دورية أكاديمية
A color prediction model for mending materials of the Yuquan Iron Pagoda in China based on machine learning
| العنوان: | A color prediction model for mending materials of the Yuquan Iron Pagoda in China based on machine learning |
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| المؤلفون: | Xuegang Liu, Yuhang Liu, Ke Wang, Yang Zhang, Yang Lei, Hai An, Mingqiang Wang, Yuqiu Chen |
| المصدر: | Heritage Science, Vol 12, Iss 1, Pp 1-15 (2024) |
| بيانات النشر: | SpringerOpen, 2024. |
| سنة النشر: | 2024 |
| المجموعة: | LCC:Fine Arts LCC:Analytical chemistry |
| مصطلحات موضوعية: | Iron pagoda, Rust removal, Mending materials, Color prediction, Machine learning, Fine Arts, Analytical chemistry, QD71-142 |
| الوصف: | Abstract During the restoration of iron cultural relics, the removal of rust from these artifacts is necessary. However, this rust removal process may lead to inconsistent local color on the iron relics. To address this, mending materials are applied to treat the surface, ensuring consistent local color. In the surface treatment of iron cultural relics, a significant challenge lies in modulating the color of these mending materials. The corrosion products of Yuquan Iron Pagoda are mainly Fe3O4, γ-FeO(OH), α-FeO(OH) and α-Fe2O3, with contents of 13.1, 16.1, 40.2 and 30.6%, respectively. Due to their structural stability and suitable color characteristics, Fe3O4 and α-Fe2O3 are selected as the primary raw materials for the repair material. This study employs machine learning methods to predict the color of mending materials corresponding to varying contents of α-Fe2O3, Fe3O4, and epoxy resin. The Artificial Neural Network (ANN), eXtreme Gradient Boosting (XGBoost), and Light Gradient Boost Machine (LightGBM) algorithms are utilized to develop the model, and the predictive performance of these three algorithms is compared. XGBoost exhibits the best prediction performance, achieving a square correlation coefficient (R2) of 0.94238 and a mean absolute error (MAE) of 0.68485. Additionally, the SHapley Additive exPlanations (SHAP) method is employed to analyze the most crucial raw material affecting the color of mending materials, which is identified as Fe3O4. The study illustrates the specific process of employing this model by applying it to the surface treatment of the Yuquan Iron Pagoda, demonstrating the practicality of the model. This model can be applied to assist in the surface treatment of other iron cultural relics. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2050-7445 |
| Relation: | https://doaj.org/toc/2050-7445 |
| DOI: | 10.1186/s40494-024-01295-1 |
| URL الوصول: | https://doaj.org/article/4e218d2b46d0498cbebc1239c13247a8 |
| رقم الأكسشن: | edsdoj.4e218d2b46d0498cbebc1239c13247a8 |
| قاعدة البيانات: | Directory of Open Access Journals |
Find this article in full text from Springer Verlag. 
Full Text Finder | تدمد: | 20507445 |
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| DOI: | 10.1186/s40494-024-01295-1 |