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Found 7 papers, 1 papers with code
EGNN-C+: Interpretable Evolving Granular Neural Network and Application in Classification of Weakly-Supervised EEG Data Streams
As an application, we focus on the classification of emotion-related patterns within electroencephalogram (EEG) signals.
Adaptive Gaussian Fuzzy Classifier for Real-Time Emotion Recognition in Computer Games
We analyze the effect of individual electrodes, time window lengths, and frequency bands on the accuracy of user-independent eGFCs.
Incremental Learning and State-Space Evolving Fuzzy Control of Nonlinear Time-Varying Systems with Unknown Model
We present a method for incremental modeling and time-varying control of unknown nonlinear systems.
Real-Time Anomaly Detection in Data Centers for Log-based Predictive Maintenance using an Evolving Fuzzy-Rule-Based Approach
Log records in the data center is a stochastic and non-stationary phenomenon in nature.
EGFC: Evolving Gaussian Fuzzy Classifier from Never-Ending Semi-Supervised Data Streams -- With Application to Power Quality Disturbance Detection and Classification
Power-quality disturbances lead to several drawbacks such as limitation of the production capacity, increased line and equipment currents, and consequent ohmic losses; higher operating temperatures, premature faults, reduction of life expectancy of machines, malfunction of equipment, and unplanned outages.
Comparison of Evolving Granular Classifiers applied to Anomaly Detection for Predictive Maintenance in Computing Centers
Evolving granular classifiers are suited to learn from time-varying log streams and, therefore, perform online classification of the severity of anomalies.
Unsupervised Fuzzy eIX: Evolving Internal-eXternal Fuzzy Clustering
Time-varying classifiers, namely, evolving classifiers, play an important role in a scenario in which information is available as a never-ending online data stream.
