technic transform to fuzzy soft expert system, (3) compute the corresponding resultant fuzzy soft set by using a combinations the parameters and talked the decision by algorithm to get the output data. Results: we shown the economic optimization of the power plants Fossil power plant station, Nuclear power plant station, Wind power plant station, Solar power plant station, Hydro power plant station, Wave power plant station, Tidal range power plant, Biogas power plant, Coal, under effective Renewable , Visual impact, Capital cost, Maintenance cost, Environmental impact, Green gas emissions, Implementation time, Cost Cent/Kwh, Danger of series accidents and Waste problem by use 𝑚-polar fuzzy soft set. Conclusion: In this work the energy from in the power plants is calculated based on model in m-polar fuzzy sets to determine the true system. The ways, first algorithms to state suitable power plants stations are introduced. In addition, we shown the economic optimization of the power plants Fossil power plant station, Nuclear power plant station, Wind power plant station, Solar power plant station, Hydro power plant station, Wave power plant station, Tidal range power plant, Biogas power plant, Coal, under effective Renewable , Visual impact, Capital cost, Maintenance cost, Environmental impact, Green gas emissions, Implementation time, Cost Cent/Kwh, Danger of series accidents and Waste problem by use 𝑚-polar fuzzy soft set.

On interval-valued fuzzy soft set theory applied to semigroups

In this paper, we focus on combining the theories of interval-valued fuzzy soft sets over semigroups, and establishing a new framework for interval-valued fuzzy soft semigroups. The aim of this manuscript is to apply interval-valued fuzzy soft set for dealing with several kinds of theories in semigroups. First, we present the concepts of interval-valued fuzzy soft sets, interval-valued fuzzy soft semigroups, interval-valued fuzzy soft ideals, interval-valued fuzzy soft quasi-ideals, interval-valued fuzzy soft interior ideals and interval-valued fuzzy soft bi-ideals. Meanwhile, some illustrative examples are given to show the rationality of the definitions introduced in this paper. Also, we prove that a non-empty subset of a semigroup S is a subsemigroup (left ideal, right ideal, ideal) of S if and only if the interval-valued fuzzy soft set over S is the interval-valued fuzzy soft subsemigroup (interval-valued fuzzy soft left ideal, interval-valued fuzzy soft right ideal, interval-valued fuzzy soft ideal) over S. Second, several new kinds of generalized fuzzy soft sets over semigroups are proposed, and related properties and mutual relationships are also investigated. Moreover, we study relation between quasi-ideals and interval-valued fuzzy soft quasi-ideals over semigroups. Finally, we obtain necessary and sufficient conditions of an interval-valued fuzzy soft ideal in order to be an interval-valued fuzzy soft interior ideal.

ON SOFT AND FUZZY SOFT RELATIONS WITH THEIR APPLICATIONS

In our day to day life we face many problems which are abstract or vague in nature. These problems cannot be solved only by using simple mathematical tools. To deal with such kind of problems a new technique popularly known as Fuzzy Set Theory was discovered. Fuzzy set is the generalization of crisp set and is used in almost every field of life including Medical Sciences, Business, Administration, Social Science and Operation Research. Later on, a new concept of parameterization of power set of the universal set was introduced. Consequently, Fuzzy Soft Set Theory was defined by embedding Fuzzy Set and Soft Set. In the present communication fuzzy binary relation is described and its applications are studied. The concepts of soft and fuzzy soft relations are also defined with their applications in decision making problems.

A combination of FAHP and fuzzy soft set theory method for solving MCDM problem in sports application

A combination of FAHP and fuzzy soft set theory method for solving MCDM problem in sports application

Application of fuzzy soft set theory and Hungarian method for assigning player's position

Application of fuzzy soft set theory and Hungarian method for assigning player's position

Fuzzy neutrosophic Soft Ideal Theory Fuzzy neutrosophic Soft Local Function and Generated Fuzzy neutrosophic Soft Topological Spaces

The purpose of this paper is to introduce the notion of fuzzy neutrosophic soft ideal in fuzzy neutrosophic soft set theory. The concept of fuzzy neutrosophic soft local function is also introduced. These concepts are discussed with a view to find new fuzzy neutrosophic soft topologies from the original one. The basic structure, especially a basis for such generated fuzzy neutrosophic soft topologies also studied here. Finally, the notion of compatibility of fuzzy neutrosophic soft ideals with fuzzy neutrosophic soft topologies is introduced and some equivalent conditions concerning this topic are established here

