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Related papers: Generalized Ideals and Co-Granular Rough Sets

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In this paper, using the concept of ideal, we study the idea of rough ideal convergence of sequences which is an extension of the notion of rough convergence of sequences in a partial metric space. We define the set of rough…

General Topology · Mathematics 2025-01-15 Sukila Khatun , Amar Kumar Banerjee , Rahul Mondal

The notion of concept has been studied for centuries, by philosophers, linguists, cognitive scientists, and researchers in artificial intelligence (Margolis & Laurence, 1999). There is a large literature on formal, mathematical models of…

Artificial Intelligence · Computer Science 2021-01-14 Stephen Clark , Alexander Lerchner , Tamara von Glehn , Olivier Tieleman , Richard Tanburn , Misha Dashevskiy , Matko Bosnjak

We introduce a lattice structure as a generalization of meet-continuous lattices and quantales. We develop a point-free approach to these new lattices and apply these results to $R$-modules. In particular, we give the module counterpart of…

Rings and Algebras · Mathematics 2016-11-01 Mauricio Medina Bárcenas , Angel Zaldívar , Martha Lizbeth Shaid Sandoval Miranda

As the first part of the treatise on A General Theory of Concept Lattice (I-V), this work develops the general concept lattice for the problem concerning categorization of objects according to their properties. Unlike the conventional…

Logic in Computer Science · Computer Science 2019-08-06 Tsong-Ming Liaw , Simon C. Lin

Concise granule descriptions for definable granules and approaching descriptions for indefinable granules are challenging and important issues in granular computing. The concept with only common attributes has been intensively studied. To…

Artificial Intelligence · Computer Science 2022-01-10 Jianqin Zhou , Sichun Yang , Xifeng Wang , Wanquan Liu

Rough set theory, a mathematical tool to deal with inexact or uncertain knowledge in information systems, has originally described the indiscernibility of elements by equivalence relations. Covering rough sets are a natural extension of…

Artificial Intelligence · Computer Science 2015-03-13 Ping Zhu

Granular operator spaces and variants had been introduced and used in theoretical investigations on the foundations of general rough sets by the present author over the last few years. In this research, higher order versions of these are…

Logic in Computer Science · Computer Science 2019-10-15 A. Mani

The notion of rough set captures indiscernibility of elements in a set. But, in many real life situations, an information system establishes the relation between different universes. This gave the extension of rough set on single universal…

Artificial Intelligence · Computer Science 2013-01-30 B. K. Tripathy , D. P. Acharjya

Taking an algebraic perspective on the basic structures of Rough Concept Analysis as the starting point, in this paper we introduce some varieties of lattices expanded with normal modal operators which can be regarded as the natural rough…

We discuss that how the majority of traditional modeling approaches are following the idealism point of view in scientific modeling, which follow the set theoretical notions of models based on abstract universals. We show that while…

Artificial Intelligence · Computer Science 2017-09-12 Vahid Moosavi

In granular computing, fuzzy sets can be approximated by granularly representable sets that are as close as possible to the original fuzzy set w.r.t. a given closeness measure. Such sets are called granular approximations. In this article,…

Artificial Intelligence · Computer Science 2022-02-16 Marko Palangetić , Chris Cornelis , Salvatore Greco , Roman Słowiński

Rough set theory is a well-known mathematical framework that can deal with inconsistent data by providing lower and upper approximations of concepts. A prominent property of these approximations is their granular representation: that is,…

Artificial Intelligence · Computer Science 2024-03-19 Adnan Theerens , Chris Cornelis

Subsethood, which is to measure the degree of set inclusion relation, is predominant in fuzzy set theory. This paper introduces some basic concepts of spatial granules, coarse-fine relation, and operations like meet, join, quotient meet and…

Artificial Intelligence · Computer Science 2023-09-07 Liquan Zhao , Yiyu Yao

New concepts of rough natural number systems, recently introduced by the present author, are used to improve most rough set-theoretical measures in general Rough Set theory (\textsf{RST}) and measures of mutual consistency of multiple…

Logic · Mathematics 2011-02-15 A. Mani

In this paper, we will be delving deeper into the connection between the rough theory and the ring theory precisely in the principle and maximal ideal. The rough set theory has shown by Pawlak as good formal tool for modeling and processing…

General Mathematics · Mathematics 2020-12-08 Faraj. A. Abdunabi

Assuming sufficiently many terms of a n-dimensional table defined over a field are given, we aim at guessing the linear recurrence relations with either constant or polynomial coefficients they satisfy. In many applications, the table terms…

Symbolic Computation · Computer Science 2021-11-19 Jérémy Berthomieu , Mohab Safey El Din

The purpose of this work is to extend the study of the commutative rings whose lattice of ideals can be a structure of BL-algebra as carry out by Heubo et al in 2018, to non commutative rings appointed in the work as pseudo BL-rings. We…

Rings and Algebras · Mathematics 2021-04-20 Surdive Atamewoue Tsafack , Arnaud Fobasso Tchinda , Yuming Feng , Selestin Ndjeya

The theory of rough sets was firstly introduced by Pawlak (see \cite{p}). Many Mathematician has been studied the relations between rough sets and algebraic systems such as groups, rings and modules. In this paper we will introduce the…

Group Theory · Mathematics 2016-02-26 Waqas Mahmood

We propose to employ the hierarchical coarse-grained structure in the artificial neural networks explicitly to improve the interpretability without degrading performance. The idea has been applied in two situations. One is a neural network…

Machine Learning · Computer Science 2024-06-19 Xi-Ci Yang , Z. Y. Xie , Xiao-Tao Yang

We propose a probabilistic model for refining coarse-grained spatial data by utilizing auxiliary spatial data sets. Existing methods require that the spatial granularities of the auxiliary data sets are the same as the desired granularity…

Machine Learning · Statistics 2019-07-19 Yusuke Tanaka , Tomoharu Iwata , Toshiyuki Tanaka , Takeshi Kurashima , Maya Okawa , Hiroyuki Toda