基于随机森林和支持向量机的古代玻璃制品成分分析与鉴别

我国古代玻璃制品受环境的影响极易被风化,对风化后的玻璃制品进行成分分析与鉴别为后续研究工作的开展提供理论依据。针对古代玻璃的成分分析与鉴别的问题,该文首先对一批我国古代玻璃制品的成分数据进行清洗工作和统计分析,在此基础上建立随机森林模型分析高钾玻璃和铅钡玻璃的分类规律,并通过聚类分析确定2类玻璃的亚分类,其次构建基于支持向量机的鉴别模型确定待分类玻璃的类别及其亚类。最后对模型分别进行灵敏度分析,验证模型的合理性和有效性。

China's ancient glass products are easily weathered by the environment.The composition analysis and identification of weathered glass products is the theoretical basis for the follow-up research work.Aiming at the problem of composition analysis and identification of ancient glass,this paper first carries out cleaning and statistical analysis on the composition data of a number of ancient glass products in China.On this basis,a random forest model is established to analyze the classification of high potassium glass and lead-barium glass,and the subclassification of the two types of glass is determined by cluster analysis,and then support vector machines are constructed to determine their categories and subclasses.Finally,the sensitivity of the model is analyzed to verify the rationality and validity of the model.