On Applications of Fuzzy Soft and Intuitionistic Fuzzy Soft Sets in Dimension Reduction and Medical Diagnosis

2021 ◽  
pp. 87-101
Author(s):  
D. S. Hooda
Keyword(s):  
Dimension Reduction ◽  
Medical Diagnosis ◽  
Soft Sets ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Soft Sets ◽  
Intuitionistic Fuzzy Soft Sets

Refined Neutrosophic Sets and Refined Neutrosophic Soft Sets

2016 ◽  
pp. 321-343 ◽  
Author(s):  
Irfan Deli
Keyword(s):  
Fuzzy Sets ◽  
Medical Diagnosis ◽  
Real Life ◽  
Intuitionistic Fuzzy Sets ◽  
Soft Sets ◽  
Neutrosophic Sets ◽  
Intuitionistic Fuzzy ◽  
Formal Framework ◽  
Fuzzy Soft Sets ◽  
Intuitionistic Fuzzy Soft Sets

Refined neutrosophic sets (RNS) are a generalization of a neutrosophic sets, intuitionistic fuzzy sets, fuzzy sets, intuitionistic fuzzy multi-sets and fuzzy multi-sets. Similarly, refined neutrosophic soft sets (RNSS) are a generalization of a neutrosophic soft sets, intuitionistic fuzzy soft sets, fuzzy soft sets, intuitionistic fuzzy soft multi-sets and fuzzy soft multi-sets. These sets are a powerful general formal framework that has been proposed to present uncertainty, imprecise, incomplete, inaccurate and inconsistent information which exist in real life. This chapter will survey concept of RNS and concept of RNSS with basic definitions and will present an efficient approach for both RNS and RNSS. Also, the chapter will introduce an application of RNS in medical diagnosis problem, pattern recognition and an application of RNSS in decision making to illustrate the advantage of the proposed approach.

scholarly journals Possibility Intuitionistic Fuzzy Soft Set

2012 ◽  
Vol 2012 ◽  
pp. 1-24 ◽  
Author(s):  
Maruah Bashir ◽  
Abdul Razak Salleh ◽  
Shawkat Alkhazaleh
Keyword(s):  
Decision Making ◽  
Similarity Measure ◽  
Medical Diagnosis ◽  
Soft Set ◽  
Fuzzy Soft Set ◽  
Soft Sets ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Soft Sets ◽  
Intuitionistic Fuzzy Soft Sets

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.

A group medical diagnosis model based on intuitionistic fuzzy soft sets

2019 ◽  
Vol 77 ◽  
pp. 453-466 ◽  
Author(s):  
Junhua Hu ◽  
Li Pan ◽  
Yan Yang ◽  
Haiwei Chen
Keyword(s):  
Medical Diagnosis ◽  
Soft Sets ◽  
Model Based ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Soft Sets ◽  
Diagnosis Model ◽  
Intuitionistic Fuzzy Soft Sets

Generalized interval-valued hesitant intuitionistic fuzzy soft sets

2021 ◽  
pp. 1-12
Author(s):  
Admi Nazra ◽  
Yudiantri Asdi ◽  
Sisri Wahyuni ◽  
Hafizah Ramadhani ◽  
Zulvera
Keyword(s):  
Hesitant Fuzzy Set ◽  
Fuzzy Soft Set ◽  
Soft Sets ◽  
Binary Operations ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Soft Sets ◽  
Comparison Table ◽  
Definition Of ◽  
Interval Valued ◽  
Intuitionistic Fuzzy Soft Sets

This paper aims to extend the Interval-valued Intuitionistic Hesitant Fuzzy Set to a Generalized Interval-valued Hesitant Intuitionistic Fuzzy Soft Set (GIVHIFSS). Definition of a GIVHIFSS and some of their operations are defined, and some of their properties are studied. In these GIVHIFSSs, the authors have defined complement, null, and absolute. Soft binary operations like operations union, intersection, a subset are also defined. Here is also verified De Morgan’s laws and the algebraic structure of GIVHIFSSs. Finally, by using the comparison table, a different approach to GIVHIFSS based decision-making is presented.

scholarly journals Hesitant intuitionistic fuzzy soft sets

2017 ◽  
Vol 890 ◽  
pp. 012118 ◽  
Author(s):  
Admi Nazra ◽  
Syafruddin ◽  
Riri Lestari ◽  
Gandung Catur Wicaksono
Keyword(s):  
Soft Sets ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Soft Sets ◽  
Intuitionistic Fuzzy Soft Sets

