Journal of Fuzzy Extension and Applications
https://www.journal-fea.com/
Journal of Fuzzy Extension and Applicationsendaily1Thu, 01 Jun 2023 00:00:00 +0430Thu, 01 Jun 2023 00:00:00 +0430On algebraic aspects of η-fuzzy subgroups
https://www.journal-fea.com/article_166554.html
In this paper, we define the term " η-fuzzy subgroup" and show that every fuzzy subgroup is a η-fuzzy subgroup. We define some of the algebraic properties of the concept of η-fuzzy cosets. Furthermore, we initiate the study of the η-fuzzy normal subgroup and the quotient group with respect to the η-fuzzy normal subgroup and demonstrate some of their various group theoretical properties.A cubic set discussed in incline algebraic sub–structure
https://www.journal-fea.com/article_171958.html
An effective and flexible method for encoding ambiguous data is using cubic sets. The concept of incline algebraic sub-structure is considered and is interlinked with the notation of the cubic set to define cubic subincline. The sense of cubic sub incline of algebra is established with relevant results. Additionally, the results such as homomorphic image, preimage, cartesian product and level sets of cubic sub incline are worked out in this study, and several of its associated findings were looked into.Intuitionistic fuzzy complex subgroups with respect to norms (T,S)
https://www.journal-fea.com/article_172365.html
In our work in this paper, we define intuitionistic fuzzy complex subgroups with respect to t-norm T and s-norm S and investigate some properties of them in detail. Next, we obtain some results about them and give some relationships between them. Later, we introduce the inverse, composition, intersection and normality of them and we prove some basic new results and present some properties of them such that the inverse and composition of two intuitionistic fuzzy complex subgroups with respect to t-norm T and s-norm S will be intuitionistic complex fuzzy subgroups with respect to t-norm T and s-norm S. Also we consider and give some characterizations of them. Finally, we discuss them under group homomorphisms and investigate some related properties such that the image and preimage of two intuitionistic fuzzy complex subgroups with respect to t-norm T and s-norm S will be intuitionistic complex fuzzy subgroups with respect to t-norm T and s-norm S.Picture fuzzy semi-prime ideals
https://www.journal-fea.com/article_171483.html
Picture Fuzzy Sets (PFSs) are expanded to include Intuitionistic Fuzzy Sets (IFSs), with the extra advantage of avoiding underlying limitations. PFS based models may be adequate in situations when we face opinions involving more answer of types: yes, abstain and no. In this paper, the concepts of semi-prime ideals of PFS are explained. We also discussed how to construct picture fuzzy regular and intra-regular ideals and represents certain fundamental facts.Pythagorean and fermatean fuzzy sub-group redefined in context of T ̃-norm and S ̃-conorm
https://www.journal-fea.com/article_172114.html
This paper aims to study Pythagorean and Fermatean Fuzzy Subgroups (FFSG) &nbsp;in the context of -norm and &nbsp;-conorm functions. The paper examines the extensions of fuzzy subgroups, specifically "Pythagorean Fuzzy Subgroups (PFSG)" and "FFSG", along with their properties. In the existing literature on Pythagorean and FFSG, the standard properties for membership and non-membership functions are based on the "min" and "max" operations, respectively. However, in this work, we develop a theory that utilizes the -norm for "min" and the -conorm for "max", providing definitions of Pythagorean and FFSG with these functions, along with relevant examples. By incorporating this approach, we introduce multiple options for selecting the minimum and maximum values. Additionally, we prove several results related to Pythagorean and FFSG using the -norm and -conorm, and discuss important properties associated with them.On refined neutrosophic finite p-group
https://www.journal-fea.com/article_163041.html
The neutrosophic automorphisms of a neutrosophic groups &nbsp;G (I) , denoted by Aut(G (I)) is a neu-trosophic group under the usual mapping composition. It is a permutation of &nbsp;G (I) which is also a neutrosophic homomorphism. Moreover, suppose that X1 = X(G (I)) is the neutrosophic group of inner neutrosophic auto-morphisms of a neutrosophic group G (I) and Xn the neutrosophic group of inner neutrosophic automorphisms of Xn-1. In this paper, we show that if any neutrosophic group of the sequence G (I), X1, X2, &hellip; is the identity, then G (I) is nilpotent.n-Cylindrical fuzzy neutrosophic topological spaces
