|本期目录/Table of Contents|

[1]宋宪捷,周建军,鹿士凯,等.基于客流量的贝叶斯回归服装销售预测方法[J].丝绸,2018,55(4):041108.[doi:10.3969/j.issn.1001-7003.2018.04.008]
 SONG Xianjie,ZHOU Jianjun,LU Shikai,et al.Clothing sales forecast based on passenger flow and Bayesian regression model[J].Journal of Silk,2018,55(4):041108.[doi:10.3969/j.issn.1001-7003.2018.04.008]
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基于客流量的贝叶斯回归服装销售预测方法(PDF)
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《丝绸》[ISSN:1001-7003/CN:33-1122/TS]

卷:
55
期数:
2018年4期
页码:
041108
栏目:
研究与技术
出版日期:
2018-04-20

文章信息/Info

Title:
Clothing sales forecast based on passenger flow and Bayesian regression model
文章编号:
1001-7003(2018)04-0044-05
作者:
宋宪捷周建军鹿士凯刘凤坤
1.天津工业大学 a. 纺织学院;b.艺术与服装学院,天津 300387 ;2.河南理工大学 计算机科学与技术学院,河南 焦作 454000 ;3.中国纺织信息中心,北京 100025
Author(s):
SONG Xianjie ZHOU Jianjun LU Shikai LIU Fengkun
 1a. College of Textile;1b. College of Fashion, Tianjin Polytechnic University, Tianjin 300387, China; 2.College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, 454000, China; 3.China Textile Information Center, Beijing 100025, China
关键词:
服装销售预测时间序列贝叶斯回归客流量
Keywords:
clothing sales forecast time series Bayesian regression passenger flow
分类号:
TS941.1
doi:
10.3969/j.issn.1001-7003.2018.04.008
文献标志码:
A
摘要:
科学、准确的地预测服装销售量,对服装企业研发、生产、配送、销售等流程起到至关重要的作用。为此,文章采用贝叶斯一元回归方法,借助贝叶斯极大似然估计的优势,并结合时间序列移动平均法构建了服装销售量预测模型。该模型首先引入客流量的概念,以此作为服装销售预测的中间转化量,采用时间序列的移动平均法构建季节因子,屏蔽季节影响因素,用以预测客流量;然后依据客流量预测值通过贝叶斯一元回归方法预测服装销售量;最后利用案例验证了贝叶斯回归服装销售量预测的有效性和准确性。
Abstract:
Scientific and accurate prediction of clothing sales is of vital importance to the development, production, distribution and sales of clothing enterprises. Therefore, clothing sales forecast model was constructed by applying Bayesian monadic regression method, taking advantage of the Bayesian maximum likelihood estimation and combining moving average method of time series. The model first introduced the concept of passenger flow as the middle transformation quantity of clothing sales forecast. Besides, the moving average method of time series was used to construct seasonal factors, shield seasonal influencing factors and predict passenger flow. Then, the clothing sales volume was predicted by Bayesian monadic regression method according to the predicted value of passenger flow. Finally, the validity and accuracy of Bayesian regression model were verified by cases

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备注/Memo

备注/Memo:
收稿日期:2017-09-09
修回日期:2018-00-00
作者简介:宋宪捷(1991—),女,硕士研究生,研究方向为服装工程
通信作者:周建军,副教授,fz02zhou@163.com
更新日期/Last Update: 2018-03-22