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Artykuły w czasopismach na temat „Anti fuzzy soft set”

Autor: Grafiati

Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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1

V., Chinnadurai, and Arulmozhi K. "ANTI FUZZY SOFT GAMMA REGULAR SEMIGROUPS." International Journal of Scientific Research and Modern Education 2, no. 1 (2017): 159–70. https://doi.org/10.5281/zenodo.810156.

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In this paper, we have introduce the notion of anti fuzzy soft -semigroups, anti fuzzy soft -ideal, bi-ideal, interior ideal-regular, soft-regular anti fuzzy soft-regular and obtain some interesting properties results and discusse in this paper

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Alsager,, K. M. "n-polar Z-hesitant Complementary Fuzzy Soft Set in BCK/BCI-Algebras." Malaysian Journal of Mathematical Sciences 17, no. 4 (2023): 629–44. http://dx.doi.org/10.47836/mjms.17.4.07.

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This paper introduces an innovative concept known as n-polar Z-hesitant Anti-Fuzzy Soft Sets (MZHAFSs) within the framework of BCK/BCI-algebras. Soft set theory originates in the captivating field of fuzzy set theory. Our approach is a harmonious synthesis of n-polar anti-fuzzy set theory, soft set models, and Z-hesitant anti-fuzzy sets, skillfully applied within the framework of BCK/BCI-algebras. This effort leads to the introduction of a new variant of fuzzy sets termed MZHAFSs (n-polar Z-hesitant anti-fuzzy soft sets) in the context of BCK/BCI-algebras. Additionally, we elucidate the concep

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3

Alshehri, Halimah, and Noura Alshehri. "Hesitant Anti-Fuzzy Soft Set in BCK-Algebras." Mathematical Problems in Engineering 2017 (2017): 1–13. http://dx.doi.org/10.1155/2017/3634258.

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We introduce the notions of hesitant anti-fuzzy soft set (subalgebras and ideals) and provide relation between them. However, we study new types of hesitant anti-fuzzy soft ideals (implicative, positive implicative, and commutative). Also, we stated and proved some theorems which determine the relationship between these notions.

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4

Alshehri, Noura, and Halimah Alshehri. "Corrigendum to “Hesitant Anti-Fuzzy Soft Set in BCK-Algebras”." Mathematical Problems in Engineering 2017 (2017): 1. http://dx.doi.org/10.1155/2017/6523784.

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HUANG, CHONGFU. "INFORMATION DIFFUSION TECHNIQUES AND SMALL-SAMPLE PROBLEM." International Journal of Information Technology & Decision Making 01, no. 02 (2002): 229–49. http://dx.doi.org/10.1142/s0219622002000142.

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Strong interests in the small-sample problem have been given towards for establishing several information diffusion techniques for pattern recognition. In this paper, we review and formalize three techniques: the soft histogram, the self-study discrete regression, and the interior-outer-set model. To promote the development of this area, in this paper we suggest two open topics: the anti-accuracy principle and the digital image compression technique based on the fuzzy if-then rules extracted by using information matrix technique.

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6

Kharola, Ashwani, and Pravin P. Patil. "A Comparative Study for Position Regulation and Anti-Swing Control of Highly Non-Linear Double Inverted Pendulum (DIP) System Using Different Soft Com." International Journal of Fuzzy System Applications 6, no. 2 (2017): 59–81. http://dx.doi.org/10.4018/ijfsa.2017040104.

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This paper presents a comparative analysis for stabilization and control of highly non-linear, complex and multi-variable Double Inverted Pendulum on cart. A Matlab-Simulink model of DIP has been built using governing mathematical equations. The objective is to control both the pendulums at vertical position while cart is free to move in horizontal direction. The control of DIP was achieved using three different soft-computing techniques namely Fuzzy logic reasoning, Neural networks (NN's) and Adaptive neuro fuzzy inference system (ANFIS). The results show that the ANFIS controller is more eff

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7

Adam, Fatma, and Nasruddin Hassan. "Q-fuzzy soft set." Applied Mathematical Sciences 8 (2014): 8689–95. http://dx.doi.org/10.12988/ams.2014.410865.

