基于PCA与Markov残差灰色模型的京津冀物流能力评价和预测
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摘要
采用主成分分析法和Markov残差灰色模型对京津冀物流能力进行评价和预测。综合研究表明,京津冀物流能力在2007年至2016年总体较为平稳,河北省近两年物流能力有所下降,北京市近五年物流能力有所起伏,天津市物流能力逐年提升,势头强劲。在未来五年,旅客周转量、客运量将成为制约河北省物流能力提升的重要指标,货运量、客运量将成为制约北京市物流能力提升的重要指标,邮电业务总量和货物周转量将成为制约天津市物流能力提升的重要指标。
This paper adopts the principal component analysis method and the Markov residual grey model to evaluate and predict the logistics capability of Beijing,Tianjin and Hebei.Comprehensive research shows that the logistics capacities of Beijing,Tianjin and Hebei are relatively stable from2007 to 2016.The logistics capacity of Hebei has declined in recent two years;the logistics capacity of Beijing has fluctuated in recent five years,and the logistics capability of Tianjin has increased year by year with a strong momentum.In the next five years,turnover of passenger traffic and passenger volume will become important indicators for Hebei province to enhance its logistics capability,freight volume and passenger traffic will become important factors that can restrict the promotion of logistics capacity of Beijing,and total volume of post and telecommunications services and turnover of freight traffic will become important index to restrict the improvement of Tianjin logistics capability.
This paper adopts the principal component analysis method and the Markov residual grey model to evaluate and predict the logistics capability of Beijing,Tianjin and Hebei.Comprehensive research shows that the logistics capacities of Beijing,Tianjin and Hebei are relatively stable from2007 to 2016.The logistics capacity of Hebei has declined in recent two years;the logistics capacity of Beijing has fluctuated in recent five years,and the logistics capability of Tianjin has increased year by year with a strong momentum.In the next five years,turnover of passenger traffic and passenger volume will become important indicators for Hebei province to enhance its logistics capability,freight volume and passenger traffic will become important factors that can restrict the promotion of logistics capacity of Beijing,and total volume of post and telecommunications services and turnover of freight traffic will become important index to restrict the improvement of Tianjin logistics capability.
引文
[1]陈吉铭,刘芳,何忠伟,等.京津冀乳制品冷链物流能力评价及地区差异研究[J].中国畜牧杂志,2018,(1):138-142.
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[13]朱念,陈东升,何昌勤,等.基于灰色GM(1,N)模型的广西北部湾港口物流预测研究[J].数学的实践与认识,2017,(23):303-310.
[14]杨荣英,张辉,苗张木.物流预测技术中的移动平均线方法[J].武汉理工大学学报(交通科学与工程版),2001,(3):353-355.
[15]张国玲,徐学红.一种基于ARIMA-BPNN的物流需求预测模型[J].控制工程,2017,(5):958-962.
[16]李夏培.基于灰色线性组合模型的农产品物流需求预测[J].北京交通大学学报(社会科学版),2017,16(1):120-126.
[17]孟建军,杨泽青.基于模糊神经网络的民航物流预测研究与仿真分析[J].计算机工程与设计,2010,(10):1056-1059.
[18]王卫群.灰色-马尔柯夫预测模型在物流产品回收中的应用研究[J].物流技术,2012,(19):154-156.
[19]王宣承,刘恩猛,程展兴,等.基于季节分解和神经网络的物流预测混合模型[J].统计与决策,2014,(11):80-82.
[20]原静.正向权重组合预测机制下的农产品冷链物流需求量预测[J].江苏农业科学,2017,(19):341-346.
[21]周泰,袁波,廖伟,等.中国西部区域物流能力的灰色聚类分析[J].北京交通大学学报(社会科学版),2016,15(1):117-121.
[2]马向国,梁艳,杨慧慧,等.基于模糊物元法的京津冀区域应急物流能力评价[J].物流技术,2017,(8):87-94.
[3]黎建强,曾立彪,周艳辉.基于模糊综合评价的企业物流能力评价研究[J].科技管理研究,2009,(1):163-170.
[4]刘鹏.我国物流企业的低碳物流能力评价[J].商业经济研究,2017,(10):87-89.
[5]徐金河.基于GRA和AHP的港口物流能力评价研究[J].重庆工商大学学报(自然科学版),2009,(5):508-513.
[6]周泰,袁波,陈煜.基于TOPDIS的区域物流能力提升方法研究[J].北京交通大学学报(社会科学版),2017,(1):97-101.
[7]冯华,何佳莉,刘洋.供应链物流能力绩效评价体系的调研分析[J].中南财经政法大学学报,2014,(1):113-118.
[8]马士华,陈铁巍.基于供应链的物流服务能力构成要素及评价方法研究[J].计算机集成制造系统,2007,(4):744-750.
[9]CLOSS J,GOLDSNY TJ,CLINTON SR.Information technology influences on world class logistics capability[J].International Journal of Physical Distribution&Logistics Management,1997,27(1):4-17.
[10]ZAWAWI N F B M,WAHAB S A,MAMUN A A.Logistics Capability,Logistics Performance,and the Moderating Effect of Firm Size:Empirical Evidence from East Coast Malaysia[J].Journal of Developing Areas,2017,51(2):171-182.
[11]唐伟鸿,李文锋.基于时间序列的支持向量机在物流预测中的应用[J].物流科技,2005,(1):8-11.
[12]张冲,王燕,李俊.基于AHP和BP神经网络的高速公路物流预测模型研究[J].商场现代化,2007,(28):102.
[13]朱念,陈东升,何昌勤,等.基于灰色GM(1,N)模型的广西北部湾港口物流预测研究[J].数学的实践与认识,2017,(23):303-310.
[14]杨荣英,张辉,苗张木.物流预测技术中的移动平均线方法[J].武汉理工大学学报(交通科学与工程版),2001,(3):353-355.
[15]张国玲,徐学红.一种基于ARIMA-BPNN的物流需求预测模型[J].控制工程,2017,(5):958-962.
[16]李夏培.基于灰色线性组合模型的农产品物流需求预测[J].北京交通大学学报(社会科学版),2017,16(1):120-126.
[17]孟建军,杨泽青.基于模糊神经网络的民航物流预测研究与仿真分析[J].计算机工程与设计,2010,(10):1056-1059.
[18]王卫群.灰色-马尔柯夫预测模型在物流产品回收中的应用研究[J].物流技术,2012,(19):154-156.
[19]王宣承,刘恩猛,程展兴,等.基于季节分解和神经网络的物流预测混合模型[J].统计与决策,2014,(11):80-82.
[20]原静.正向权重组合预测机制下的农产品冷链物流需求量预测[J].江苏农业科学,2017,(19):341-346.
[21]周泰,袁波,廖伟,等.中国西部区域物流能力的灰色聚类分析[J].北京交通大学学报(社会科学版),2016,15(1):117-121.