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21 articles for “Fuzzy set theory”
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Optimizing Sampling Techniques Using Fuzzy Set Theory: A Comprehensive Approach
Abstract: Sampling is a critical process in statistics, used to estimate population parameters without needing to examine the entire population. Traditional sampling methods, such as simple random sampling, stratified sampling, and cluster sampling, face limitations when applied to complex or heterogeneous populations with imprecise boundaries. These methods often fail to accurately represent populations with overlapping characteristics or missing data, resulting in sampling bias and reduced accuracy. To address these challenges, this …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 1, 2025 · pp. 29–43 Read article
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Fuzzy Programming Technique and Proposed Application
Abstract: A solution approach supported fuzzy linear programming is planned and applied to best machine scheduling downside. During this resolution approach, errors within the demand of assorted product throughout ensuing production period are thought of to be fuzzy in nature. In standard linear programming approach it's assumed that there's no error within the expected demand of assorted product. A fuzzy linear programming approach is planned to get an optimal resolution underneath …
Published in Recent Trends in Programming languages · Vol. 2, Issue 1, 2015 · pp. 7–11 Read article
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Modeling and Simulation of Autonomous Vehicle Management System Using Fuzzy Theory
Abstract: ABSTRACT Fuzzy techniques have demonstrated a surge in the practical applications of fuzzy set theory. This paper presents the speed control mechanism that solves the problem intelligently by learning, adaptation and incorporating human knowledge. The proposed speed controller is used to manage the speed of the trains while at the same time managing the uncertainty in the condition of railway tracks. To deal with the aforesaid issues of uncertainty a …
Published in Current Trends in Information Technology · Vol. 2, Issue 1, 2012 · pp. 39–47 Read article
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Applications of Fuzzy Set in Mathematical Programming
Abstract: The Information in today’s world are uncertain and are under circumstances of increased uncertainty so decisions are difficult to be made. There are different techniques to represent these uncertainties. One of the ways of representing it is with the help of Fuzzy Set Theory & Fuzzy Numbers. One of the very fascinating ideas of using fuzzy set in Mathematical programming and linear programming problems has benefited largely in decision-making, in …
Published in Research & Reviews : Journal of Statistics · Vol. 10, Issue 3, 2021 · pp. 24–28 Read article
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A Survey on Multiobjective Decision Making on Vague Sets
Abstract: This paper provides report of a survey on the vague sets and also multiobjective decision making. As a further fuzzy set theory generalization, the vague set theory can overcome the fuzzy set shortcomings through defining the membership from two different sides of both FALSE and TRUE, rather than only through a value of a single membership. MCDM approach has evolved to accommodate numerous application types. Methods dozens have been developed, …
Published in Journal of Advanced Database Management & Systems · Vol. 3, Issue 1, 2016 · pp. 1–8 Read article
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Novel Distance Measure for Linear Diophantine Fuzzy Sets
Abstract: Unlike other fuzzy set theories, the theory of Linear Diophantine fuzzy set (LDFS) aims to overcome uncertainties via the reference parameters. The Parameters provide flexibility and efficiency to LDFS in handling the uncertain data. In this study, we introduce new distance measure for linear Diophantine fuzzy sets. Then, we studied the properties of proposed distance measure. Finally, we established a new similarity measure for LDFSs based on distance measure.
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 9, Issue 2, 2022 · pp. 38–45 Read article
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Fuzzy Logic and Its Application
Abstract: Fuzzy Logic has an extremely vital role in the arena of computer science and engineering, Artificial Intelligence, control theory and mathematics etc. Fuzzy logic is the way of organizing belief or idea that cannot be defined precisely but which depends upon their contexts i.e. the human way of logic thinking, reasoning, and perception. Fuzzy Logic finds widespread use the businesses, medicinal sciences, engineering, behavioral sciences, etc. due to perpetually growing …
Published in Journal of Microcontroller Engineering and Applications · Vol. 8, Issue 1, 2021 · pp. 31–38 Read article
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Multicriteria Decision Making using SR-Fuzzy Sets
Abstract: In this study, we introduce and explore square-root fuzzy sets (SR-Fuzzy sets), a novel extension within the realm of fuzzy set theory. We begin by establishing a comparative analysis between SR-Fuzzy sets and two well-known fuzzy set models: Intuitionistic Fuzzy Sets (IFS) and Pythagorean Fuzzy Sets (PFS). This comparison highlights the unique characteristics and mathematical structure of SR-Fuzzy sets. A particular focus is placed on the complement operator, which plays …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 12–20 Read article
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Total Quality Management Initiatives for Enhancing the Performance of Manufacturing Companies: An Empirical Investigation
Abstract: Total quality management is the industrial management approach of reducing defects by improving the processes. This study has been carried out in SMEs of northern India which have implemented TQM initiatives and faced different barriers in its successful implementation. Questionnaire survey has been performed followed by Qualitative and Quantitative modeling including interpretive structural modeling, fuzzy set theory, and structural equation modeling. Results of investigation recommended that resistance from employees is …
Published in Journal of Production Research & Management · Vol. 9, Issue 3, 2019 · pp. 41–55 Read article
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Abstract Fuzzy Function
Abstract: The grading of the set is studied by L. A. Zadeh in 1965. The set is defined by the membership function. Fuzzy set and fuzzy logic are the two domain defined as the discrete mathematical structure. Its discreteness is associated with the fundamental axioms of the classical set theory and its operation. This paper defines the fuzzy function and its applications.Keywords: Fuzzy Set, Fuzzy Logic, Fuzzy Function, Set Theory, Membership …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 7, Issue 2, 2020 · pp. 10–13 Read article
