基于SVM的进口纺织服装固体废物属性风险等级鉴别  

Identification of risk level of imported textile and clothing solid waste properties based on SVM

作　　者：赵介军 毛立 姚静 过峰 Zhao Jiejun;Mao Li;Yao Jing;Guo Feng(Wuxi Customs House District P.R.China,Wuxi 214101,China)

机构地区：[1]无锡海关,江苏无锡214101

出　　处：《纺织报告》2022年第5期28-30,39,共4页

基　　金：2020年度南京海关科研项目计划(2020KJ29)。

摘　　要：针对纺织服装类产品进口时固体废物属性难以鉴别的问题,文章结合国家相关法律法规和专家经验,建立了纺织服装类产品固废属性风险等级鉴定体系,提供了详细可行的纺织服装类产品固废属性风险等级鉴定标准,用于指导监管部门对进口纺织品固废的鉴定工作。该鉴别标准有31个指标,涵盖货物源头风险、掺杂夹带风险、卫生安全风险、机械安全风险及丧失使用价值风险。以这些指标为输入,通过支持向量机(SVM)算法构建的智能鉴别方法,可以将纺织服装类产品的风险等级识别为低风险、中风险和高风险。为了验证该方法的有效性和实用性,使用了监管部门提供的鉴定案例。结果表明,该识别方法具有较高的自学能力和准确性。Aiming at the problem that it is difficult to identify the properties of solid waste when importing textile and clothing products,combined with relevant national laws and regulations and expert experience,this paper establishes the risk level identification system of solid waste properties of textile and clothing products,and provides a detailed and feasible risk level identification standard of solid waste of textile and clothing products,which is used to guide the supervision department to identify the imported textile solid waste.The identification standard has 31 indicators,covering the source risk of goods,doping and entrainment risk,health and safety risk,machinery safety risk and loss of use value risk.Taking these indicators as input,the intelligent identification method constructed by support vector machine(SVM)algorithm can identify the risk level of textile and clothing products as low risk,medium risk and high risk.In order to verify the effectiveness and practicability of this method,the identification cases provided by the regulatory authorities are used.The results show that the recognition method has strong self-learning ability and accuracy.

关 键 词：纺织品进口 固体废物属性 风险鉴别 支持向量机 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]