聚类分析理论在港口规模确定中的应用研究
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摘要
随着世界经济与贸易的发展,我国港口的现代化建设也在如火如荼地进行。有效地确定港口规模、研究各种港口吞吐量预测方法的选择理论,对于正确预测未来港口吞吐量,指导港口规划建设,确定港口投资规模和促进地区经济的发展具有极其重要的战略意义。传统的港口规模确定的研究更侧重于宏观规划决策,往往受到主观因素的影响较大;而传统的对预测方法研究主要集中于对方法本身的改进,忽视了对各种预测方法的选择。本文尝试采用实证研究的方法,将历史经验数据作为理论研究的基石,通过对大量历史数据的统计分析,采用聚类分析法将不同规模的港口分成若干层次,分析了港口运量增长规律的差异性,并对比了几种预测模型在对不同类型港口进行预测时适用性。
本文阐述了聚类分析的基本原理,对港口规模的影响因素进行分析,选择了港口规模聚类的指标变量,并选择我国沿海五大港口群以及内河的20个港口进行聚类分析。根据港口规模的不同,将这20个港口分为国际强港、国际大港、区域性枢纽港、沿海区域性大港、内河区域性大港和地方性喂给港六个层次。同时,根据港口增长规律的不同,将这20个港口分为平稳增长型、加速增长型和波动增长型三大类;并对具有不同增长规律的港口,在使用时间序列法、回归分析法、灰色模型法、RBF神经网络模型法这四种预测模型进行吞吐量预测时的适用性进行比较分析,总结出具有不同增长规律的各类港口相对适用的预测方法。
Along with the development of the world economy and trade, modernization of port construction has been like a raging fire in China. There will be crucial strategic meanings to ascertaining port scale effectively and researching the methods to forecast port throughput and doing the prediction properly, in order to guide the programming and construction of the ports, to confirm the investment scale of the ports and moreover to accelerate the development of the areas. Traditional research on ascertaining port scale emphasize particularly on macroscopically programming and decision-making, which is affected by subjective factors; Traditional research on forecasting methods mainly focus on amelioration of methods themselves without choosing. This paper tries to use the method of demonstration research based on experiential data, analyzes a great deal of historical data, classifies ports of different scale into many levels through cluster analysis, studies the differences of increasing rules of the port's throughput ,and gets the conclusion of applicable forecasting methods of special port through the comparison and analysis.
This paper expounds the fundamental of cluster analysis, studies the factors of port scale ,chooses index variables for port scale cluster analysis and 20 ports in our country to study .These ports are classified into 6 levels through the dissimilarity of port scale ,including international strong port, international big port, regional hinge port, regional big seaport .regional big freshwater port and locality replenishment port. These ports are also classified into 3 levels through the differences of increasing rules, including normally increasing port, accelerated increasing port and fluctuated increasing port. Finally, the author applies the time series models, grey models, regression model and RBF neural network model to forecast the port throughput of the three type ports, and gets the conclusion of applicable forecasting methods for special port through the comparison and analysis.
本文阐述了聚类分析的基本原理,对港口规模的影响因素进行分析,选择了港口规模聚类的指标变量,并选择我国沿海五大港口群以及内河的20个港口进行聚类分析。根据港口规模的不同,将这20个港口分为国际强港、国际大港、区域性枢纽港、沿海区域性大港、内河区域性大港和地方性喂给港六个层次。同时,根据港口增长规律的不同,将这20个港口分为平稳增长型、加速增长型和波动增长型三大类;并对具有不同增长规律的港口,在使用时间序列法、回归分析法、灰色模型法、RBF神经网络模型法这四种预测模型进行吞吐量预测时的适用性进行比较分析,总结出具有不同增长规律的各类港口相对适用的预测方法。
Along with the development of the world economy and trade, modernization of port construction has been like a raging fire in China. There will be crucial strategic meanings to ascertaining port scale effectively and researching the methods to forecast port throughput and doing the prediction properly, in order to guide the programming and construction of the ports, to confirm the investment scale of the ports and moreover to accelerate the development of the areas. Traditional research on ascertaining port scale emphasize particularly on macroscopically programming and decision-making, which is affected by subjective factors; Traditional research on forecasting methods mainly focus on amelioration of methods themselves without choosing. This paper tries to use the method of demonstration research based on experiential data, analyzes a great deal of historical data, classifies ports of different scale into many levels through cluster analysis, studies the differences of increasing rules of the port's throughput ,and gets the conclusion of applicable forecasting methods of special port through the comparison and analysis.
This paper expounds the fundamental of cluster analysis, studies the factors of port scale ,chooses index variables for port scale cluster analysis and 20 ports in our country to study .These ports are classified into 6 levels through the dissimilarity of port scale ,including international strong port, international big port, regional hinge port, regional big seaport .regional big freshwater port and locality replenishment port. These ports are also classified into 3 levels through the differences of increasing rules, including normally increasing port, accelerated increasing port and fluctuated increasing port. Finally, the author applies the time series models, grey models, regression model and RBF neural network model to forecast the port throughput of the three type ports, and gets the conclusion of applicable forecasting methods for special port through the comparison and analysis.
