State of the art Symbolic Regression (SR) methods currently build specialized models, while
the application of Large Language Models (LLMs) remains largely unexplored. In this work …

Currently, applications of the algorithms based on artificial intelligence (AI) principles can be
observed in various fields. This can be also noticed in the wide area of electrical drives …

This paper presents a novel approach to power converter design and optimization, where
the optimal component characteristics for a DC-DC converter architecture are selected given …

Power converters are pervasive in modern electronic component design. They can be found
in all electronic devices from household appliances and cellphone chargers to vehicles …

Symbolic optimization methods have been used to solve varied challenging and relevant
problems such as symbolic regression and neural architecture search. However, the current …

Design optimization of dc-dc converters at the component level can be assisted by machine
learning (ML) techniques, where component models are trained using large amounts of …

Reinforcement Learning (RL) has been used to solve numerous application problems with
impressive performance. Super or experthuman performance has been achieved in varied …

Symbolic Optimization has been used to solve varied challenging and relevant problems
such as Symbolic Regression and Neural Architecture Search. However, the current state-of …

In this paper, we present an intelligent system that has the capabilities of automatically
selecting topology classes and optimizing circuit parameters of DC-DC power converters for …

The design of switched-mode power converters at the component level can be assisted by
machine-learning (ML) techniques, where component models are trained using large …