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Academic Journal of Mathematical Sciences, 2022, 3(2); doi: 10.25236/AJMS.2022.030209.

Multiple regression-based glass composition prediction and statistics

Author(s)

Xiaohan Deng1, Tangliang Wang2

Corresponding Author:
Xiaohan Deng
Affiliation(s)

1College of Science, Chongqing University of Technology, Chongqing, 400054, China

2College of Mechanical Engineering, Chongqing University of Technology, Chongqing, 400054, China

Abstract

The surface weathering of ancient glass can be distinguished from the type of ancient glass by chemical composition as well as color and ornamentation. This paper constructs mathematical models to analyze the relationship between surface weathering and glass type, color and ornamentation based on different chemical compositions and characteristic data of color and ornamentation in ancient glass, explores the statistical law of chemical composition content with and without weathering, and constructs an effective classification model to realize glass type classification. This paper solves the relationship between glass type, decoration and color and their weathering degree; analyzes the statistical law of chemical composition content with and without weathering on the surface of two types of glass; derives the prediction formula and predicts the chemical composition content of two types of glass before weathering.

Keywords

Random Forest Model; Multiple Regression Model; High Potassium Glass; Lead Barium Glass

Cite This Paper

Xiaohan Deng, Tangliang Wang. Multiple regression-based glass composition prediction and statistics. Academic Journal of Mathematical Sciences (2022) Vol. 3, Issue 2: 57-62. https://doi.org/10.25236/AJMS.2022.030209.

References

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