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8

Alkhazaleh, Shawkat, Abdul Razak Salleh, and Nasruddin Hassan. "Possibility Fuzzy Soft Set." Advances in Decision Sciences 2011 (September 8, 2011): 1–18. http://dx.doi.org/10.1155/2011/479756.

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We introduce the concept of possibility fuzzy soft set and its operation and study some of its properties. We give applications of this theory in solving a decision-making problem. We also introduce a similarity measure of two possibility fuzzy soft sets and discuss their application in a medical diagnosis problem.

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9

G., Muhiuddin A. Mahboob and M. Balamurugan. "Hesitant anti-intuitionistic fuzzy soft commutative ideals of BCK-algebras." Annals of Communications in Mathematics 3, no. 2 (2020): 158–70. https://doi.org/10.5281/zenodo.10044331.

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In this paper, the notions of hesitant anti-intuitionistic fuzzy soft BCI-commutative ideals of BCI-algebras and hesitant anti-intuitionistic fuzzy soft subcommutative ideals of BCK-algebras are introduced and their related properties are investigate. Relations between a hesitant anti-intuitionistic fuzzy soft ideals and hesitant anti-intuitionistic fuzzy soft BCI-commutative ideals are discussed. Conditions for a hesitant anti-intuitionistic fuzzy soft ideal to be a hesitant anti-intuitionistic fuzzy soft BCIcommutative ideal are provided. Finally, it is proved that a hesitant anti-intuitioni

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10

Borah, Manash, and Bipan Hazarika. "Soft ideal topological space and mixed fuzzy soft ideal topological space." Boletim da Sociedade Paranaense de Matemática 37, no. 1 (2017): 141–51. http://dx.doi.org/10.5269/bspm.v37i1.29647.

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In this paper we introduce fuzzy soft ideal and mixed fuzzy soft ideal topological spaces and some properties of this space. Also we introduce fuzzy soft $I$-open set, fuzzy soft $\alpha$-$I$-open set, fuzzy soft pre-$I$-open set, fuzzy soft semi-$I$-open set and fuzzy soft $\beta$-$I$-open set and discuss some of their properties.

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11

Singh, Seema, and D. S. Hooda. "ON SOFT AND FUZZY SOFT RELATIONS WITH THEIR APPLICATIONS." Jnanabha 50, no. 01 (2020): 102–14. http://dx.doi.org/10.58250/jnanabha.2020.50112.

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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

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12

Alkhazaleh, Shawkat, and Abdul Razak Salleh. "Generalised Interval-Valued Fuzzy Soft Set." Journal of Applied Mathematics 2012 (2012): 1–18. http://dx.doi.org/10.1155/2012/870504.

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We introduce the concept of generalised interval-valued fuzzy soft set and its operations and study some of their properties. We give applications of this theory in solving a decision making problem. We also introduce a similarity measure of two generalised interval-valued fuzzy soft sets and discuss its application in a medical diagnosis problem: fuzzy set; soft set; fuzzy soft set; generalised fuzzy soft set; generalised interval-valued fuzzy soft set; interval-valued fuzzy set; interval-valued fuzzy soft set.

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13

Oriza, Sri Delvia, and Nova Noliza Bakar. "HIMPUNAN LEMBUT KABUR HESITANT DAN APLIKASINYA DALAM PENGAMBILAN KEPUTUSAN." Jurnal Matematika UNAND 6, no. 3 (2017): 23. http://dx.doi.org/10.25077/jmu.6.3.23-31.2017.

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Abstract. Molodstov's soft set theory is a newly emerging mathematical tool to handleuncertainty. The soft set theory can be combined with other mathematical theory like asfuzzy set theory. This paper aims to extend hesitant fuzzy set to hesitant fuzzy soft sets.Then, the complement, "AND", "OR", union, intersection operations and De Morgan'slaw are dened on hesitant fuzzy soft sets. Finally, with the help of level soft set, thehesitant fuzzy soft sets are applied to a decision making problem.Kata Kunci: Soft set, Fuzzy set, Hesitant fuzzy set, Hesitant fuzzy soft set, Level softset

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14

Hassan, Nasruddin, and Yousef Al-Qudah. "Fuzzy parameterized complex multi-fuzzy soft set." Journal of Physics: Conference Series 1212 (April 2019): 012016. http://dx.doi.org/10.1088/1742-6596/1212/1/012016.

