A Hermite spline model for data regression

IF 5.4 3区材料科学 Q2 CHEMISTRY, PHYSICAL

ACS Applied Energy Materials Pub Date : 2024-09-30 DOI:10.1016/j.matcom.2024.09.011

Rosanna Campagna , Mariantonia Cotronei , Domenico Fazzino

引用次数: 0

Abstract

This paper introduces a novel Hermite spline model for data regression, integrating both function values and derivatives along with a penalty term to control smoothness. A comparative analysis is conducted with conventional penalized models, specifically with P-spline models. The primary objective of this study is to empirically demonstrate the superior performance of the proposed model in reconstructing data, even in the absence of a penalty term (pure regression).

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用于数据回归的赫米特样条模型

本文介绍了一种用于数据回归的新型 Hermite 样条模型，该模型同时整合了函数值和导数以及用于控制平滑度的惩罚项。本文与传统的惩罚模型，特别是 P-样条模型进行了比较分析。本研究的主要目的是通过实证证明，即使在没有惩罚项（纯回归）的情况下，所提出的模型在重建数据方面也具有卓越的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

ACS Applied Energy Materials Materials Science-Materials Chemistry

CiteScore

10.30

自引率

6.20%

发文量

1368

期刊介绍： ACS Applied Energy Materials is an interdisciplinary journal publishing original research covering all aspects of materials, engineering, chemistry, physics and biology relevant to energy conversion and storage. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important energy applications.