Evolving Intelligent Systems: Methodology and Applications

323 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Actively Semi-Supervised Deep Rule-based Classifier Applied to Adverse Driving Scenarios (2019, background): “A promising approach to deal with large amounts of data is through the use of a class of methods known as evolving intelligent systems [10-14].”
Detecting concept drift in data streams using model explanation (2018, background): “C E A notable group of methods are evolving learners, which continually develop their structure, functionality and internal knowledge representation through learning and interacting with the environment (Angelov et al., 2010; Lughofer, 2011; Kasabov, 2007).”
Novelty Detection and Learning from Extremely Weak Supervision (2019, background): “Evolving learning, ability of the algorithms to adapt their parameters and structure according to the non-stationary data streams, is a more sophisticated form of online learning [16, 17].”