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15

Zhang, Zhiming. "The Parameter Reduction of Fuzzy Soft Sets Based on Soft Fuzzy Rough Sets." Advances in Fuzzy Systems 2013 (2013): 1–12. http://dx.doi.org/10.1155/2013/197435.

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Fuzzy set theory, rough set theory, and soft set theory are three effective mathematical tools for dealing with uncertainties and have many wide applications both in theory and practise. Meng et al. (2011) introduced the notion of soft fuzzy rough sets by combining fuzzy sets, rough sets, and soft sets all together. The aim of this paper is to study the parameter reduction of fuzzy soft sets based on soft fuzzy rough approximation operators. We propose some concepts and conditions for two fuzzy soft sets to generate the same lower soft fuzzy rough approximation operators and the same upper sof

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16

Al-shami, Tareq M., José Carlos R. Alcantud, and Abdelwaheb Mhemdi. "New generalization of fuzzy soft sets: $ (a, b) $-Fuzzy soft sets." AIMS Mathematics 8, no. 2 (2023): 2995–3025. http://dx.doi.org/10.3934/math.2023155.

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<abstract><p>Many models of uncertain knowledge have been designed that combine expanded views of fuzziness (expressions of partial memberships) with parameterization (multiple subsethood indexed by a parameter set). The standard orthopair fuzzy soft set is a very general example of this successful blend initiated by fuzzy soft sets. It is a mapping from a set of parameters to the family of all orthopair fuzzy sets (which allow for a very general view of acceptable membership and non-membership evaluations). To expand the scope of application of fuzzy soft set theory, the restricti

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17

K. Japhia Tino Mercy. "Novel Picture of Topological Spaces in the Frame of Fuzzy Soft Sequential Sets." Communications on Applied Nonlinear Analysis 31, no. 8s (2024): 87–94. http://dx.doi.org/10.52783/cana.v31.1458.

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The goal of this paper is to introduce fuzzy soft sequential topological spaces over the universal set via fuzzy soft sequential set by merging the concept of fuzzy soft set and sequential set. We provide a comprehensive study of their properties and explore a relationship between fuzzy soft topology and fuzzy soft sequential topology. We offers a new outlook on the theory of fuzzy soft sequential neighborhood of a fuzzy soft sequential set and we investigate the quasi-coincident relation.

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18

Singh, Shiva Raj, Surendra Singh Gautam, and Abhishekh . "An Intuitionistic Fuzzy Soft Set Theoretic Approach to Decision Making Problems." MATEMATIKA 34, no. 1 (2018): 49–58. http://dx.doi.org/10.11113/matematika.v34.n1.890.

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In general most of real life problem of decision making involve imprecise parameters. In recent past the major emphasis of research workers in this area have been to develop the reliable models to deal with such imprecision and vagueness effectively. Several theories have been developed such as fuzzy set theory, interval valued fuzzy set, intuitionistic fuzzy set, and interval valued intuitionistic fuzzy set, rough set and soft set. The primary objectives of all the above developed theories are to deal with various kinds of uncertainty, imprecision and vagueness but unfortunately every theory

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19

Woldie, Masresha Wassie, Jejaw Demamu Mebrat, and Mihret Alamneh Taye. "New Approaches of Generalised Fuzzy Soft sets on fuzzy Codes and Its Properties on Decision-Makings." F1000Research 13 (December 2, 2024): 1461. https://doi.org/10.12688/f1000research.158747.1.

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Background Several scholars defined the concepts of fuzzy soft set theory and their application on decision-making problem. Based on this concept, researchers defined the generalised fuzzy soft set and its applications. However, to the best of the author’s knowledge, the generalised fuzzy soft set has not been dealing with in the generalised fuzzy soft code set. In this paper, we introduce the notion of generalised fuzzy soft code set and its application. Methods The theory of fuzzy soft sets and its application, generalised fuzzy soft sets and fuzzy codes in different years were studied with

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20

Woldie, Masresha Wassie, Jejaw Demamu Mebrat, and Mihret Alamneh Taye. "New Approaches of Generalised Fuzzy Soft sets on fuzzy Codes and Its Properties on Decision-Makings." F1000Research 13 (April 9, 2025): 1461. https://doi.org/10.12688/f1000research.158747.2.

