Survey of optimization algorithms in modern neural networks
The main goal of machine learning is the creation of self-learning algorithms in many areas
of human activity. It allows a replacement of a person with artificial intelligence in seeking to …
of human activity. It allows a replacement of a person with artificial intelligence in seeking to …
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 …
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 …
The fusion of deep learning and fuzzy systems: A state-of-the-art survey
Deep learning presents excellent learning ability in constructing learning model and greatly
promotes the development of artificial intelligence, but its conventional models cannot …
promotes the development of artificial intelligence, but its conventional models cannot …
Multi-correntropy fusion based fuzzy system for predicting DNA N4-methylcytosine sites
The identification of DNA N4-methylcytosine (4mC) sites is an important field of
bioinformatics. Statistical learning methods and deep learning have been applied in this …
bioinformatics. Statistical learning methods and deep learning have been applied in this …
Hierarchical fuzzy regression tree: A new gradient boosting approach to design a TSK fuzzy model
Z Mei, T Zhao, X Xie - Information Sciences, 2024 - Elsevier
This paper proposes a novel gradient-boosting-based ensemble system with a fuzzy
regression tree (FRT) as its base component for regression tasks. FRT first initializes the rule …
regression tree (FRT) as its base component for regression tasks. FRT first initializes the rule …
[PDF][PDF] Interval type-2 fuzzy sets and systems: Overview and outlook
WU Dongrui, Z Zhi-Gang, MO Hong, W Fei-Yue - ACTA Autom. Sin, 2020 - aas.net.cn
Type-1 fuzzy sets can model the linguistic uncertainty from a single user, ie, intra-personal
uncertainty. Type-1 fuzzy systems have been widely used in controls and machine learning …
uncertainty. Type-1 fuzzy systems have been widely used in controls and machine learning …
Privacy-preserving domain adaptation for motor imagery-based brain-computer interfaces
Objective: Electroencephalogram (EEG) is one of the most widely used signals in motor
imagery (MI) based brain-computer interfaces (BCIs). Domain adaptation has been …
imagery (MI) based brain-computer interfaces (BCIs). Domain adaptation has been …
C-loss based higher order fuzzy inference systems for identifying DNA N4-methylcytosine sites
DNA methylation is an epigenetic marker that plays an important role in the biological
processes of regulating gene expression, maintaining chromatin structure, imprinting genes …
processes of regulating gene expression, maintaining chromatin structure, imprinting genes …
[HTML][HTML] Enabling federated learning of explainable AI models within beyond-5G/6G networks
The quest for trustworthiness in Artificial Intelligence (AI) is increasingly urgent, especially in
the field of next-generation wireless networks. Future Beyond 5G (B5G)/6G networks will …
the field of next-generation wireless networks. Future Beyond 5G (B5G)/6G networks will …