全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

基于C#与MATLAB混合编程的物流需求预测系统的实现物流需求预测系统的实现

DOI: 10.3969/j.issn.1674-0696.2015.04.25, PP. 128-132

Keywords: 管理工程,混合编程,物流需求预测系统,managementengineering,hybridprogramming,logisticsdemandforecastingsystem

Full-Text   Cite this paper   Add to My Lib

Abstract:

:?根据物流需求数据的不同特点,归纳了灰色GM(1,1)模型、移动平均值模型、指数平滑模型、季节指数模型、BP神经网络模型、线性回归模型、多项式拟合模型和非线性回归模型8种常见的物流需求预测模型,并据此为物流企业开发了基于C#与MATLAB混合编程的物流需求预测系统,降低了物流企业物流需求预测的复杂度。最后通过预测实例表明该系统具有较好的适用性和较高的预测精度。

References

[1]  [1] Rodrigo A G,Hani S M.Forecasting freight transportation demand with the space-time multinomial probity model [J].Transportation Research:Part B,2000(34):403-418.
[2]  Ouyang Xiaoxun,Dai Yuqing.Non-linear model analysis of social logistics needs [J].Commercial Times,2009(20):23-24.
[3]  [12]耿立艳,丁璐璐.基于灰关联分析的最小二乘支持向量机物流需求预测[J].物流技术,2013,32(10):130-132.
[4]  Geng Liyan,Ding Lulu.Forecasting of logistics demand based on grey correlation analysis and least square SVM [J].Logistics Technology,2013,32(10):130-132.
[5]  [13]黄海宽,张云锋,魏东,等.基于COM的MATLAB在中药分析中的应用[J].自动化与仪表,2006(4):5-7.
[6]  Huang Haikuan,Zhang Yunfeng,Wei Dong,et al.Application of MATLAB based on COM in Chinese medicine [J].Automation & Instrumentation,2006(4):5-7.
[7]  [14]黄一丹,严洪森,冯丽娟,等.基于C#.NET与Matlab接口和BP网络的汽车产量预测[J].计算机技术与发展,2008,18(11):36-40.
[8]  Huang Yidan,Yan Hongsen,Feng Lijuan,et al.Vehicle production forecasting based on BPNN and interface between C#.NET and Matlab [J].Computer Technology and Development,2008,18(11):36-40.
[9]  [2] 马凯,艾力·斯木吐拉.交通规划四阶段法在物流需求预测中的应用[J].重庆交通大学学报:自然科学版,2009,28(4):745-750.
[10]  Ma Kai,Eili Ismutull.Application of four-step method of traffic planning to logistics demand forecast [J].Journal of Chongqing Jiaotong University:Natural Science,2009,28(4):745-750.
[11]  [3] 周晓娟,景志英.基于多元线性回归模型的河北省物流需求预测实证分析[J].物流技术,2013,32(5):270-272.
[12]  Zhou Xiaojuan,Jing Zhiying.Empirical analysis of logistics demand forecasting of Hebei based on multi-linear regression model [J].Logistics Technology,2013,32(5):270-272.
[13]  [4] 闫娟,李萍.泊松分布灰色理论在物流需求预测中的应用[J].计算机仿真,2012,29(4):229-233.
[14]  Yan Juan,Li Ping.Application research of poisson distribution grey theory in logistics demand forecasting [J].Computer Simulation,2012,29(4):229-233.
[15]  [5] 后锐,张毕西.基于MLP神经网络的区域物流需求预测方法及其应用[J].系统工程理论与实践,2005(12):43-47.
[16]  Hou Rui,Zhang Bixi.A method for forecasting regional logistics demand based on MLP neural network and its application [J].Systems Engineering-theory & Practice,2005(12):43-47.
[17]  [6] 杨蕾,张苗苗.时间序列模型在物流需求预测中的应用[J].商业时代,2013(13):26-27.
[18]  Yang Lei,Zhang Miaomiao.The application of time series model in logistics demand forecasting [J].Commercial Times,2013(13):26-27.
[19]  [7] 司玲玲,王亚楠,徐贵军.改进灰色模型在物流需求预测中的应用[J].计算机仿真,2012,29(6):192-194.
[20]  Si Lingling,Wang Ya’nan,Xu Guijun.Logistics demand forecasting based on improved grey model [J].Computer Simulation,2012,29(6):192-194.
[21]  [8] 施泽军,李凯.基于灰色模型和指数平滑法的集装箱吞吐量预测[J].重庆交通大学学报:自然科学版,2008,27(2):302-204.
[22]  Shi Zejun,Li Kai.Container throughput forecasting based on gray method and exponential smoothing method [J].Journal of Chongqing Jiaotong University:Natural Science,2008,27(2):302-204.
[23]  [9] 刘智琦,李春贵,陈波.基于因子分析与神经网络的区域物流需求预测[J].计算机仿真,2012,29(6):359-362.
[24]  Liu Zhiqi,Li Chungui,Chen Bo.Regional logistics demand forecast based on factor analysis and neural network [J].Computer Simulation,2012,29(6):359-362.
[25]  [10]李自立,黄芬.基于主成分分析的区域物流需求预测指标研究[J].物流技术,2009,28(12):128-130.
[26]  Li Zili,Huang Fen.Research on the forecasting indices of regional logistics demand based on PCA [J].Logistics Technology,2009,28(12):128-130.
[27]  [11]欧阳小迅,戴育琴.社会物流需求的非线性模型分析[J].商业时代,2009(20):23-24.
[28]  [15]谭伟,陆百川,黄美灵.神经网络结合遗传算法用于航迹预测[J].重庆交通大学学报:自然科学版,2010,29(1):147-150.
[29]  Tan Wei,Lu Baichuan,Huang Meiling.Track prediction based on neural networks and genetic algorithm [J].Journal of Chongqing Jiaotong University:Natural Science,2010,29(1):147-150.
[30]  [16]中国物流与采购联合会.中国物流年鉴[M].北京:中国财富出版社,2013.
[31]  China Federation of Logistics & Purchasing.China Logistics Yearbook [M].Beijing:China Fortune Press,2013.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133