https://www.journal-fea.com/article_170808.html
The objective of this study is to incorporate topological space into the realm of n-Cylindrical Fuzzy Neutrosophic Sets (n-CyFNS), which are the most novel type of fuzzy neutrosophic sets. In this paper, we introduce n-Cylindrical Fuzzy Neutrosophic Topological Spaces (n-CyFNTS), n-Cylindrical Fuzzy Neutrosophic (n-CyFN) open sets, and n-CyFN closed sets. We also defined the n-CyFN base, n-CyFN subbase, and some related theorems here.Providing a Hybrid Fuzzy Approach to Explain Managers’ Mental Paradigms to Prioritize Employee Needs
https://www.journal-fea.com/article_159883.html
Today, most manufacturing and service companies adopt a customer-oriented approach to take into account employee needs and expectations as a strategic principle for sustainability and success in a competitive market. Meanwhile, Sengeh argues that &ldquo;many of the best ideas and strategies will not be realized due to the conflict between new ideas and managers&rsquo; subjective model, rather than the management weakness&rdquo;. On the other hand, managers&rsquo; decisions based on self-developed rules can suffer all kinds of biases . As Bierzman explains: &ldquo;managers&rsquo; mental heuristic rules lead to weak analysis of information, inappropriate weighting of the various data, and an investigation of few alternatives for decision-making, which can lead to systematic errors and common biases in the decision&rdquo;. Addressing the existing gap between managers&rsquo; subjective perceptions of employees and employees&rsquo; self-perceptions, the present study aims to present a new systematic approach with a combination of Delphi, Kano and AHP methods in an attempt to explain managers&rsquo; mental paradigms in Abadan Oil Refinary Company as one of the elading ones in the Middle East. The statistical population of the study consists of 18 experienced managers (using snowball method) and 203 employees at Abadan&rsquo;s Oil Refinery (using the Cochran formula). The validity and reliability of the questionnaire were also confirmed using Kendall&rsquo;s Correlation Coefficient, Cronbach&rsquo;s Alpha coefficient, and Gogus and Butcher&rsquo;s Incompatibility Rate. First, needs were determined from the views of the experts using the Fuzzy Delphi method, and then, Kano&rsquo;s non-linear model and Alpha-cut (&alpha;-Cut) method were used to classify 21 components as basic, performance, and excitement needs. In the end, the needs have been ranked using the Fuzzy AHP method. The results indicated that the proposed method was effectively successful in reducing biases, vagueness, and possible inconsistencies in managers' decisions and judgments. Overall, the method presented insights on the significance ofOn the Introduction to neutrosophic statistics and neutrosophic algebraic structures ( involving the fuzziness, similarity and the symmetry properties on the neutrosophic interval probability) (1)
https://www.journal-fea.com/article_162594.html
Abstract The neutrosophic interval statistical number (NISN) has been known to be very useful in expressing the interval values under indeterminate environments. One of the essential and so important useful as tools for measuring the degree of similarity between sets of given objects is the similarity measure . In this paper, neutrosophic numbers as well as the generalized Dice similarity measure for neutrosophic numbers for two sets are defined after which the axioms of fuzziness similarity and symmetry satisfying the NISN the properties were proved.BRIDGE DOMINATION IN FUZZY GRAPHS
https://www.journal-fea.com/article_170809.html
In communication networks, strong connectivity between nodes are critical. The failure of strong connectivity between nodes may jeopardize the network&rsquo;s stability. In fuzzy graphs, various dominating sets using strong edges are identified to avoid network stability. In this paper, the concept of bridge domination set and bridge domination number &gamma;_B (G) in fuzzy graphs is introduced. A few prominent properties of bridge domination numbers are chosen and analysed using relevant examples. The bridge domination number of fuzzy trees, constant fuzzy cycles, complete fuzzy and bipartite fuzzy graphs are identified. The use of bridge domination in a partial mesh topology to ensure network continuity in the event of a node failure is demonstrated.Interval Type-2 Fuzzy Logic System for Early Software Reliability Prediction
