Actively semi-supervised deep rule-based classifier applied to adverse driving scenarios
This paper presents an actively semi-supervised multi-layer neuro-fuzzy modeling method,
ASSDRB, to classify different lighting conditions for driving scenes. ASSDRB is composed of …
ASSDRB, to classify different lighting conditions for driving scenes. ASSDRB is composed of …
X-Fuzz: An Evolving and Interpretable Neurofuzzy Learner for Data Streams
While evolving neuro-fuzzy systems have shown promise for learning from non-stationary
streaming data with concept drift, most existing models lack transparency due to the limited …
streaming data with concept drift, most existing models lack transparency due to the limited …
Recurrent neural network models for myoelectricbased control of a prosthetic hand
This paper proposes a set of recurrent neural networks (RNNs) capable of replicating the
non-linear mechanism of a prosthetic hand based on surface myoelectric sensors. The …
non-linear mechanism of a prosthetic hand based on surface myoelectric sensors. The …
Self-boosting first-order autonomous learning neuro-fuzzy systems
In this paper, a detailed mathematical analysis of the optimality of the premise and
consequent parts of the recently introduced first-order Autonomous Learning Multi-Model …
consequent parts of the recently introduced first-order Autonomous Learning Multi-Model …
Explainable density-based approach for self-driving actions classification
This paper describes a new self-organizing neuro-fuzzy approach to autonomously learn
interpretable models by self-driving cars. A new explainable self-organizing architecture and …
interpretable models by self-driving cars. A new explainable self-organizing architecture and …
Fuzzy neural networks based on fuzzy logic neurons regularized by resampling techniques and regularization theory for regression problems
PV de Campos Souza, AJ Guimaraes… - Inteligencia …, 2018 - journal.iberamia.org
This paper presents a novel learning algorithm for fuzzy logic neuron based on neural
networks and fuzzy systems able to generate accurate and transparent models. The learning …
networks and fuzzy systems able to generate accurate and transparent models. The learning …
Numerical study on the feasibility of dynamic evolving neural-fuzzy inference system for approximation of compressive strength of dry-cast concrete
This paper assesses effectiveness of dynamic evolving neural-fuzzy inference system
(DENFIS) models in predicting the compressive strength of dry-cast concretes, and …
(DENFIS) models in predicting the compressive strength of dry-cast concretes, and …
Unsupervised classification of data streams based on typicality and eccentricity data analytics
In this paper, we propose a novel approach to unsupervised and online data classification.
The algorithm is based on the statistical analysis of selected features and development of a …
The algorithm is based on the statistical analysis of selected features and development of a …
A semi-supervised deep rule-based classifier for robust finger knuckle-print verification
Today, biometric recognition systems play an important role in various applications of
different domains. Despite remarkable progress, their performance remains insufficient for …
different domains. Despite remarkable progress, their performance remains insufficient for …
Empirical fuzzy sets
PP Angelov, X Gu - International journal of intelligent systems, 2018 - Wiley Online Library
In this paper, we introduce a new form of describing fuzzy sets (FSs) and a new form of fuzzy
rule‐based (FRB) systems, namely, empirical fuzzy sets (εFSs) and empirical fuzzy rule …
rule‐based (FRB) systems, namely, empirical fuzzy sets (εFSs) and empirical fuzzy rule …