面向供应链风险评估的改进BP小波神经网络研究

计算机科学 ›› 2022, Vol. 49 ›› Issue (6A): 654-660.doi: 10.11896/jsjkx.210800049

面向供应链风险评估的改进BP小波神经网络研究

徐佳楠¹, 张天瑞¹, 赵伟博², 贾泽轩¹

1 沈阳大学机械工程学院沈阳 110044
2 沈阳大学国际学院沈阳 110044

出版日期:2022-06-10 发布日期:2022-06-08
通讯作者: 张天瑞(trzhang@syu.edu.cn)
作者简介:(mikexu1226@163.com)
基金资助:
中央引导地方科技发展资金计划(2021JH6/10500149);辽宁省自然科学基金(20180551001)

Study on Improved BP Wavelet Neural Network for Supply Chain Risk Assessment

XU Jia-nan¹, ZHANG Tian-rui¹, ZHAO Wei-bo², JIA Ze-xuan¹

1 School of Mechanical Engineering,Shenyang University,Shenyang 110044,China
2 School of International Studies,Shenyang University,Shenyang 110044,China

Online:2022-06-10 Published:2022-06-08
About author:XU Jia-nan,born in 1997,postgraduate.His main research interests include supply chain management and so on.
ZHANG Tian-rui,born in 1985,Ph.D,associate professor,postgraduate supervisor.His main research interests include intelligent manufacturing and production and operation management.
Supported by:
Science and Technology Development Fund Projects of Central Guided Region(2021JH6/10500149) and Natural Science Foundation of Liaoning Province,China(20180551001).

摘要/Abstract

摘要： 针对供应链风险在制造行业上下游企业之间产生的影响,首先以供应链运作参考(Supply Chain Operation Reference,SCOR)模型为基础,以汽车制造企业为研究背景,通过对汽车供应链风险进行分析并结合现场调研结果,研究了供应链风险指标识别过程,建立了涉及战略计划风险等五大风险类别的评价指标体系。其次,鉴于BP神经网络模型在优化评估过程中容易出现局部最优解等问题,通过增加动量对其改进优化,同时用Morlet小波函数替换基础评价模型中的S型函数,重构供应链风险评价模型。最后,通过汽车企业实际案例进行风险识别与评估研究,采用Matlab进行仿真,对比分析改进BP小波神经网络与模糊综合评价、BP神经网络、增加动量的BP神经网络,结果表明,改进的BP小波神经网络模型具有良好的实用性和可靠性。

关键词: BP神经网络, SCOR, 风险识别, 供应链, 小波理论

Abstract: In view of the impact of supply chain risks on upstream and downstream enterprises in the manufacturing industry,it is important to research the method of identification and evaluation for the supply chain risks.Firstly,based on supply chain operation reference model(SCOR) and taking automobile manufacturing enterprises as the research background,the identification process of supply chain risk indicators is studied by analyzing automobile supply chain risks and combining with the field survey results.An evaluation index system involving five risk categories,including strategic planning risk,procu-rement risk,manufacturing risk,distribution risk and return risk,is established.Secondly,considering that BP neural network model is prone to local optimal solution and other problems in the process of optimization evaluation,it is improved and optimized by increasing momentum,and the S-type function in the basic evaluation model is replaced by Morlet wavelet function to reconstruct the supply chain risk evaluation model.Finally,risk identification and assessment are studied with automobile enterprise of actual case,using the Matlab simulation to compare and analyze the improved BP wavelet neural network and fuzzy comprehensive evaluation,BP neural network,increased momentum of BP neural network.The results show that the improved BP wavelet neural network model has the better practicability and reliability.

Key words: BP neural network, Risk identification, Supply chain, Supply chain operation reference, Wavelet theory

中图分类号:

TP391.9

徐佳楠, 张天瑞, 赵伟博, 贾泽轩. 面向供应链风险评估的改进BP小波神经网络研究[J]. 计算机科学, 2022, 49(6A): 654-660. https://doi.org/10.11896/jsjkx.210800049

XU Jia-nan, ZHANG Tian-rui, ZHAO Wei-bo, JIA Ze-xuan. Study on Improved BP Wavelet Neural Network for Supply Chain Risk Assessment[J]. Computer Science, 2022, 49(6A): 654-660. https://doi.org/10.11896/jsjkx.210800049

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