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Background Several scholars defined the concepts of fuzzy soft set theory and their application on decision-making problem. Based on this concept, researchers defined the generalised fuzzy soft set and its applications. However, to the best of the author’s knowledge, the generalised fuzzy soft set has not been dealing with in the generalised fuzzy soft code set. In this paper, we introduce the notion of generalised fuzzy soft code set and its application. Methods The theory of fuzzy soft sets and its application, generalised fuzzy soft sets and fuzzy codes in different years were studied with

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21

Shahzadi, Sundas, Musavarah Sarwar, and Muhammad Akram. "Decision-Making Approach with Fuzzy Type-2 Soft Graphs." Journal of Mathematics 2020 (November 17, 2020): 1–25. http://dx.doi.org/10.1155/2020/8872446.

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Molodtsov’s theory of soft sets is free from the parameterizations insufficiency of fuzzy set theory. Type-2 soft set as an extension of a soft set has an essential mathematical structure to deal with parametrizations and their primary relationship. Fuzzy type-2 soft models play a key role to study the partial membership and uncertainty of objects along with underlying and primary set of parameters. In this research article, we introduce the concept of fuzzy type-2 soft set by integrating fuzzy set theory and type-2 soft set theory. We also introduce the notions of fuzzy type-2 soft graphs, re

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22

Bashir, Maruah. "Possibility Fuzzy Soft Expert Set." Open Journal of Applied Sciences 02, no. 04 (2012): 208–11. http://dx.doi.org/10.4236/ojapps.2012.24b047.

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23

Bashir, Maruah, Abdul Razak Salleh, and Shawkat Alkhazaleh. "Possibility Intuitionistic Fuzzy Soft Set." Advances in Decision Sciences 2012 (March 13, 2012): 1–24. http://dx.doi.org/10.1155/2012/404325.

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Possibility intuitionistic fuzzy soft set and its operations are introduced, and a few of their properties are studied. An application of possibility intuitionistic fuzzy soft sets in decision making is investigated. A similarity measure of two possibility intuitionistic fuzzy soft sets has been discussed. An application of this similarity measure in medical diagnosis has been shown.

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24

Bashir, Maruah, and Abdul Razak Salleh. "Fuzzy Parameterized Soft Expert Set." Abstract and Applied Analysis 2012 (2012): 1–15. http://dx.doi.org/10.1155/2012/258361.

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In 2011 Alkhazaleh and Salleh introduced the concept of soft expert set and gave an application in a decision-making problem. In this paper we introduce the concept of fuzzy parameterized soft expert set by giving an important degree for each element in the set of parameters. We also study its properties and define its basic operations, namely, complement, union, intersection, AND, and OR. Finally, we give an application in decision making.

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25

Hazaymeh, Ayman A., Ismail B. Abdullah, Zaid T. Balkhi, and Rose I. Ibrahim. "Generalized Fuzzy Soft Expert Set." Journal of Applied Mathematics 2012 (2012): 1–22. http://dx.doi.org/10.1155/2012/328195.

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In 2011 Alkhazaleh and Salleh defined the concept of soft expert sets where the user can know the opinion of all the experts in one model and give an application of this concept in decision-making problems. Also, they introduced the concept of the fuzzy soft expert set as a combination between the soft expert set and the fuzzy set. In 2010 Majumdar and Samanta presented the concept of a generalized fuzzy soft sets. The purpose of this paper is to combine the work of Alkhazaleh and Salleh (2011) and Majumdar and Samanta (2010), from which we can obtain a new concept: generalized fuzzy soft expe

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26

Faried, Nashat, Mohamed S. S. Ali, and Hanan H. Sakr. "On Fuzzy Soft Linear Operators in Fuzzy Soft Hilbert Spaces." Abstract and Applied Analysis 2020 (July 31, 2020): 1–13. http://dx.doi.org/10.1155/2020/5804957.

