NGBoost algorithm-based prediction of mechanical properties of a hot-rolled strip and its interpretability research with ANOVA values
Hot-rolled strip steel is an essential material extensively used in various industrial fields, with its mechanical properties being critical to product quality and engineering design. This article presents a method for predicting the mechanical properties of hot-rolled strip steel using the NGBoost...
Gespeichert in:
| Veröffentlicht in: | AIMS mathematics Jg. 9; H. 11; S. 33000 - 33022 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
AIMS Press
01.01.2024
|
| Schlagworte: | |
| ISSN: | 2473-6988, 2473-6988 |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Zusammenfassung: | Hot-rolled strip steel is an essential material extensively used in various industrial fields, with its mechanical properties being critical to product quality and engineering design. This article presents a method for predicting the mechanical properties of hot-rolled strip steel using the NGBoost (natural gradient boosting) algorithm. The study focused on predicting tensile strength, yield strength, and elongation of hot-rolled strip steel and compared the predictive results with those obtained from the gradient boosting algorithm, Lasso regression, and decision tree algorithms. The results indicated that the NGBoost algorithm performs well on average coverage error (ACE) and prediction interval absolute width (PIAW) values at different confidence levels, demonstrating strong predictive performance. Furthermore, the analysis of variance (ANOVA) method was employed to identify factors that significantly impact mechanical performance, providing theoretical support for optimizing design schemes and enhancing structural safety and reliability. |
|---|---|
| ISSN: | 2473-6988 2473-6988 |
| DOI: | 10.3934/math.20241578 |