基于Apriori关联规则算法的服务供应链风险预测研究

发布时间：2018-05-01 19:23

本文选题：数据挖掘 + 关联规则　；参考：《广西民族大学》2017年硕士论文

【摘要】：随着大数据时代的来临,经济全球化进程日益加速,企业之间的竞争不断加大,供应链之间的竞争也在不断加剧。服务供应链是信息环境下以服务集成商为主导的提供专业化功能服务的新型供应链。在服务全球化背景下,服务供应链之间的市场竞争也日趋加剧,风险预测及管理工作对其极其重要。利用大数据信息及数据挖掘技术做风险分析与管理已经成为服务供应链在当今日益激烈的市场竞争中保持核心竞争力的重要手段。但是,由于服务供应链整体的复杂性和不确定性,使得服务供应链在面对风险时更加被动、脆弱,因此风险研究也变得越发重要。相对于发达国家而言,我国对于服务供应链以及供应链风险的研究尚处于起步阶段,这使我国的企业在全球化进程中处于不利的位置,因此要发展壮大我国企业,须加大对服务供应链及其风险方面的研究。基于这样的背景,本文通过应用数据挖掘中的关联规则算法对服务供应链风险进行预测研究,并提出相关的对策建议,望对我国服务供应链风险及其相关研究增砖添瓦,对我国企业的全球化发展进程有所促进。本文首先对现有的服务供应链风险和数据挖掘的研究基础进行了论述,然后总结分析出服务供应链风险的六大类型,包括信息风险、协同风险、管理风险、需求风险、信用风险、环境风险,然后对风险的成因进行分析,得出每种风险的诱发事件,并总结出风险类型和风险事件之间的关联性。通过模拟实验的方法得出服务供应链风险事件发生的数据,使用关联规则中的Apriori算法来对实验数据进行分析,得出风险事件之间的关联性,即潜在风险事件,然后将风险事件以及潜在风险事件通过代入模型中求出当风险事件发生时对各种类型服务供应链风险的影响程度,最终得出企业在不同情况下应该注意管理的重点所在,有效降低服务供应链风险发生时的损失情况,维护服务供应链的整体稳定性。
[Abstract]:With the advent of big data era, the process of economic globalization is accelerating day by day, the competition between enterprises is increasing, and the competition between supply chains is also intensifying. Service supply chain (SSC) is a new type of supply chain in which service integrator is the leading service provider in information environment. Under the background of service globalization, the market competition between service supply chain is becoming more and more serious, and risk prediction and management are very important to it. Using big data information and data mining technology to do risk analysis and management has become an important means to maintain the core competitiveness of service supply chain in the increasingly fierce market competition. However, because of the complexity and uncertainty of the whole service supply chain, the service supply chain is more passive and fragile in the face of risks, so the risk research becomes more and more important. Compared with developed countries, the research on service supply chain and supply chain risk in China is still in the initial stage, which makes our enterprises in a disadvantageous position in the process of globalization, so we should develop and strengthen our enterprises. Research on service supply chain and its risk should be increased. Based on this background, this paper uses the association rules algorithm in data mining to predict the risk of service supply chain, and puts forward relevant countermeasures and suggestions, hoping to increase the risk of service supply chain and its related research in China. To our country enterprise globalization development process has promoted. This paper firstly discusses the research foundation of service supply chain risk and data mining, then summarizes and analyzes six types of service supply chain risk, including information risk, collaborative risk, management risk, demand risk. Credit risk, environmental risk, and then analyze the causes of risk, get the induced events of each kind of risk, and summarize the relationship between risk types and risk events. The data of risk events in service supply chain are obtained by simulation experiment. The Apriori algorithm in association rules is used to analyze the experimental data, and the correlation between risk events, that is, potential risk events, is obtained. Then the risk event and the potential risk event are put into the model to find out the degree of influence on the risk of various types of service supply chain when the risk event occurs. Finally, the enterprise should pay attention to the key point of management under different circumstances. Effectively reduce the loss of service supply chain risk, maintain the overall stability of service supply chain.
【学位授予单位】：广西民族大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP311.13;F274

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