基于支持向量机(SVM)的古代玻璃制品分类  

Classification of Ancient Glass Products Based on Support Vector Machine(SVM)

作　　者：高国云 王青芸[1] GAO Guoyun;WANG Qingyun(School of Mathematics and Computer Science,Gannan Normal University,Ganzhou 341000,China)

机构地区：[1]赣南师范大学数学与计算机科学学院,江西赣州341000

出　　处：《赣南师范大学学报》2024年第3期19-22,共4页Journal of Gannan Normal University

基　　金：江西省自然科学基金(20224BAB201014);赣州市科技计划项目(2023PNS16940)。

摘　　要：古代玻璃制品是古丝绸之路交易的商品之一,一般依据化学成分对玻璃制品进行分类.但是风化会改变玻璃制品化学成分的含量,从而影响玻璃制品类型的鉴别.本文尝试先预测风化前的化学成分以消除风化的影响,再采用灰色关联分析化学成分的关联关系以及差异,最后建立支持向量机(SVM)模型对古代玻璃制品进行分类.Ancient glass products are one of the commodities traded on the ancient Silk Road.Ancient glass products were generally classified based on their chemical composition,but weathering can affect the identification of glass types.Therefore,this article attempts to predict the chemical composition before weathering to eliminate the influence of weathering,then use grey correlation analysis to analyze the correlation and differences of chemical composition,and finally establish a support vector machine(SVM)model to classify ancient glass products.

关 键 词：支持向量机(SVM) 系统聚类 灰色关联分析 古代玻璃 玻璃风化 

分 类 号：O29[理学—应用数学]