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Fuzzy rough set (FRS) has a great effect on data mining processes and the fuzzy logical operators play a key role in the development of FRS theory. In order to further generalize the FRS theory to more complicated data environments, we…

General Mathematics · Mathematics 2022-05-23 Gongao Qi , Bin Yang , Wei Li

Statistical limits are defined relaxing conditions on conventional convergence. The main idea of the statistical convergence of a sequence l is that the majority of elements from l converge and we do not care what is going on with other…

Classical Analysis and ODEs · Mathematics 2008-03-31 Mark Burgin , Oktay Duman

The purpose of this paper is to study a non-convex fuzzy multi-objective quadratic programming problem, in which both the technological coefficients and resources are fuzzy with nonlinear membership function. A computational procedure to…

Optimization and Control · Mathematics 2013-08-02 Shashi Aggarwal , Uday Sharma

In this article, we combine the concept of a bipolar fuzzy set and a soft set. We introduce the notion of bipolar fuzzy soft set and study fundamental properties. We study basic operations on bipolar fuzzy soft set. We define exdended…

Artificial Intelligence · Computer Science 2014-03-10 Muhammad Aslam , Saleem Abdullah , Kifayat ullah

Support vector machines (SVMs) and fuzzy rule systems are functionally equivalent under some conditions. Therefore, the learning algorithms developed in the field of support vector machines can be used to adapt the parameters of fuzzy…

Machine Learning · Computer Science 2014-08-25 Duc-Hien Nguyen , Manh-Thanh Le

We introduce a general theory of epistemic random fuzzy sets for reasoning with fuzzy or crisp evidence. This framework generalizes both the Dempster-Shafer theory of belief functions, and possibility theory. Independent epistemic random…

Artificial Intelligence · Computer Science 2024-05-08 Thierry Denoeux

In this article, we introduce a differentiability concept for fuzzy functions $\tilde{f}: F(\mathbb{R}) \to F(\mathbb{R})$, where $F(\mathbb{R})$ is the set of all fuzzy numbers. With the help of the proposed differentiability notion, we…

Optimization and Control · Mathematics 2019-10-08 U. M. Pirzada , Debdas Ghosh

We introduce non-commutative algebras, which can be associated with the function algebra of functions on a finite or half-finite cylinder. The algebras, which depend on a deformation parameter, are crossed product algebras of a partial…

Quantum Algebra · Mathematics 2023-09-12 Andreas Sykora

The measure of distance between two fuzzy sets is a fundamental tool within fuzzy set theory, however, distance measures currently within the literature use a crisp value to represent the distance between fuzzy sets. A real valued distance…

Artificial Intelligence · Computer Science 2014-09-04 Josie C. McCullochy , Chris J. Hinde , Christian Wagner , Uwe Aickelin

Theory of operators generated by binary fuzzy relations is highly increasing for its nature and applicability. The main goal of the paper is to present several representation theorems for operators induced by fuzzy relations (for example…

Logic · Mathematics 2014-06-10 Michal Botur

In this paper we introduce a fuzzy version of symport/antiport membrane systems. Our fuzzy membrane systems handle possibly inexact copies of reactives and their rules are endowed with threshold functions that determine whether a rule can…

Other Computer Science · Computer Science 2007-05-23 Jaume Casasnovas , Joe Miro , Manuel Moya , Francesc Rossello

In this paper, concept of fuzzy continuous operator, fuzzy bounded linear operator are introduced in fuzzy strong $\phi$-b-normed linear spaces and their relations are studied. Idea of operator fuzzy norm is developed and completeness of…

General Mathematics · Mathematics 2023-02-22 Abhishikta Das , T. Bag

The concept of fuzzy soft set was introduced for the first time by Maji et al. in 2002, and was considered sharply from applicable aspects to theoretical aspects by a wide range of researchers. In this paper the concept of fuzzy soft norm…

Functional Analysis · Mathematics 2013-10-04 A. Zahedi Khameneh , A. Kilicman , A. R. Salleh

Incomplete information is a problem in many aspects of actual environments. Furthermore, in many sceneries the knowledge is not represented in a crisp way. It is common to find fuzzy concepts or problems with some level of uncertainty.…

Programming Languages · Computer Science 2007-05-23 Susana Munoz-Hernandez , Claudio Vaucheret

We introduce and study a new class of partial differential equations (PDEs) with hybrid fuzzy-stochastic parameters, coined fuzzy-stochastic PDEs. Compared to purely stochastic PDEs or purely fuzzy PDEs, fuzzy-stochastic PDEs offer powerful…

Analysis of PDEs · Mathematics 2019-06-11 Mohammad Motamed

In this paper, we present the concept of subdifferential for fuzzy n-cell number valued functions. Then we state some theorems related to subdifferentiability based on the new definition. Finally, we present some applications emphasized on…

Optimization and Control · Mathematics 2024-04-30 Samira Fatemi , Ildar Sadeqi , Fridoun Moradlou

At the first, we revise the Kosinski definition of the sum of ordered fuzzy numbers. The associativity of revised sum is investigated here. In addition, we show that the multiple revised sum of finite sequence of trapezoidal ordered fuzzy…

Discrete Mathematics · Computer Science 2017-10-11 Anna Łyczkowska-Hanćkowiak , Krzysztof Piasecki

How to express an expert's or a decision maker's preference for alternatives is an open issue. Consistent fuzzy preference relation (CFPR) is with big advantages to handle this problem due to it can be construed via a smaller number of…

Artificial Intelligence · Computer Science 2014-03-25 Xinyang Deng , Felix T. S. Chan , Rehan Sadiq , Sankaran Mahadevan , Yong Deng

This study reexamines diffusive representations for fractional integrals with the goal of pioneering new variants of such representations. These variants aim to offer highly efficient numerical algorithms for the approximate computation of…

Numerical Analysis · Mathematics 2025-07-08 Renu Chaudhary , Kai Diethelm

Time series clustering is a central machine learning task with applications in many fields. While the majority of the methods focus on real-valued time series, very few works consider series with discrete response. In this paper, the…

Machine Learning · Statistics 2023-04-25 Ángel López Oriona , Christian Weiss , José Antonio Vilar