Partial discharge classifications: Review of recent progress
It is well known that a correlation exist between the pattern of partial discharge (PD)
behavior and the insulation quality. Since different sources of partial discharge have their …
behavior and the insulation quality. Since different sources of partial discharge have their …
Microgrid energy management systems design by computational intelligence techniques
With the capillary spread of multi-energy systems such as microgrids, nanogrids, smart
homes and hybrid electric vehicles, the design of a suitable Energy Management System …
homes and hybrid electric vehicles, the design of a suitable Energy Management System …
Fuzzy min–max neural networks: a bibliometric and social network analysis
ÖN Kenger, E Özceylan - Neural Computing and Applications, 2023 - Springer
The amount of digital data in the universe is growing at an exponential rate with the rapid
development of digital information, and this reveals new machine learning methods …
development of digital information, and this reveals new machine learning methods …
An on-line algorithm for creating self-organizing fuzzy neural networks
G Leng, G Prasad, TM McGinnity - Neural Networks, 2004 - Elsevier
This paper presents a new on-line algorithm for creating a self-organizing fuzzy neural
network (SOFNN) from sample patterns to implement a singleton or Takagi-Sugeno (TS) …
network (SOFNN) from sample patterns to implement a singleton or Takagi-Sugeno (TS) …
Data-core-based fuzzy min–max neural network for pattern classification
A fuzzy min–max neural network based on data core (DCFMN) is proposed for pattern
classification. A new membership function for classifying the neuron of DCFMN is defined in …
classification. A new membership function for classifying the neuron of DCFMN is defined in …
An enhanced fuzzy min–max neural network for pattern classification
MF Mohammed, CP Lim - IEEE transactions on neural networks …, 2014 - ieeexplore.ieee.org
An enhanced fuzzy min-max (EFMM) network is proposed for pattern classification in this
paper. The aim is to overcome a number of limitations of the original fuzzy min-max (FMM) …
paper. The aim is to overcome a number of limitations of the original fuzzy min-max (FMM) …
A fuzzy min-max neural network classifier with compensatory neuron architecture
AV Nandedkar, PK Biswas - IEEE transactions on neural …, 2007 - ieeexplore.ieee.org
This paper proposes a fuzzy min-max neural network classifier with compensatory neurons
(FMCNs). FMCN uses hyperbox fuzzy sets to represent the pattern classes. It is a supervised …
(FMCNs). FMCN uses hyperbox fuzzy sets to represent the pattern classes. It is a supervised …
Faster self-organizing fuzzy neural network training and a hyperparameter analysis for a brain–computer interface
This paper introduces a number of modifications to the learning algorithm of the self-
organizing fuzzy neural network (SOFNN) to improve computational efficiency. It is shown …
organizing fuzzy neural network (SOFNN) to improve computational efficiency. It is shown …