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Due to the difficulty of representing problem parameters fuzziness using the soft set theory, the fuzzy soft set is regarded to be more general and flexible than using the soft set. In this paper, we define the fuzzy soft linear operator T~ in the fuzzy soft Hilbert space H~ based on the definition of the fuzzy soft inner product space U~,·,·~ in terms of the fuzzy soft vector v~fGe modified in our work. Moreover, it is shown that ℂnA, ℝnA and ℓ2A are suitable examples of fuzzy soft Hilbert spaces and also some related examples, properties and results of fuzzy soft linear operators are introdu

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27

Lu, Hanchuan, Ahmed Mostafa Khalil, W. Alharbi, and M. A. El-Gayar. "A new type of generalized picture fuzzy soft set and its application in decision making." Journal of Intelligent & Fuzzy Systems 40, no. 6 (2021): 12459–75. http://dx.doi.org/10.3233/jifs-201706.

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In this article, we propose a novel concept of the generalized picture fuzzy soft set by combining the picture fuzzy soft set and the fuzzy parameter set. For possible applications, we explain five kinds of operations (e.g., subset, equal, union, intersection, and complement) based on generalized picture fuzzy soft sets. Then, we establish several theoretical operations of generalized picture fuzzy soft sets. In addition, we present the new type by using the AND operation of the generalized picture fuzzy soft set for fuzzy decision-making and clarify its applicability with a numerical example.

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Hijriati, Na'imah, Irma Sari Yulianti, Dewi Sri Susanti, and Dewi Anggraini. "THE CONSTRUCTION OF SOFT SETS FROM FUZZY SUBSETS." BAREKENG: Jurnal Ilmu Matematika dan Terapan 17, no. 3 (2023): 1473–82. http://dx.doi.org/10.30598/barekengvol17iss3pp1473-1482.

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Molodtsov introduced the concept of soft sets formed from fuzzy subsets in 1999. The soft set formed from a fuzzy subset is a particular form of a soft set on its parameter set. On a soft set formed from a fuzzy subset, the parameter used is the image of a fuzzy subset which is then mapped to the collection of all subsets of a universal set. This research explains the construction of soft sets formed from fuzzy subsets. We provide the sufficient condition that a soft set formed from a fuzzy subset is a subset of another soft set. Also, give some properties of the soft sets formed from a fuzzy

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29

Aygünoğlu, Abdülkadir, Ebru Aydoğdu, and Halis Aygün. "Fuzzy soft metric and fuzzifying soft topology induced by fuzzy soft metric." Filomat 33, no. 2 (2019): 645–53. http://dx.doi.org/10.2298/fil1902645a.

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Our main goal with this paper is to construct soft topology and fuzzifying soft topology induced by fuzzy soft metric. For this, we present fuzzy soft metric spaces compatible to soft set theory and studied some of its basic properties. Then we investigate soft topological structures induced by fuzzy soft metrics.

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30

Khalil, Ahmed Mostafa, Dunqian Cao, Abdelfatah Azzam, Florentin Smarandache, and Wedad R. Alharbi. "Combination of the Single-Valued Neutrosophic Fuzzy Set and the Soft Set with Applications in Decision-Making." Symmetry 12, no. 8 (2020): 1361. http://dx.doi.org/10.3390/sym12081361.

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In this article, we propose a novel concept of the single-valued neutrosophic fuzzy soft set by combining the single-valued neutrosophic fuzzy set and the soft set. For possible applications, five kinds of operations (e.g., subset, equal, union, intersection, and complement) on single-valued neutrosophic fuzzy soft sets are presented. Then, several theoretical operations of single-valued neutrosophic fuzzy soft sets are given. In addition, the first type for the fuzzy decision-making based on single-valued neutrosophic fuzzy soft set matrix is constructed. Finally, we present the second type b

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31

SRIVASTAVA, JULEE, and SUDHIR MADDHESHIYA. ""D-Fuzzy set and its applications in decision making problems"." Creative Mathematics and Informatics 31, no. 1 (2022): 121–34. http://dx.doi.org/10.37193/cmi.2022.01.12.

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"In this paper we have presented an approach to deal with decision making problems. For this purpose we have constructed a fuzzy set, namely D-fuzzy set, for a soft set. This concept of D-fuzzy set will also be used when the information is given in form of weighted soft set, fuzzy soft set or weighted fuzzy soft set. Further we will apply this method when there are more than one observer. We will define such sets as multi-observer soft set, multi-observer weighted soft set etc."

