摘要
为了减少运输过程中碳排放,对高速公路与铁路适运货物进行研究。基于高速公路联网收费调查数据和主动调查数据,采用灰色关联度评价法与改进的K-prototypes聚类算法(DAC KP算法)相结合的方式,对收集到的高速公路大数据进行数据挖掘,得到相应的基于指标权重的聚类模型,得出聚类结果分为3种Cluster。对于部分货物由高速公路改为铁路运输更加适合,减少碳排放29.871%,为下一步运输结构调整提供数据支撑和理论依据。
In order to reduce the carbon emission in the process of transportation,the research on the suitable transportation means of goods by highway and railway is carried out.Based on expressway networking tolling data and investigation data,the grey correlation evaluation method and the improved K-prototypes clustering algorithm(DACKP algorithm)are combined to explore on the data of expressway that collected,so as to obtain the corresponding cluster model that based on weight of indexes.It is concluded that three types of Cluster are obtained from the clustering results.It is more suitable for some goods to be transported by railway instead of expressway,and the carbon emission can be reduced by 29.871%.The results can provide data support and theoretical basis for the further transport structure adjustment.
作者
朱朋朋
蔡玉贺
楼国良
米良
宋媛媛
ZHU Peng-peng;CAI Yu-he;LOU Guo-liang;MI Liang;SONG Yuan-yuan(Chang'an University,Xi'an 710064,China;China Communications News,Beijing 100101,China;Transport Planning and Research Institute Ministry of Transport,Beijing 100020,China)
出处
《公路》
北大核心
2021年第9期260-265,共6页
Highway
基金
大气重污染成因与治理攻关项目,项目编号DQGG0207-03
国家重点研发计划重点专项,项目编号2017YFC0212103。