Ordered Intuitionistic Fuzzy Soft Sets and Its Application in Decision Making Problem

2018 ◽  
Vol 7 (3) ◽  
pp. 76-98
Author(s):  
Pachaiyappan Muthukumar ◽  
Sai Sundara Krishnan Gangadharan
Keyword(s):  
Decision Making ◽  
Soft Sets ◽  
Numerical Example ◽  
Intuitionistic Fuzzy ◽  
Decision Making Problem ◽  
Algebraic Properties ◽  
Fuzzy Soft Sets ◽  
Intuitionistic Fuzzy Soft Sets

In this article, some new basic operations and results of Ordered Intuitionistic Fuzzy Soft (OIFS) sets, such as equality, complement, subset, union, intersection, OR, and AND operators along with several examples are investigated. Further, based on the analysis of several operations on OIFS sets, numerous algebraic properties and famous De Morgans inclusions and De Morgans laws are established. Finally, using the notions of OIFS sets, an algorithm is developed and implemented in a numerical example.

scholarly journals Minkowski Weighted Score Functions of Intuitionistic Fuzzy Values

Mathematics ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 1143
Author(s):  
Feng Feng ◽  
Yujuan Zheng ◽  
José Carlos R. Alcantud ◽  
Qian Wang
Keyword(s):  
Decision Making ◽  
Score Function ◽  
Soft Sets ◽  
Score Functions ◽  
Intuitionistic Fuzzy ◽  
Geometric Point ◽  
Weighted Score ◽  
Fuzzy Soft Sets ◽  
Intuitionistic Fuzzy Value ◽  
Intuitionistic Fuzzy Soft Sets

In multiple attribute decision-making in an intuitionistic fuzzy environment, the decision information is sometimes given by intuitionistic fuzzy soft sets. In order to address intuitionistic fuzzy decision-making problems in a more efficient way, many scholars have produced increasingly better procedures for ranking intuitionistic fuzzy values. In this study, we further investigate the problem of ranking intuitionistic fuzzy values from a geometric point of view, and we produce related applications to decision-making. We present Minkowski score functions of intuitionistic fuzzy values, which are natural generalizations of the expectation score function and other useful score functions in the literature. The rationale for Minkowski score functions lies in the geometric intuition that a better score should be assigned to an intuitionistic fuzzy value farther from the negative ideal intuitionistic fuzzy value. To capture the subjective attitude of decision makers, we further propose the Minkowski weighted score function that incorporates an attitudinal parameter. The Minkowski score function is a special case corresponding to a neutral attitude. Some fundamental properties of Minkowski (weighted) score functions are examined in detail. With the aid of the Minkowski weighted score function and the maximizing deviation method, we design a new algorithm for solving decision-making problems based on intuitionistic fuzzy soft sets. Moreover, two numerical examples regarding risk investment and supplier selection are employed to conduct comparative analyses and to demonstrate the feasibility of the approach proposed in this article.

scholarly journals Data Analysis Approach for Incomplete Interval-Valued Intuitionistic Fuzzy Soft Sets

Symmetry ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1061
Author(s):  
Hongwu Qin ◽  
Huifang Li ◽  
Xiuqin Ma ◽  
Zhangyun Gong ◽  
Yuntao Cheng ◽  
...  
Keyword(s):  
Missing Data ◽  
Soft Set ◽  
Fuzzy Soft Set ◽  
Soft Sets ◽  
Intuitionistic Fuzzy ◽  
Degree Of Membership ◽  
Filling Method ◽  
Fuzzy Soft Sets ◽  
Interval Valued ◽  
Intuitionistic Fuzzy Soft Sets

The model of interval-valued intuitionistic fuzzy soft sets is a novel excellent solution which can manage the uncertainty and fuzziness of data. However, when we apply this model into practical applications, it is an indisputable fact that there are some missing data in many cases for a variety of reasons. For the purpose of handling this problem, this paper presents new data processing approaches for an incomplete interval-valued intuitionistic fuzzy soft set. The missing data will be ignored if percentages of missing degree of membership and nonmember ship in total degree of membership and nonmember ship for both the related parameter and object are below the threshold values; otherwise, it will be filled. The proposed filling method fully considers and employs the characteristics of the interval-valued intuitionistic fuzzy soft set itself. A case is shown in order to display the proposed method. From the results of experiments on all thirty randomly generated datasets, we can discover that the overall accuracy rate is up to 80.1% by our filling method. Finally, we give one real-life application to illustrate our proposed method.

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