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Review on Weather Events Forecasting Using Data Mining Algorithms
Abstract: Weather events forecasting is the most imperious and stimulatingfunctioning responsibilities supported by meteorological departments worldwide. Amongst all weather events, rainfall plays the most authoritative role in the life of human beings. Human society to a great level depends upon its frequency at various scales. Data mining is a process that mechanically abstracts useful patterns from a given data set. Thecommon algorithms and techniques for rain forecasting like Artificial Neural Networks …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 5, Issue 1, 2018 · pp. 12–22 Read article
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Expanding Hicks Contraction Theory, Multi-Valued Mappings in Generalized b-Menger Spaces
Abstract: This paper extends the Hicks contraction theory to multi-valued mappings within generalized b-Manger spaces, a class of metric-like structures that accommodate more flexible distance functions. By introducing new definitions, such as generalized admissibility conditions and weak compatibility in the multivalued sense, we provide a comprehensive analysis of how these contractions behave in broader topological and metric contexts. Our approach systematically generalizes classical contraction principles by relaxing conventional constraints, thereby broadening …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 1, 2025 · pp. 1–05 Read article
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Big Data Management: Theory & Practice
Abstract: In this paper, Big Data Management is studied. There is finite number of information in Big Data and correspondingly its method of analysis exists. Big Data Analysis (BDA) method is proposed in this paper. A compact method (K-Means Cluster, Generalised K-Means Cluster, C-Means, Fuzzy Means, Fuzzy Numbers, Fuzzy Set, Fuzzy Logic, Neural Network, Genetic Algorithm) based big data analysis is presented in this paper. There are four models are presented …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 7, Issue 2, 2020 · pp. 13–22 Read article
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Use of Vague Set Theory for Multiple Objectives Decision Making
Abstract: AbstractIn this paper, we goal to prolong the inspiration of classical soft expert sets to possibility vague soft expert sets through applying the theory of soft expert sets to the probability vague soft sets. The complement, union, intersection, AND/OR operations as well as some related ideas referring to this inspiration are defined. Since vague sets (VSs) can give more data than fuzzy sets, it is prevalent in mathematical analysis of …
Published in Journal of Advanced Database Management & Systems · Vol. 4, Issue 1, 2017 · pp. 1–6 Read article
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Study of Proximity Points and Fixed Points
Abstract: This paper explores the concepts of proximity points and fixed points, which are fundamental in mathematical analysis and nonlinear functional analysis. Fixed-point theorems play a crucial role in optimization, game theory, differential equations, and dynamic systems. Proximity points, an extension of fixed points, provide a more generalized approach, allowing near-coincidence rather than exact identity. The study discusses classical fixed-point theorems, such as Banach’s contraction principle, Brouwer’s fixed-point theorem, and Schauder’s …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 28–31 Read article
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Cryptosystem Based on Fuzzy Theory
Abstract: This paper proposes a cryptosystem whose security comprises with the membership function of fuzzy. The security lies with the linguistic and numeric representation of information and its transformation by fuzzy. The one way hash function is substituted to membership function. The key generation and encryption comprises with fuzzy set and fuzzy logic respectively. Thus, the proposed system provides the security against all attacks by linguistic transformation rather than numeric representation. …
Published in Journal of Open Source Developments · Vol. 7, Issue 2, 2020 · pp. 7–14 Read article
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Quantum-Fuzzy Tensor Operators and Uncertainty-Band Bifurcation for Symmetry-Preserving State Discrimination
Abstract: A tensor-operator framework is developed for fuzzy conjunction, fuzzy disjunction, and symmetry-preserving state discrimination in multi-qubit quantum systems. In this formulation, fuzzy membership and non-membership degrees are represented through expectations of effect operators acting on density matrices, providing a natural bridge between fuzzy logic and quantum measurement theory. Conjunction and disjunction operations are extended to the quantum domain via tensorised channels, constructed using projective measurements and unitary transformations, enabling logical …
Published in Emerging Trends in Symmetry · Vol. 2, Issue 1, 2026 · pp. 08–15 Read article
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Fuzzy and Cryptosystem
Abstract: Zadeh’s theory of fuzzy for grading the objects is reviewed in this paper under the context to develop the cryptosystem. This paper proposes a cryptosystem whose security comprises with the membership function of fuzzy. The security lies with the linguistic and numeric representation of information and its transformation by fuzzy. The one way hash function is substituted to membership function. The key generation and encryption comprises with fuzzy set and …
Published in Journal of Advancements in Robotics · Vol. 7, Issue 2, 2020 · pp. 1–8 Read article
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Measures of Location for Imprecise Data
Abstract: AbstractStatistical analysis is usually done on data sets that contain precise information. However, data obtained may not be precise always. This may be due to vagueness in the process of measurement itself or due to the values being expressed in linguistic terms. Data that are not precise are referred to as imprecise data or fuzzy data. Developing statistical measures for imprecise data has been pursued by researchers during the past …
Published in Research & Reviews : Journal of Statistics · Vol. 2, Issue 3, 2013 · pp. 35–40 Read article
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A Study of Fixed-Point and Best Proximity Point
Abstract: Fixed-point theory plays a fundamental role in nonlinear analysis and has significant applications in optimization, differential equations, and applied mathematics. This study investigates the existence and properties of fixed points and best proximity points for various classes of mappings defined on metric and normed spaces. While fixed-point results guarantee the existence of a point that remains invariant under a given mapping, such points may not exist when the mapping is …
Published in Recent Trends in Mathematics · Vol. 3, Issue 1, 2026 · pp. 28–39 Read article