On statistical concepts of intuitionistic fuzzy soft set theory via utility

On statistical concepts of intuitionistic fuzzy soft set theory via utility

New Improved Normal Parameter Reduction Method for Fuzzy Soft Set

There are many redundant parameters in the actual decision-making process based on fuzzy soft sets. Kong et al. [Z. Kong, J. Ai, L. Wang, P. Li, L. Ma, and F. Lu, “New Normal Parameter Reduction Method in Fuzzy Soft Set Theory,” in IEEE Access, vol. 7, pp. 2986-2998, 2019] described the parameter reduction method with regard to four special dispensable sets based on score decision criteria. However, this method is complicated and has high computational complexity. This paper firstly gives some new calculation methods of comparison matrix, and then proposes a new improved normal parameter reduction method. The comparison results on two real-life datasets validate that the proposed algorithm reduces the complexity of the algorithm and greatly simplifies the process of parameter reduction compared with the algorithm of Kong et al.

New Operations on Interval-Valued Picture Fuzzy Set, Interval-Valued Picture Fuzzy Soft Set and Their Applications

An interval-valued picture fuzzy set (IVPFS) is one of the generalizations of an interval-valued fuzzy set to handle the uncertainties in the data during analysis. The aim of this paper is to introduce and study new operations of IVPFS, along with its properties, and examples. In addition, we present the notion of the interval-valued picture fuzzy soft set theory and investigated their properties. Several operations on such as subset, equal, complement, inf product, sup product, union, and intersection are defined over the interval-valued picture fuzzy soft set and discussed their basic properties. Furthermore, we construct an algorithm using an interval-valued picture fuzzy soft set to solve the decision-making problems and illustrate its applicability through a numerical example. From the study, we conclude that the proposed approach is viable in order to handle the uncertainties during the decision-making problems.

Data Analysis Approaches of Interval-Valued Fuzzy Soft Sets Under Incomplete Information

Interval-valued fuzzy soft set theory is a new and developing mathematical tool, which figures out a creative way aiming at dealing with uncertain and fuzzy data. Studies on decision making approaches and parameter reduction based on the complete interval-valued fuzzy soft sets became very active. However, we have to face up to a mount of incomplete data in real applications of interval-valued fuzzy soft sets. In this paper, we propose data analysis approaches of interval-valued fuzzy soft sets under incomplete information, which involves ignoring incomplete data when the percentage of missing entries is higher than the threshold and a filling approach for incomplete information while the percentage of missing entries is lower than the threshold. A suitable and practical case study demonstrates the implementation and validation of the proposed analysis approaches. The experimental results show that the overall accuracy estimation of the filling approach is up to 96.11%.

Application of Average fs-Aggregate Algorithm for Multi-criteria Decision Making in Real Life Problem

Generally in our day to day life we come across the real life situations when right decision making becomes difficult. In different fields like economics, social science, medical science, environment, where such complicacy arises and involves uncertainties. The conventional mathematical methods are unsuitable to solve such problems. To solve this problem, we are to find the various parameters related to the problem to use them to get the accurate result. So fuzzy soft set theory is the best mathematical tool for solving such problems using different techniques. In this research paper, we have taken a multi-criteria real life problem to select a suitable city which suits the best conditions as per the given parameters. For getting the solution, we used average fs-aggregation algorithm for using multi-criteria parameters.

Intuitionistic fuzzy parameterized fuzzy soft set theory and its application

This paper presents the opinion of intuitionistic fuzzy parameterized fuzzy soft set (IFP-FS set) by considering the images of approximate function in the fuzzy subsets of the set of universe of discourse rather than to a crisp subset. Some of the desired operations and relations of IFP-FS set are also considered in this study. A decision making approach based on the proposed IFP-FS set is used. Finally, an example is conducted which illustrates that the proposed approach can be use for many real life problems that include ambiguities and uncertainties.

Intertemporal Choice of Fuzzy Soft Sets

This paper first merges two noteworthy aspects of choice. On the one hand, soft sets and fuzzy soft sets are popular models that have been largely applied to decision making problems, such as real estate valuation, medical diagnosis (glaucoma, prostate cancer, etc.), data mining, or international trade. They provide crisp or fuzzy parameterized descriptions of the universe of alternatives. On the other hand, in many decisions, costs and benefits occur at different points in time. This brings about intertemporal choices, which may involve an indefinitely large number of periods. However, the literature does not provide a model, let alone a solution, to the intertemporal problem when the alternatives are described by (fuzzy) parameterizations. In this paper, we propose a novel soft set inspired model that applies to the intertemporal framework, hence it fills an important gap in the development of fuzzy soft set theory. An algorithm allows the selection of the optimal option in intertemporal choice problems with an infinite time horizon. We illustrate its application with a numerical example involving alternative portfolios of projects that a public administration may undertake. This allows us to establish a pioneering intertemporal model of choice in the framework of extended fuzzy set theories.