引文
[1]梅长林,周家良.实用统计方法.北京:科学出版社,2002
[2]王学民.应用多元分析.上海:上海财经大学出版社,1999
[3]任若恩,王惠文.多元统计数据分析--理论、方法、实例.北京:国防工业出版社,1997
[4]冯文权,茅奇,周毓萍.经济预测与决策技术.武汉:武汉大学出版社,2002
[5]杨大鸣,王呈方,张培林.港口岸线评价模型及应用.水运工程,2003.4,
[6]苏瑛.聚类分析模型在房地产投资决策中的应用研究.硕士学位论文,2004
[7]罗贤缙.聚类分析在电力营销中的应用研究.硕士学位论文,2004
[8]刘伟.谈发展港口规模经济.港口经济,2004.2
[9]潘文军,王少梅.基于神经网络的聚类分析方法及在港口设备配置中的应用.交通与计算机.2003.5
[10]武骁,宗蓓华,郑士源.我国沿海集装箱港口层次布局问题研究.综合运输,2004.6
[11]高鸿丽.长江三角洲地区港口与区域经济关系及港口群合理定位的研究.硕士学位论文,2002
[12]胡明.港口网络体系规划方法研究.硕士学位论文,2004
[13]高洁.上海港集装箱运输竞争力研究.硕士学位论文,2004
[14]叶剑.基于聚类分析的港口集装箱吞吐量预测方法的研究.硕:上学位论文,2005
[15]甄毅.河南省各县市社会经济发展水平聚类分析.硕士学位论文,2005
[16]刘洋.面向电子商务的聚类分析算法的研究和实现.硕士学位论文,2003
[17]余建英,何旭宏.数据统计分析与SPSS应用.北京:人民邮电出版社,2003
[18]飞思科技产品研发中心.MATLAB6.5辅助神经网络分析与设计.北京:电子工业出版社,2003
[19]于汝民主编.港口规划与建设.北京:人民交通出版社,2003
[20]洪承礼.港口规划与布置.北京:人民交通出版社,1999
[21]王红,宋风杰.预测技术在港口吞吐量预测中的应用.物流技术,1995,(3):8-1
[22]李一智,徐选华.商务决策数量方法.北京::经济科学出版社,2003,11-17
[23]徐丽娜.神经网络控制.哈尔滨:哈尔滨工业大学出版社,1999,88-122
[24]苑希民,李鸿雁,刘树坤等.神经网络和遗传算法在水科学领域的应用.北京:中国水利水电出版社,2002,83-96
[25]苏金明,张莲花,刘波恩等.MATLAB工具箱应用.北京:电子工业出版社,2004
[26]董长虹.MATLAB神经网络与应用.北京:国防工业出版社,2005
[27]闻新,周露,李翔等.MATLAB神经网络仿真与应用.北京:科学出版社,2003
[28]王学武,谭得健,神经网络的应用与发展趋势.计算机工程与应用,2003,(3):98-100
[29]Hsu L C.Applying the Grey prediction model to the global integrated circuit industry.Technological Forecasting&Social Change,2003,(70):563-574
[30]Hsu C I,Wen Y U.Improved Grey prediction models for trans-Pacific air passenger market.Transp.Piano.Technol,1998,(22):87-107.
[31]Hsu C C,Chen C Y.Applications of improved grey prediction model for power demand forecasting.Energy Conversion and Management,2003,(44):2241-2249.
[32]Wang M H,Hung C P.Novel grey model for the prediction of trend of dissolved gases in oil-filled power apparatus.Electric Power Systems Research,2003,(67):53-58.