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32

Kazancı, Osman, Sarka Hoskova-Mayerova, and Bijan Davvaz. "Algebraic Hyperstructure of Multi-Fuzzy Soft Sets Related to Polygroups." Mathematics 10, no. 13 (2022): 2178. http://dx.doi.org/10.3390/math10132178.

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The combination of two elements in a group structure is an element, while, in a hypergroup, the combination of two elements is a non-empty set. The use of hypergroups appears mainly in certain subclasses. For instance, polygroups, which are a special subcategory of hypergroups, are used in many branches of mathematics and basic sciences. On the other hand, in a multi-fuzzy set, an element of a universal set may occur more than once with possibly the same or different membership values. A soft set over a universal set is a mapping from parameters to the family of subsets of the universal set. I

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Yolcu, Adem. "Bipolar Spherical Fuzzy Soft Topology with Applications to Multi-Criteria Group Decision-Making in Buildings Risk Assessment." Symmetry 14, no. 11 (2022): 2362. http://dx.doi.org/10.3390/sym14112362.

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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 fun

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Selvakumari, K., and S. Lavanya. "Neutrosophic Fuzzy Soft Game." International Journal of Engineering & Technology 7, no. 3.34 (2018): 667. http://dx.doi.org/10.14419/ijet.v7i3.34.19412.

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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.

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Balamurugan, Manivannan, Nazek Alessa, Karuppusamy Loganathan, and M. Sudheer Kumar. "Bipolar Intuitionistic Fuzzy Soft Ideals of BCK/BCI-Algebras and Its Applications in Decision-Making." Mathematics 11, no. 21 (2023): 4471. http://dx.doi.org/10.3390/math11214471.

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In this paper, we merge the concepts of soft set theory and a bipolar intuitionistic fuzzy set. A bipolar intuitionistic fuzzy soft ideal in a BCK-algebra is defined as a soft set over the set of elements in the BCK-algebra, with each element associated with an intuitionistic fuzzy set. This relationship captures degrees of uncertainty, hesitancy, and non-membership degrees within the context of BCK-algebras. We investigate basic operations on bipolar intuitionistic fuzzy soft ideals such as union, intersection, AND, and OR. The intersection, union, AND, and OR of two bipolar intuitionistic fu

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Sari, Fitria Winda. "Himpunan Kabur Lembut Berparameter Kabur dan Aplikasinya." Jurnal Matematika UNAND 4, no. 4 (2019): 173. http://dx.doi.org/10.25077/jmu.4.4.173-185.2015.

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Pada tulisan ini akan diperkenalkan Himpunan Kabur Lembut Berparameter Kabur (FPSF) dan beberapa sifat-sifat aljabarnya. Selanjutnya juga diperkenalkan operator aggregate dari himpunan FPSF, yang digunakan untuk pengambilan keputusan. Pada akhirnya dengan menerapkan himpunan FPSF dan operator aggregate FPSF, didapatkan algoritma dalam pengambilan keputusan yang digunakan untuk membuat model peringatan banjir dan cara memilih juri yang terbaik dalam memberikan penilaian pada seorang peserta lomba.Kata Kunci: Soft Set, Fuzzy Set, Fuzzy Soft Set, Fuzzy Parameterized Soft Set, Fuzzy Parameterized

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Alkhazaleh, Shawkat, and Abdul Razak Salleh. "Fuzzy Soft Multiset Theory." Abstract and Applied Analysis 2012 (2012): 1–20. http://dx.doi.org/10.1155/2012/350603.

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In 1999 Molodtsov introduced the concept of soft set theory as a general mathematical tool for dealing with uncertainty. Alkhazaleh et al. in 2011 introduced the definition of a soft multiset as a generalization of Molodtsov's soft set. In this paper we give the definition of fuzzy soft multiset as a combination of soft multiset and fuzzy set and study its properties and operations. We give examples for these concepts. Basic properties of the operations are also given. An application of this theory in decision-making problems is shown.

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Anwar, Anwar, and Ayman A. Hazaymeh. "Time Fuzzy Parameterized Fuzzy Soft Expert Sets." International Journal of Neutrosophic Science 25, no. 4 (2025): 101–21. https://doi.org/10.54216/ijns.250409.

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Finally In this study, we define parameterized time fuzzy soft expert set (PTFSES) as an extension of fuzzy soft set. Additionally, we will clarify and investigate the characteristics of its primary operation (complement, union intersection, ”AND” and ”OR”). , we’ll apply this approach to decision-making difficulties.

