This technical FAQ examines three modeling gaps identified in engineering literature and outlines algorithmic methods to address them.

Abstract: This paper presents a novel approach to practical nonlinear model predictive control (PNMPC) using Kolmogorov–Arnold networks (KANs) as prediction models. KANs are based on the ...

Abstract: Modeling of nonlinear loads is crucial for analyzing and evaluating power quality in modern power system. To further enhance both accuracy and robustness, a novel data-driven nonlinear load ...

Moreover, we discuss strategies for metadata selection and human evaluation to ensure the quality and effectiveness of ITDs. By integrating these elements, this tutorial provides a structured ...

A comprehensive repository for fine-tuning the Donut model for document image classification and parsing tasks. This project provides optimized training pipelines using Hugging Face Transformers with ...