[33]Zhang Hong,Li Zhuguo,Chen Zhaoneng.Application of grey modeling method to fitting and forecasting wear trend of marine diesel engines.Tribology International,2003,(36):753-756
[34]邓聚龙.灰预测基础.武汉:华中科技大学出版社,2002,218-238
[35]邓聚龙.灰预测与灰决策.武汉:华中科技大学出版社,2002,99-105
[36]John T,Starr and Brian Slank.Ports as gateways:a traditional concept revisited.Fifth international conference of cities and ports.Dakar.Publish AIVP,1995
[37]Hoyle.B.S.and Charlier,J.J.Inter-port competition in developing countries:an East African cause study.Jounal of Transport Geography,1995
[38]胡国定,张润楚.多元统计分析方法--纯代数处理.天津:南开大学出版社
[39]中国人民大学统计系.数据挖掘中的聚类分析.统计与信息理论,2002
[40]霍保世,张秀媛.Fuzzy聚类分析原理在客流预测中的应用.数理经济技术经济研究,2001.12
[41]贾志永,洪方明.对应聚类分析在铁路建设投融资决策中的应用.西南民族学院学报,2000
[42]张国伍.交通运输系统分析.成都:西南交通大学出版社,1991.12
[2]王学民.应用多元分析.上海:上海财经大学出版社,1999
[3]任若恩,王惠文.多元统计数据分析--理论、方法、实例.北京:国防工业出版社,1997
[4]冯文权,茅奇,周毓萍.经济预测与决策技术.武汉:武汉大学出版社,2002
[5]杨大鸣,王呈方,张培林.港口岸线评价模型及应用.水运工程,2003.4,
[6]苏瑛.聚类分析模型在房地产投资决策中的应用研究.硕士学位论文,2004
[7]罗贤缙.聚类分析在电力营销中的应用研究.硕士学位论文,2004
[8]刘伟.谈发展港口规模经济.港口经济,2004.2
[9]潘文军,王少梅.基于神经网络的聚类分析方法及在港口设备配置中的应用.交通与计算机.2003.5
[10]武骁,宗蓓华,郑士源.我国沿海集装箱港口层次布局问题研究.综合运输,2004.6
[11]高鸿丽.长江三角洲地区港口与区域经济关系及港口群合理定位的研究.硕士学位论文,2002
[12]胡明.港口网络体系规划方法研究.硕士学位论文,2004
[13]高洁.上海港集装箱运输竞争力研究.硕士学位论文,2004
[14]叶剑.基于聚类分析的港口集装箱吞吐量预测方法的研究.硕:上学位论文,2005
[15]甄毅.河南省各县市社会经济发展水平聚类分析.硕士学位论文,2005
[16]刘洋.面向电子商务的聚类分析算法的研究和实现.硕士学位论文,2003
[17]余建英,何旭宏.数据统计分析与SPSS应用.北京:人民邮电出版社,2003
[18]飞思科技产品研发中心.MATLAB6.5辅助神经网络分析与设计.北京:电子工业出版社,2003
[19]于汝民主编.港口规划与建设.北京:人民交通出版社,2003
[20]洪承礼.港口规划与布置.北京:人民交通出版社,1999
[21]王红,宋风杰.预测技术在港口吞吐量预测中的应用.物流技术,1995,(3):8-1
[22]李一智,徐选华.商务决策数量方法.北京::经济科学出版社,2003,11-17
[23]徐丽娜.神经网络控制.哈尔滨:哈尔滨工业大学出版社,1999,88-122
[24]苑希民,李鸿雁,刘树坤等.神经网络和遗传算法在水科学领域的应用.北京:中国水利水电出版社,2002,83-96
[25]苏金明,张莲花,刘波恩等.MATLAB工具箱应用.北京:电子工业出版社,2004
[26]董长虹.MATLAB神经网络与应用.北京:国防工业出版社,2005
[27]闻新,周露,李翔等.MATLAB神经网络仿真与应用.北京:科学出版社,2003
[28]王学武,谭得健,神经网络的应用与发展趋势.计算机工程与应用,2003,(3):98-100
[29]Hsu L C.Applying the Grey prediction model to the global integrated circuit industry.Technological Forecasting&Social Change,2003,(70):563-574
[30]Hsu C I,Wen Y U.Improved Grey prediction models for trans-Pacific air passenger market.Transp.Piano.Technol,1998,(22):87-107.
[31]Hsu C C,Chen C Y.Applications of improved grey prediction model for power demand forecasting.Energy Conversion and Management,2003,(44):2241-2249.
[32]Wang M H,Hung C P.Novel grey model for the prediction of trend of dissolved gases in oil-filled power apparatus.Electric Power Systems Research,2003,(67):53-58.
[33]Zhang Hong,Li Zhuguo,Chen Zhaoneng.Application of grey modeling method to fitting and forecasting wear trend of marine diesel engines.Tribology International,2003,(36):753-756
[34]邓聚龙.灰预测基础.武汉:华中科技大学出版社,2002,218-238
[35]邓聚龙.灰预测与灰决策.武汉:华中科技大学出版社,2002,99-105
[36]John T,Starr and Brian Slank.Ports as gateways:a traditional concept revisited.Fifth international conference of cities and ports.Dakar.Publish AIVP,1995
[37]Hoyle.B.S.and Charlier,J.J.Inter-port competition in developing countries:an East African cause study.Jounal of Transport Geography,1995
[38]胡国定,张润楚.多元统计分析方法--纯代数处理.天津:南开大学出版社
[39]中国人民大学统计系.数据挖掘中的聚类分析.统计与信息理论,2002
[40]霍保世,张秀媛.Fuzzy聚类分析原理在客流预测中的应用.数理经济技术经济研究,2001.12
[41]贾志永,洪方明.对应聚类分析在铁路建设投融资决策中的应用.西南民族学院学报,2000
[42]张国伍.交通运输系统分析.成都:西南交通大学出版社,1991.12