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Iampan, Aiyared, and N. Rajesh. "Characterizing (∈, ∈∨q)-Anti-Intuitionistic Fuzzy Soft UP (BCC)-Subalgebras of UP (BCC)-Algebras." International Journal of Analysis and Applications 21 (October 23, 2023): 115. http://dx.doi.org/10.28924/2291-8639-21-2023-115.

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In this paper, the concepts of (∈, ∈∨q)-anti-intuitionistic fuzzy soft UP (BCC)-subalgebras and (∈, ∈)-anti-intuitionistic fuzzy soft UP (BCC)-subalgebras of UP (BCC)-algebras are introduced and studied. The UP (BCC)-homomorphic image and inverse image are investigated in (∈, ∈∨q)-anti-intuitionistic fuzzy soft UP (BCC)-subalgebras of UP (BCC)-algebras. Characterizations of (∈, ∈∨q)-anti-intuitionistic fuzzy soft UP (BCC)-subalgebras of UP (BCC)-algebras are discussed.

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P., Thirunavukarasu, and Suresh R. "Parameterized Soft Complex Fuzzy Sets." Journal of Progressive Research in Mathematics 4, no. 2 (2015): 303–8. https://doi.org/10.5281/zenodo.3980480.

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In this paper, we presents a new concept of parameterized soft complex fuzzy set (pscf-set) which is generalized from the innovative concept of a complex fuzzy set by adding phase term to the definition of fuzzy set. Various operators with examples of pscf-set provided in this paper. We then define a pscf-set aggregation operator.

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Zhang, Zhiming, and Shouhua Zhang. "Type-2 Fuzzy Soft Sets and Their Applications in Decision Making." Journal of Applied Mathematics 2012 (2012): 1–35. http://dx.doi.org/10.1155/2012/608681.

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Molodtsov introduced the theory of soft sets, which can be used as a general mathematical tool for dealing with uncertainty. This paper aims to introduce the concept of the type-2 fuzzy soft set by integrating the type-2 fuzzy set theory and the soft set theory. Some operations on the type-2 fuzzy soft sets are given. Furthermore, we investigate the decision making based on type-2 fuzzy soft sets. By means of level soft sets, we propose an adjustable approach to type-2 fuzzy-soft-set based decision making and give some illustrative examples. Moreover, we also introduce the weighted type-2 fuzz

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Abdullah, Saleem, Wafa S. Al Shammakh, Tahir Mahmood, and Muhammad Shahzad. "Fuzzy soft set over a fuzzy topological space." International Journal of Machine Learning and Cybernetics 7, no. 3 (2015): 491–99. http://dx.doi.org/10.1007/s13042-015-0420-z.

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Alhussain, Zahraa F. Abd, and Asmhan F. Hassan. "N-ary relation fuzzy-soft set." Journal of Interdisciplinary Mathematics 26, no. 7 (2023): 1449–54. http://dx.doi.org/10.47974/jim-1564.

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We introduce in this paper a novel idea (new model) of fuzzy-soft-sets via linking the Binary, Ternary and N-ary relation soft-sets definitions together with the fuzzy-sets definitions for power sets and then arises the novel kinds which are named as (Binary relation, Ternary relation, N-ary relation fuzzy-soft sets), we will denote for them as (B-R-F-S), (T-R-F-S) and (N-R-F-S) resp. , which are more useful and functional to create theoretical and practical works also to make some new studies (new ideas) cutting-edge the fuzzy-soft-set theory. We focus on the main processess on N-ary relation

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et al., Muhiuddin. "Fuzzy soft set theory applied to commutative ideals of BCK-algebras." International Journal of ADVANCED AND APPLIED SCIENCES 8, no. 6 (2021): 48–56. http://dx.doi.org/10.21833/ijaas.2021.06.006.

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In the present paper, we apply the fuzzy soft set theory to commutative ideals of BCK-algebras. In fact, the notion of fuzzy soft commutative ideals over BCK-algebras is introduced, and related properties are investigated. Relations between fuzzy soft ideals and fuzzy soft commutative ideals are discussed, and conditions for a fuzzy soft ideal to be a fuzzy soft commutative ideal are provided. The “AND” operation, “extended intersection” and “union” of fuzzy soft (commutative) ideals are studied. Furthermore, characterizations of fuzzy soft (commutative) ideals are considered.

