With the growing popularity of machine learning (ML), regression problems in many
domains are becoming increasingly high-dimensional. Identifying relevant features from a …

Computational cost in metaheuristics such as Evolutionary Algorithm (EAs) is often a major
concern, particularly with their ability to scale. In data-based training, traditional EAs typically …

The problem of data classification or data fitting is widely applicable in a multitude of
scientific areas, and for this reason, a number of machine learning models have been …

Sequential circuits are time-dependent circuits whose output depends not only on their
current inputs but also on previous ones. This makes them substantially more complex than …

By the very nature of its representation, symbolic regression through Grammatical Evolution
(GE) stands a chance of being interpretable. However, while GE builds solutions using …

Quickly designing correct and efficient digital circuits is a crucial need for the electronics
industry. Several Electronic Design Automation tools are used for this task. Still, they often …

The importance of designing efficient and accurate digital circuits has grown due to the
widespread use of wearable, ready-made, and custom electronic products. These digital …

Simbolicka regresija predstavlja tip regresione analize. Njen cilj je pronalazak modela kojim
se najbolje opisuje dati skup podataka. Proces formiranja modela se sastoji od pretrage …

Grammar is a key input in grammar-based genetic programming. Grammar design not only
influences performance, but also program size. However, grammar design and the choice of …