基于支持向量机算法的葡萄酒质量检测模型  

Wine Quality Detection Model Based on Support Vector Machine Algorithm

作　　者：张一明 魏霖静[2] ZHANG Yiming;WEI Linjing(College of Science,Gansu Agricultural University;College of Information Science and Technology,Gansu Agricultural University,Lanzhou 730070,China)

机构地区：[1]甘肃农业大学理学院 [2]甘肃农业大学信息科学技术学院,甘肃兰州730070

出　　处：《软件导刊》2024年第9期137-142,共6页Software Guide

基　　金：科技部外专项目(G2022042005L);兰州市人才创新创业项目(2021-RC-47)。

摘　　要：随着我国经济的不断发展,葡萄酒作为一种悦人悦己的生活媒介已经登上大众餐桌。然而,葡萄酒的质量检测仍以品酒师品尝为主,已不能满足规模化、智能化的食品工业发展需求。为此,基于支持向量机算法对葡萄酒理化指标进行建模,利用R语言实现Box-plot法对异常值进行处理,同时对RBF核的支持向量机参数进行优化,最终得到一个精度达到96.46%的葡萄酒质量检测模型,为葡萄酒的质量控制提供了一条行之有效的途径。With the continuous development of our country′s economy,wine,as a delightful medium of life,has entered the public dining ta-ble.However,the quality inspection of wine is still mainly based on the tasting of wine tasters,which can no longer meet the needs of the large-scale and intelligent development of the food industry.Therefore,based on the support vector machine algorithm,the physicochemical indicators of wine were modeled,and the Box plot method was implemented using R language to handle outliers.At the same time,the support vector machine parameters of the RBF kernel were optimized,resulting in a wine quality detection model with an accuracy of 96.46%.This pro-vides an effective approach for wine quality control.

关 键 词：支持向量机 R语言 Box-plot法 葡萄酒质量检测 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]