Abstract Evolutionary Ensemble Learning (EEL) provides a general approach for scaling
evolutionary learning algorithms to increasingly complex tasks. This is generally achieved …

Gearboxes are widely used in industrial processes as mechanical power transmission
systems. Then, gearbox failures can affect other parts of the system and produce economic …

This paper presents the proposal of a method to recognize emotional states through EEG
analysis. The novelty of this work lies in its feature improvement strategy, based on …

Hypervolume (HV) has become one of the most popular indicators to assess the quality of
Pareto front approximations. However, the best algorithm for computing these values has a …

This chapter reviews the use of Evolutionary Machine Learning (EML) in environmental
science. We cover the various steps of the machine learning pipeline, also addressing topics …

Lack of knowledge is a common consequence of data incompleteness when learning from
real-world data. To deal with such a situation, this work utilizes transfer learning (TL) to …

The uncertain capacitated arc routing problem has many real-world applications in logistics
domains. Genetic programming (GP) is a promising approach to training routing policies to …

The meaningful problem of improving crane safety, reliability, and efficiency is extensively
studied in the literature and targeted via various model-based control approaches. In recent …

Genetic programming (GP) is a powerful machine learning (ML) algorithm that can produce
readable white-box models. Although successfully used for solving an array of problems in …

Computer science is the science that deals with the treatment of information by means of
automatic procedures. It has multiple objectives, including the study of computation at a …