Rough sets and near sets in medical imaging: A review

AE Hassanien, A Abraham, JF Peters… - IEEE Transactions …, 2009‏ - ieeexplore.ieee.org
This paper presents a review of the current literature on rough-set-and near-set-based
approaches to solving various problems in medical imaging such as medical image …

Interval dominance-based feature selection for interval-valued ordered data

W Li, H Zhou, W Xu, XZ Wang… - IEEE Transactions on …, 2022‏ - ieeexplore.ieee.org
Dominance-based rough approximation discovers inconsistencies from ordered criteria and
satisfies the requirement of the dominance principle between single-valued domains of …

Soft clustering–fuzzy and rough approaches and their extensions and derivatives

G Peters, F Crespo, P Lingras, R Weber - International Journal of …, 2013‏ - Elsevier
Clustering is one of the most widely used approaches in data mining with real life
applications in virtually any domain. The huge interest in clustering has led to a possibly …

Fuzzy preference based rough sets

Q Hu, D Yu, M Guo - Information sciences, 2010‏ - Elsevier
Preference analysis is an important task in multi-criteria decision making. The rough set
theory has been successfully extended to deal with preference analysis by replacing …

Multigranulation supertrust model for attribute reduction

W Ding, W Pedrycz, I Triguero, Z Cao… - IEEE Transactions on …, 2020‏ - ieeexplore.ieee.org
As big data often contains a significant amount of uncertain, unstructured, and imprecise
data that are structurally complex and incomplete, traditional attribute reduction methods are …

Using fuzzy inference system for architectural space analysis

BC Arabacioglu - Applied Soft Computing, 2010‏ - Elsevier
Though architectural space is the main source and the only indispensable component of any
architectural construction, in many cases its boundaries are uncertain, leading intuitive …

Biological image classification using rough-fuzzy artificial neural network

C Affonso, RJ Sassi, RM Barreiros - Expert Systems with Applications, 2015‏ - Elsevier
This paper presents a methodology to biological image classification through a Rough-
Fuzzy Artificial Neural Network (RFANN). This approach is used in order to improve the …

The incremental method for fast computing the rough fuzzy approximations

Y Cheng - Data & Knowledge Engineering, 2011‏ - Elsevier
The lower and upper approximations are basic concepts in rough fuzzy set theory. The
effective computation of approximations is very important for improving the performance of …

# FIVE: High-level components for develo** collaborative and interactive virtual environments

R Bouville, V Gouranton, T Boggini… - 2015 IEEE 8th …, 2015‏ - ieeexplore.ieee.org
This paper presents# FIVE (Framework for Interactive Virtual Environments), a framework for
the development of interactive and collaborative virtual environments.# FIVE has been …

[PDF][PDF] Lithology prediction using well logs: A granular computing approach

TM Hossain, J Watada, IA Aziz… - Int. J. Innov. Comput …, 2021‏ - researchgate.net
With the advancement of machine learning and artificial intelligence, the automated
estimation of a bed's complex lithology has become one of the most crucial requirements in …