An adaptive neuro-fuzzy system with integrated feature selection and rule extraction for high-dimensional classification problems
A major limitation of fuzzy or neuro-fuzzy systems is their failure to deal with high-
dimensional datasets. This happens primarily due to the use of T-norm, particularly, product …
dimensional datasets. This happens primarily due to the use of T-norm, particularly, product …
[图书][B] Granular computing: analysis and design of intelligent systems
W Pedrycz - 2018 - taylorfrancis.com
Information granules, as encountered in natural language, are implicit in nature. To make
them fully operational so they can be effectively used to analyze and design intelligent …
them fully operational so they can be effectively used to analyze and design intelligent …
Nonstationary fuzzy neural network based on FCMnet clustering and a modified CG method with Armijo-type rule
Nonstationary fuzzy inference systems (NFISs) model the variation in opinions of individual
experts and expert groups. They have the capability similar to type-2 fuzzy systems in some …
experts and expert groups. They have the capability similar to type-2 fuzzy systems in some …
A smoothing group lasso based interval type-2 fuzzy neural network for simultaneous feature selection and system identification
Inspired by the life philosophy, an ingenious gate (membership) function, which can mimic
the open and close of the gate in the real world, is proposed to realize feature selection (FS) …
the open and close of the gate in the real world, is proposed to realize feature selection (FS) …
GENEFIS: Toward an effective localist network
M Pratama, SG Anavatti… - IEEE Transactions on …, 2013 - ieeexplore.ieee.org
Nowadays, there is increasing demand for an integrated system usable to real-time
environments under limited computational resources and minimum operator supervision. In …
environments under limited computational resources and minimum operator supervision. In …
Intelligent global sliding mode control using recurrent feature selection neural network for active power filter
S Hou, Y Chu, J Fei - IEEE Transactions on Industrial …, 2020 - ieeexplore.ieee.org
This study develops an intelligent global sliding mode control using recurrent feature
selection neural network for active power filter (APF). First, the dynamic model of an APF is …
selection neural network for active power filter (APF). First, the dynamic model of an APF is …
pClass: an effective classifier for streaming examples
In this paper, a novel evolving fuzzy-rule-based classifier, termed parsimonious classifier
(pClass), is proposed. pClass can drive its learning engine from scratch with an empty rule …
(pClass), is proposed. pClass can drive its learning engine from scratch with an empty rule …
Fuzzy rule-based approach for software fault prediction
Knowing faulty modules prior to testing makes testing more effective and helps to obtain
reliable software. Here, we develop a framework for automatic extraction of human …
reliable software. Here, we develop a framework for automatic extraction of human …
Dg-aletsk: a high-dimensional fuzzy approach with simultaneous feature selection and rule extraction
Fuzzy or neuro-fuzzy systems have been successfully employed in many areas, but their
limitation in solving high-dimensional problems remains a challenging task. On the other …
limitation in solving high-dimensional problems remains a challenging task. On the other …
An interval type-2 neural fuzzy system for online system identification and feature elimination
We propose an integrated mechanism for discarding derogatory features and extraction of
fuzzy rules based on an interval type-2 neural fuzzy system (NFS)-in fact, it is a more general …
fuzzy rules based on an interval type-2 neural fuzzy system (NFS)-in fact, it is a more general …