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Related papers: Simulation of Random LR Fuzzy Intervals

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The clustering methods have been used in a variety of fields such as image processing, data mining, pattern recognition, and statistical analysis. Generally, the clustering algorithms consider all variables equally relevant or not…

Machine Learning · Computer Science 2021-02-19 Sara Ines Rizo Rodriguez , Francisco de Assis Tenorio de Carvalho

Concepts of graph theory have applications in many areas of computer science including data mining, image segmentation, clustering, image capturing, networks, etc . An interval-valued fuzzy set is a generalization of the notion of a fuzzy…

Discrete Mathematics · Computer Science 2014-01-07 Hossein Rashmanlou , Madhumangal Pal

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

Many mathematical models utilize limit processes. Continuous functions and the calculus, differential equations and topology, all are based on limits and continuity. However, when we perform measurements and computations, we can achieve…

Artificial Intelligence · Computer Science 2025-10-20 Mark Burgin

The paper focuses on mining patterns that are characterized by a fuzzy lagged relationship between the data objects forming them. Such a regulatory mechanism is quite common in real life settings. It appears in a variety of fields: finance,…

Artificial Intelligence · Computer Science 2014-05-16 Eran Shaham , David Sarne , Boaz Ben-Moshe

Monte Carlo simulations are an important tool in statistical physics, complex systems science, and many other fields. An increasing number of these simulations is run on parallel systems ranging from multicore desktop computers to…

Statistical Mechanics · Physics 2009-06-10 Stephan Mertens

In Round Robin CPU scheduling algorithm the main concern is with the size of time quantum and the increased waiting and turnaround time. Decision for these is usually based on parameters which are assumed to be precise. However, in many…

Other Computer Science · Computer Science 2012-03-13 Supriya Raheja , Reena Dadhich , Smita Rajpal

In a recent paper [1] we introduced the Fuzzy Bayesian Learning (FBL) paradigm where expert opinions can be encoded in the form of fuzzy rule bases and the hyper-parameters of the fuzzy sets can be learned from data using a Bayesian…

Machine Learning · Statistics 2017-04-07 Indranil Pan , Dirk Bester

In this paper, we introduce a fundamental framework to create a bridge between Probability Theory and Fuzzy Logic. Indeed, our theory formulates a random experiment of selecting crisp elements with the criterion of having a certain fuzzy…

Logic in Computer Science · Computer Science 2022-05-31 Amir Saki , Usef Faghihi

In this paper, we introduce the notion of fuzzy soft numbers. Here defined fuzzy soft number and four arithmetic operations $ \tilde{+}, \tilde{-}, \tilde{\times}, \tilde{\div} $ and related properties. Also introduce Hausdorff distance,…

General Mathematics · Mathematics 2021-12-28 Manash Jyoti Borah , Bipan Hazarika

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

Fuzzy data, prevalent in social sciences and other fields, capture uncertainties arising from subjective evaluations and measurement imprecision. Despite significant advancements in fuzzy statistics, a unified inferential regression-based…

Methodology · Statistics 2025-06-05 Antonio Calcagnì , Przemysław Grzegorzewski , Maciej Romaniuk

In several research areas, ratings data and response times have been successfully used to unfold the stage-wise process through which human raters provide their responses to questionnaires and social surveys. A limitation of the standard…

Applications · Statistics 2022-03-24 Niccolò Cao , Antonio Calcagnì

In this paper, we revisit the diffusive representations of fractional integrals established in \cite{diethelm2023diffusive} to explore novel variants of such representations which provide highly efficient numerical algorithms for the…

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

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

In this paper, we define irregular interval-valued fuzzy graphs and their various classifications. Size of regular interval-valued fuzzy graphs is derived. The relation between highly and neighbourly irregular interval-valued fuzzy graphs…

Discrete Mathematics · Computer Science 2014-07-24 Madhumangal Pal , Hossein Rashmanlou

The paper deals with the developing of the methodological backgrounds for the modeling and simulation of complex dynamical objects. Such backgrounds allow us to perform coordinate transformation and formulate the algorithm of its usage for…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-08-07 Roman Voliansky , Andri Pranolo

In this paper, a new interval type-2 fuzzy neural network able to construct non-separable fuzzy rules with adaptive shapes is introduced. To reflect the uncertainty, the shape of fuzzy sets considered to be uncertain. Therefore, a new form…

Machine Learning · Computer Science 2021-12-22 Armin Salimi-Badr

Especially in research areas of computer science such as data mining, image segmentation, clustering image capturing and networking. The interval-valued fuzzy graphs are more flexible and compatible than fuzzy graphs due to the fact that…

Discrete Mathematics · Computer Science 2014-05-26 Hossein Rashmanlou , Madhumangal Pal

In the process of measuring objects with local self-similarity, such as satellite images or coastlines, we obtain a data set with both local self-similarity and uncertainty. To better interpolate such data sets, an interpolation function…

General Mathematics · Mathematics 2025-08-05 Hyang Choe , MiGyong Ri , CholHui Yun