以消费者需求为导向的烟草零售客户“去库存”研究——基于神经网络修正灰色残差的建模方法
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- 英文论文题名：The research of tobacco retail clients to inventory by Consumer demand oriented----- Based on method of neural network correction grey residual modeling
- 论文作者：冯明亮
- 英文论文作者：Feng Mingliang
- 年：2016
- 作者机构：含山县烟草专卖局(营销部);
- 论文关键词：消费者需求 ; 去库存 ; BP神经网络 ; 灰色残差序列
- 会议召开时间：2016-12-01
- 会议录名称：中国烟草学会2016年度优秀论文汇编——烟草经济与管理主题
- 语种：中文
- 分类号：F721;F274;TP183
- 学会代码：ZGYG
- 学会名称：中国烟草学会
- 页数：12
- 文件大小：1154k
- 原文格式：D
摘要
通过系统的收集零售客户的库存现状,分析了库存积压的原因,并从提高零售客户对卷烟品牌(规格)的需求预测准确度出发,构建以消费者需求为导向的组合预测模型,在此基础上选取了安徽市场的零售客户进行了实证分析,通过分析发现模型具有较高的预测准确性,这有助于帮助卷烟市场去库存。
Through the system of collecting retail customer inventory status, analyses the reasons of the inventory is too large, and from improving retail customer demand forecast accuracy of the cigarette brand(specification), the consumer demand oriented combination forecast model was constructed, on the basis of selecting the Anhui retail customer has carried on the empirical analysis of the market, through the analysis found that the model has higher prediction accuracy, and it will help the cigarette market to inventory.
Through the system of collecting retail customer inventory status, analyses the reasons of the inventory is too large, and from improving retail customer demand forecast accuracy of the cigarette brand(specification), the consumer demand oriented combination forecast model was constructed, on the basis of selecting the Anhui retail customer has carried on the empirical analysis of the market, through the analysis found that the model has higher prediction accuracy, and it will help the cigarette market to inventory.
引文
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[2]Gavin Shaddick,Time Series Analysis,2002,13-27.
[3]Dilli R Aryal,WANG Yao-wu.Time-series analysis with a hybrid Box-Jenkins ARIMA and neural network model.2004:26-78
[4]李世杰,王峰.市场调查与预测.武汉:武汉理工大学出版社,2005.
[5]周明,孙树栋.遗传算法原理及应用.北京:国防工业出版社,1999,78-89
[6]Chen Mutian,Cai Hexi.The geometric region-divided method for solving the China TSP problem.Computer Engineering and Science,1998,20(1):22-27
[7]Bob Nau,Carol Bray.Spreadsheet implementation of seasonal adjustment and exponential smoothing,2005:term 4
[8]林海,孙吉贵.预测及其主要模型的实现系统.吉林大学学报(信息科学版),2002:58~63
[9]章敬东,刘小辉,邓飞其等.灰色神经网络组合算法在复杂非线性预测中的应用[J].计算机工程与应用,2003,39(12):56-58.
[10]邓聚龙.灰色系统理论教程[M].武汉:华中理工大学出版社,1990.
[11]孙才志,潘俊.修正的灰色预测模型在水文时间序列分析中的应用[J].工程勘察,2000,(3):23-26.
[12]Funahashi K.On the Approximate Realization of Continuous Mapping by neural Networks[J].Neural Networks,1989,2(3):183-192.
[13]Cristiano Cervellera,Aihong Wen,Victoria C.P.Chen.Neural network and regression spline value function approximations for stochastic dynamic programming[J].Computer&Operations Research,2007,34(1):70-90.
[14]刘思峰,党耀国,方志耕.灰色系统理论及其应用[M].北京:科学出版社,2004.
[15]飞思科技产品研发中心.神经网络理论与MATLAB7实现[M].北京:电子工业出版社,2006.
[16]Junfeng Li,Aiping Yang,Wenzhan Dai.Modeling Mechanism of Grey Neural Network and Its Application[C].Proceedings of 2007 IEEE International Conference on Grey Systems and Intelligent Services,Nanjin,2007:404-408.
[17]Qiu-Ping WANG,Jian-Bo YAN.The Application of Grey GM(1,1)Forecasting Model with Neural Network Residual Modification to Oil Consumption[J].Sloan Management Review,2006,V01.38 No.1,p2l-30.