https://www.journal-fea.com/article_171957.html
The reliability of software product is seen as critical quality factor that cannot be overemphasized. Since real world application is loaded with high amount of uncertainty, such as applicable to software reliability, there should be a technique of dealing with such uncertainty. This paper presents a reliability model to effectively handle uncertainty in software data to enhance reliability prediction of software at the early (requirements and design) stages of software development life cycle. In this paper, a hybrid methodology of Takagi-Sugeno-Kang (TSK)-based Interval type-2 fuzzy logic system (IT2FLS) with artificial neural network (ANN) learning is employed for the prediction of software reliability. The parameters of the model are optimized using gradient descent back-propagation method. Relevant reliability software requirement and design metrics and software size metrics are utilized as inputs. The proposed approach uses twenty-eight real software project data. The performance of the model is evaluated using five performance metrics and found to provide output values that are very close to the actual output showing better predictive accuracy.A new approach to MCDM problems by fuzzy binary soft sets
https://www.journal-fea.com/article_175256.html
Many real-world problems faces strenuous in making decisions. Many theories have evoloved for dealing with such problems. The present paper deals with fuzzy binary soft sets and their applications to multi-criteria decision-making (MCDM) problems. Then introduced expanded matrix representation of fuzzy binary soft sets, extended resultant matrix, AND operator and also, introduced an algorithm to solve a proposed problem.Fire Extinguishers Based on Acoustic Oscillations in Airflow Using Fuzzy Classification
https://www.journal-fea.com/article_175269.html
Fire, a natural calamity, poses a severe threat to human existence and is typically combated utilizing traditional measures. However, due to the limitations and potential environmental damage associated with these conventional strategies, there is a compelling need to devise innovative firefighting techniques. Among these emergent strategies, fire suppression systems utilizing sound wave technologies present a promising alternative.In the present investigation, a comprehensive compilation of data harvested from a series of experimental trials focused on sound wave-based extinguishment was employed. Utilizing these data, a fire suppression model predicated on sound wave technologies was architectured, integrating five distinct fuzzy logic methodologies. These include Fuzzy Rough Set (FRS), Fuzzy K-nearest neighbors (FNN), Fuzzy ownership K-nearest neighbors (FONN), Fuzzy-rough K-nearest neighbors (FRNN), and Vaguely quantified K-nearest neighbors (VQNN).The ultimate goal of these models is to accurately discern between the extinguished and non-extinguished state of the flame. This classification is based on a variety of input parameters intrinsic to the model, such as fuel type, flame size, decibel level, frequency, airflow, and distance parameters.Evaluation of the models' classification efficacy was carried out through a combination of various statistical methods including Mean Absolute Error (MAE), Root Mean Square Error (RMSE), kappa statistic (KP), and Mean Squared Error (MSE).The analysis yielded encouraging results, with FRS, FNN, FONN, FRNN, and VQNN models demonstrating classification accuracies of 93.12%, 96.66%, 95.56%, 96.35%, and 96.89% respectively. Hence, it was concluded that the proposed model exhibits high accuracy in classifying firefighting data, affirming its applicability.COMPLEX FUZZY LIE SUBALGEBRAS AND COMPLEX FUZZY IDEALS UNDER t-NORMS
https://www.journal-fea.com/article_178449.html
In this paper, we define the conceps of complex fuzzy Lie subalgebras and complexfuzzy ideals of Lie algebras with respect to t-norms and investigate some of characteristics andrelationship between them. Next, we introduce the concepos of quotient subalgebras, intersection, sum and direct product of them and prove some results about them. Finally, we introduceand study the image and the inverse image of them under Lie algebra homomorphisms.