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Rough sets and near sets in medical imaging: A review
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 …
approaches to solving various problems in medical imaging such as medical image …
Interval dominance-based feature selection for interval-valued ordered data
Dominance-based rough approximation discovers inconsistencies from ordered criteria and
satisfies the requirement of the dominance principle between single-valued domains of …
satisfies the requirement of the dominance principle between single-valued domains of …
Soft clustering–fuzzy and rough approaches and their extensions and derivatives
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 …
applications in virtually any domain. The huge interest in clustering has led to a possibly …
Fuzzy preference based rough sets
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 …
theory has been successfully extended to deal with preference analysis by replacing …
Multigranulation supertrust model for attribute reduction
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 …
data that are structurally complex and incomplete, traditional attribute reduction methods are …
Using fuzzy inference system for architectural space analysis
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 …
architectural construction, in many cases its boundaries are uncertain, leading intuitive …
Biological image classification using rough-fuzzy artificial neural network
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 …
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 …
effective computation of approximations is very important for improving the performance of …
# FIVE: High-level components for develo** collaborative and interactive virtual environments
This paper presents# FIVE (Framework for Interactive Virtual Environments), a framework for
the development of interactive and collaborative virtual environments.# FIVE has been …
the development of interactive and collaborative virtual environments.# FIVE has been …
[PDF][PDF] Lithology prediction using well logs: A granular computing approach
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 …
estimation of a bed's complex lithology has become one of the most crucial requirements in …