Results 1 to 10 of about 699,072 (277)

Generalized Ideals and Co-Granular Rough Sets

, 2017
Lattice-theoretic ideals have been used to define and generate non granular rough approximations over general approximation spaces over the last few years by few authors.
Mani, A
core   +1 more source

Port throughput influence factors based on neighborhood rough sets: An exploratory study

Journal of Industrial Engineering and Management, 2015
Purpose: The purpose of this paper is to devise a efficient method for the importance analysis on Port Throughput Influence Factors. Design/methodology/approach: Neighborhood rough sets is applied to solve the problem of selection factors.
Weiping Cui, Lei Huang, Ying Wang
doaj   +1 more source

Kernel Neighborhood Rough Sets Model and Its Application

Complexity, 2018
Rough set theory has been successfully applied to many fields, such as data mining, pattern recognition, and machine learning. Kernel rough sets and neighborhood rough sets are two important models that differ in terms of granulation.
Kai Zeng, Siyuan Jing
doaj   +1 more source

Approximations from Anywhere and General Rough Sets

, 2017
Not all approximations arise from information systems. The problem of fitting approximations, subjected to some rules (and related data), to information systems in a rough scheme of things is known as the \emph{inverse problem}.
A Mani, A Mani, A Mani, A Mani, A Mani, A Mani, A Mani, A Skowron, AI Malcev, BA Davey, C Qing, I Duntsch, I Duntsch, I Duntsch, I Duntsch, I Düntsch, J Stepaniuk, JPS Kung, L Polkowski, M Banerjee, M Banerjee, M Dorigo, P Pagliani, Z Pawlak   +23 more
core   +1 more source

Two kinds of average approximation accuracy

CAAI Transactions on Intelligence Technology
Rough set theory places great importance on approximation accuracy, which is used to gauge how well a rough set model describes a target concept. However, traditional approximation accuracy has limitations since it varies with changes in the target ...
Qingzhao Kong, Wanting Wang, Dongxiao Zhang, Wenbin Zhang   +3 more
doaj   +1 more source

Multigranulation rough set: A multiset based strategy

International Journal of Computational Intelligence Systems, 2017
A simple multigranulation rough set approach is to approximate the target through a family of binary relations. Optimistic and pessimistic multigranulation rough sets are two typical examples of such approach.
Xibei Yang, Suping Xu, Huili Dou, Xiaoning Song, Hualong Yu, Jingyu Yang   +5 more
doaj   +1 more source

Rough sets theory for travel demand analysis in Malaysia [PDF]

, 2008
This study integrates the rough sets theory into tourism demand analysis. Originated from the area of Artificial Intelligence, the rough sets theory was introduced to disclose important structures and to classify objects.
Wong, Jenn Hwee
core  

Covering-Based Rough Single Valued Neutrosophic Sets [PDF]

Neutrosophic Sets and Systems, 2017
Rough sets theory is a powerful tool to deal with uncertainty and incompleteness of knowledge in information systems. Wang et al. proposed single valued neutrosophic sets as an extension of intuitionistic fuzzy sets to deal with real-world problems.
Yingcang Ma, Wanying Zhou, Qing Wan
doaj   +1 more source

Fuzzy Rough Sets versus Rough Fuzzy Sets

, 1998
Reihe Computational Intelligence ...
openaire   +2 more sources

Connectedness of graphs and its application to connected matroids through covering-based rough sets [PDF]

, 2015
Graph theoretical ideas are highly utilized by computer science fields especially data mining. In this field, a data structure can be designed in the form of tree.
Huang, Aiping, Zhu, William
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