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Garg, Harish, Fathima Perveen P A, Sunil Jacob John, and Luis Perez-Dominguez. "Spherical Fuzzy Soft Topology and Its Application in Group Decision-Making Problems." Mathematical Problems in Engineering 2022 (April 26, 2022): 1–19. http://dx.doi.org/10.1155/2022/1007133.

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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 se

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F.H., Khedr, A. Abd Allah M., and S. Malfi M. "Fuzzy soft separation axioms in fuzzy soft topological spaces." Journal of Progressive Research in Mathematics 15, no. 2 (2019): 2668–81. https://doi.org/10.5281/zenodo.3996878.

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Fuzzy soft separation axioms was introduced by Mahanta and Das ([5]) using the definitions of a `fuzzy soft point' and `the complement of a fuzzy soft point is a fuzzy soft point', and `distinct of fuzzy soft points' in there sense.  In this paper we, introduce fuzzy soft separation axioms in terms of the modified definitions of a `fuzzy soft point', the complement of a fuzzy soft point is a fuzzy soft set' and `distinct of fuzzy soft points'([7]). Also, we study some of their properties. Finally, we discuss fuzzy soft topological property for such spaces. 

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Khan, Muhammad Jabir, Poom Kumam, Peide Liu, Kumam, and Ashraf. "A Novel Approach to Generalized Intuitionistic Fuzzy Soft Sets and Its Application in Decision Support System." Mathematics 7, no. 8 (2019): 742. http://dx.doi.org/10.3390/math7080742.

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The basic idea underneath the generalized intuitionistic fuzzy soft set is very constructive in decision making, since it considers how to exploit an extra intuitionistic fuzzy input from the director to make up for any distortion in the information provided by the evaluation experts, which is redefined and clarified by F. Feng. In this paper, we introduced a method to solve decision making problems using an adjustable weighted soft discernibility matrix in a generalized intuitionistic fuzzy soft set. We define the threshold functions like mid-threshold, top-bottom-threshold, bottom-bottom-thr

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Hussein, Boushra Y., and Sara F. Hassan. "Characterization on fuzzy soft ordered Banach algebra." Boletim da Sociedade Paranaense de Matemática 40 (February 6, 2022): 1–8. http://dx.doi.org/10.5269/bspm.51387.

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In this paper, we define fuzzy soft ordered Banach algebra with fuzzy soft algebra cone, and introduce the character on fuzzy soft ordered Banach algebra in both cases real and complex. Also, we deduce some of its basic properties and we define a new concept which is a maximal fuzzy soft algebra cone and showing that the set of all fuzzy soft character is isomorphism to the set of all maximal fuzzy soft algebra cone. we prove that the set of all real characters is convex and extreme point, we applied Gelfand- Mazur theorem on fuzzy soft Banach algebra, we showed that character (the set of all

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Edeghagba, Elijah E., and Umar F. Muhammad. "On Full Fuzzy Parameterized Soft Set." International Journal of Mathematical Analysis and Optimization: Theory and Applications 7, no. 2 (2022): 76–87. http://dx.doi.org/10.52968/28302774.

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Some Years back, researchers made attempts in trying to fuzzify set of parameters of soft set. In this paper, we consider a review of “fuzzy parameterized soft set", and improve it by introducing a way to fully fuzzify the set of parameters of soft set. We define the concept “full fuzzy parametrized soft set" and study some of its basic operations. We also illustrate the concept with example.

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Farhadinia, B. "Multicriteria Decision Making Method Based on the Higher Order Hesitant Fuzzy Soft Set." International Scholarly Research Notices 2014 (August 21, 2014): 1–11. http://dx.doi.org/10.1155/2014/873454.

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The main goal of this contribution is to introduce the concept of higher order hesitant fuzzy soft set as an extension of fuzzy soft set that encompasses most of the existing extensions of fuzzy soft set as special cases. Furthermore, this new concept provides us with a method for dealing with multicriteria fuzzy decision making problems which are difficult to explain in other existing extensions of fuzzy soft set theory, especially when problems involve parameters with different-dimensional levels.

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