摘要
为了充分挖掘绿色货运中的数据价值,促进货运业碳减排。提出一种基于大数据挖掘和偏好顺序结构评估法的绿色货运绩效评价方法。在深入分析绿色货运绩效影响因素的基础上,确定评价指标体系,采用蓝鲸大数据挖掘软件进行建模,以物流云平台模式下绿色货运项目数据为样本进行K-means聚类分析。利用傅勒三角形法确定评价指标权重,采用偏好顺序结构评估法,借助Visual PROMETHEE软件对聚类分析结果进行验证,并对30辆货车的绿色运输绩效做出全面深层次评价。针对样本货车运输中存在的问题,提出了公路货运业碳排放管理策略。
In order to fully discover the data value in green freight transport and promote carbon emission reduction in freight transport industry,a performance evaluation method of green freight that based on big data mining and promethee was proposed.Based on the in-depth analyzed of the influencing factors in green freight performance,the evaluation index system was determined,and the Blue Whale big data mining software was used to model construction.The K-means cluster analysis was conducted with green freight project data under the logistics cloud platform model as the sample.Fourier triangle method was used to determine the weight of the evaluation index,and the preference order structure evaluation method was used to verify the clustering analysis results by means of Visual PROMETHEE software,and a comprehensive and in-depth evaluation of the green transport performance of 30 trucks was made.Aimed at the problems existing in the sample truck transportation,the carbon emission management countermeasures of road freight industry were proposed.
作者
秦新生
QIN Xinsheng(School of Management,Guangzhou College of Commerce,Guangzhou 511363,China)
出处
《物流科技》
2023年第15期54-59,共6页
Logistics Sci-Tech
基金
广东省普通高校特色创新类(人文社科)项目“面向智能制造的广东绿色供应链金融系统协同研究”(2021WTSCX105)
广州市哲学社科规划项目“广州加快低碳发展推动绿色化转型研究:‘双碳’战略下产业供应链绿色低碳多重耦合协同演进视角”(2022GZGJ85)。
