This paper presents a novel approach to generate data-driven regression models that not only give reliable prediction of the observed data but also have smoother response surfaces and extra ...

This innovative approach combines traditional symbolic regression with large language models (LLMs) to introduce a new layer of efficiency and accuracy. The researchers designed LASR to build a ...

Symbolic Regression remains an NP-Hard problem, with extensive research focusing on AI models for this task. We propose applying k-fold cross-validation to a transformer-based symbolic regression ...

This paper proposes eco-control optimization with consideration of the physics model informed by data-model to emphasize the maritime carbon emissions reduction problem. More specifically, our work ...

What makes Symbolic Modeling particularly innovative is its ability to discover a unified mathematical model that can represent multiple assets simultaneously. Unlike traditional Symbolic Regression, ...