Neutrosophic Fuzzy Soft Game

The Soft set theory, originally proposed by Molodtsov, can be used as a general mathematical tool for dealing with uncertainity.This paper is devoted to the discussions of Neutrosophic fuzzy soft set. A new game modelis proposed and called Neutrosophicfuzzy soft game since it is based on Neutrosophic fuzzy soft set theory. We concentrate on discussing a class of two person zero-sum games with Neutrosophic fuzzy soft payoffs.The proposed scheme is illustrated by an example regarding the pure strategy problem.

Evaluation of the maintenance window scheme using fuzzy soft set theory

The maintenance window scheme (MWS) is one of the most important railway transportation organizational plans and plays an important role in ensuring railway operational safety. However, MWS setting is a very complicated process, and most countries currently do so with the help of a computer-aided decision system. In general, a decision system can generate multiple alternatives for MWS within an acceptable time. Therefore, how to choose the best option from the alternatives is a vital decision. This paper presents a novel framework for MWS evaluation based on the Chinese railway system. Specifically, the requirements of each department related to MWS setting are analysed, and we construct an evaluation indicator system for MWS based on the preferences of different departments. Then, we apply the fuzzy soft set theory to MWS evaluation, a method that not only effectively deals with evaluation of uncertain information, but also gives flexibility for experts to input their subjective judgment. Additionally, using the “AND” operation of soft set theory allows combing evaluation information from multiple evaluators to give comprehensive results. Finally, a case study illustrates the proposed framework, showing that the proposed evaluation indicator system and evaluation method are effective and practical.

Intuitionistic Fuzzy Soft Set Theory and Its Application in Medical Diagnosis

For finding coherent and logical solution to various real life problems containing uncertainty, impreciseness and vagueness, fuzzy soft set theory is gaining importance. Later on a theoretical study of the intuitionistic fuzzy soft set was developed. The combination of intuitionistic fuzzy set and intuitionistic fuzzy soft set are more useful for application point of view in the field wherever uncertainty due to vagueness appear in more complex form. In the present communication the concepts of fuzzy soft set and Intuitionistic fuzzy soft Setare defined as hybridization of fuzzy set and soft set theory. A new method of application of intuitionistic fuzzy soft set is studied in Medical Diagnosis following Sanchez’s approach. A hypothetical case study is also discussed in brief using the proposed method.

Novel scaled prioritized intuitionistic fuzzy soft interaction averaging aggregation operators and their application to multi criteria decision making

Intuitionistic fuzzy soft set (IFSS) theory is one of the successful extension of the soft set theory to deal the uncertainty by introducing the parametrization factor during the analysis. Under this environment, the present paper develops two new scaled prioritized averaging aggregation operators by considering the interaction between the membership degrees. Further, some shortcomings of the existing operators have been highlighted and overcome by the proposed operators. The principal advantage of the operators is that they consider the priority relationships between the parameters as well as experts. Furthermore, some properties based on these operators are discussed in detail. Then, we utilized these operators to solve decision-making problem and validate it with a numerical example.

Bonferroni mean aggregation operators under intuitionistic fuzzy soft set environment and their applications to decision-making

Intuitionistic fuzzy soft set (IFSS) theory is one of the successful extensions of soft set theory for handling the uncertainty in the data by introducing the parametrisation factor during the decision-making process as compared to the existing theories. Under this IFSS environment, the present paper developed some new Bonferroni mean(BM) and weighted BM averaging operator for aggregating the different preferences of the decision-maker. Some of its desirable properties have also been discussed in details. Further, a decision-making method based on proposed operators has been presented and then illustrated with a numerical example. A comparison analysis between the proposed and the existing measures under IFSS environment has been performed in terms of counter-intuitive cases for showing the validity of it.

Skin Disease analysis using Intuitionistic Fuzzy Set

Skin diseases occurs in different patterns due to wide ranges of factor such as climatic conditions, geographical locations, pollution, hygienic standards, age, level of health care and many more. These diseases cause a lot of distress in human health. Intuitionistic fuzzy and intuitionistic fuzzy soft set theory plays a major role in handling vague concepts and it has been applied in many fields. In this paper we aim at finding the age group in which maximum skin diseases occurs using the concept of intuitionistic fuzzy soft set by using AGEMSD measure.

An Approach to Data Reduction and Decision Making Problem by Hybridization of Fuzzy Soft Set and Graph Theory

An Approach to Data Reduction and Decision Making Problem by Hybridization of Fuzzy Soft Set and Graph Theory