基于SOA和支持向量机的企业财务风险预警系统设计与实现

发布时间：2018-03-14 04:51

本文选题：企业财务风险预警　切入点：支持向量机　出处：《吉林大学》2014年硕士论文　论文类型：学位论文

【摘要】：随着我国社会经济市场化和国际化程度越来越高，企业财务风险管理和预警的重要性愈加凸显。财务风险预警体系，研究企业或者政府等的财务状况，结合历史数据和累积的经验，对财务状况是否会有风险做出预警。企业财务风险预警涉及企业各方面海量的数据，不仅与企业内部因素有关，也且与行业因素和外部大环境有关。进行企业财务风险预警的研究，首先要搞清楚以下几个问题：第一，企业每天都产生了哪些数据，哪些数据对研究有用，哪些数据对研究没用；第二，在企业产生的海量数据中，哪些与财务有关，哪些是主要因素，哪些是次要因素；第三，通过分析，判断企业处于财务风险的哪个阶段，应该采取哪些措施，来尽量减少企业财务风险给企业造成的可能的损失。传统上，人们在进行财务风险预警的时候，使用的方法多种多样，但是，它们都要求较多的前提条件，这些限制条件往往影响了预测结果的准确性和预警的可靠性与普遍性。现在，支持向量机、神经网络等数据挖掘方法在预测方面被广泛应用，具有很高的可信度，，而且可以解决具有大量参数的难题。本文就采用支持向量机作为企业财务风险预警的方法，当然，本文建立的企业财务预警体系不仅可应用于企业，还可应用于政府等各种组织机构。针对传统财务风险预警领域的问题，本文提出了基于支持向量机的企业财务风险预警模型，并将基于支持向量机的企业财务风险预警模型和面向服务的体系架构结合起来，实现了企业财务风险预警服务与面向服务的体系架构的组合，使得财务风险预警的结果可以进行及时的发布。科学可靠有效的企业财务风险预警体系，通过长期的观测和分析，可以在前期就对可能出现的财务风险进行预报和警示，并将预警结果进行及时发布，使得企业可以及时采取措施，来减少企业损失。
[Abstract]:With the increasing degree of marketization and internationalization of social economy in our country, the importance of financial risk management and early warning of enterprises is becoming more and more prominent. The financial risk warning system studies the financial situation of enterprises or governments, etc. Combining with historical data and accumulated experience, we can make early warning on whether there will be risks in the financial situation. Enterprise financial risk early warning involves a large amount of data from all aspects of the enterprise, not only related to the internal factors of the enterprise. It is also related to the industry factors and the external environment. To carry out the research on early warning of enterprise financial risk, we should first find out the following questions: first, what data are generated by the enterprise every day and which data are useful for the research? Which data are useless for research; second, which of the vast amounts of data generated by enterprises are related to finance, which are major factors, and which are secondary factors; and third, through analysis, we can determine which stage of financial risk the enterprise is in. What measures should be taken to minimize the possible losses caused by financial risks. Traditionally, people have used a variety of methods for early warning of financial risks, but they all require more preconditions. These constraints often affect the accuracy of prediction results and the reliability and universality of early warning. Nowadays, support vector machines, neural networks and other data mining methods are widely used in prediction, and have high credibility. In this paper, support vector machine is adopted as the method of enterprise financial risk warning, of course, the enterprise financial early-warning system established in this paper can not only be applied to enterprises, It can also be applied to government and other organizations. Aiming at the problems in the traditional financial risk early warning field, this paper puts forward the enterprise financial risk early warning model based on support vector machine, and combines the enterprise financial risk warning model based on support vector machine with the service-oriented architecture. The combination of enterprise financial risk early warning service and service-oriented architecture is realized, and the results of financial risk warning can be released in time. The scientific, reliable and effective enterprise financial risk warning system, through long-term observation and analysis, The financial risk may be forecasted and warned in the early stage, and the early warning result can be issued in time, so that the enterprise can take measures in time to reduce the loss of the enterprise.
【学位授予单位】：吉林大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP393.09;TP181

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