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 ...

In this paper, a novel approach based on symbolic regression is proposed with the aim of exploring slewing bearings’ explicit life models in depth and to predict residual useful life (RUL). The ...

comparison of functions discovered by symbolic regression, and functions discovered by symbolic modeling. GA, UNITED STATES, March 21, 2025 Tuesday, 02 January 2024 12:17 GMT ...

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, ...