基于灰色系统理论的财务数据挖掘研究和应用

【作者】 王庆；

【导师】 刘震宇；

【作者基本信息】 厦门大学 ， 系统工程， 2001， 硕士

【摘要】 数据挖掘是目前发展极为迅速的一个研究领域，它综合了数学、统计学、数据库、模式识别、人工智能、最优化等多门学科，随着社会的发展，人们对数据的使用不再仅仅满足于普通的数据处理，而是希望能通过某种方法去挖掘深层次的、隐含的、有价值的东西，数据挖掘便是在这种条件下应运而生，并发展壮大起来的。 本文所研究的中心是在灰色系统理论的基础上建立数据挖掘方法，结合财务分析知识，对已有的上市公司财务数据进行挖掘。在文中我们给出实例，并结合这些方法得出有关结论，并在计算机上予以实现。 第—章：对数据挖掘进行综述，介绍数据挖掘的基本概念，介绍数据挖掘近期发展的研究方法和方向。 第二章：介绍财务报表分析的基本概念和几种方法，详细介绍在财务比率分析中财务比率的计算及含义，为今后的挖掘做准备，考虑到数据挖掘的优点，还讨论了能够在财务数据中应用挖掘的几种方法。 第三章：作为本文所讨论的重点，在给出灰色系统理论的有关概念后，结合财务比率知识，提出增长率挖掘和发展态势挖掘，评价上市公司的增长和发展状况，并讨论在财务数据中使用灰关联和灰聚类挖掘，得出财务比率间的关联和聚类状况。 第四章：在这章里主要介绍软件实现方面的情况。 第五章：总结全文，对数据挖掘进行展望。更多还原

【Abstract】 Data mining is one of the research fields that are developing fast recently. It includes many subjects such as mathematics, statistics, databases, pattern recognition, artificial intelligence, optimization etc. With the development of the society, people are not satisfied with the ordinary processing about data and hope to get something deep, undiscovered and valuable information from data by some way. So, data mining emerges as the times require and develops gradually.The focus of this thesis is to put forward the methods based on gray system theory for data mining and to mine the financial data of the companies in the Chinese stock market along with the knowledge of financial analysis. We give some examples and obtain some results from them by using the methods. And the methods are performed in computer.Chapter 1: here we give an overall statement of data mining, including introduction of the basic concept, the methods and research branches up to the present etc.Chapter 2: before explaining the mining methods, we introduce the basic concept and methods for financial statement analysis, explicate the formulae and the meanings of financial ratios which are mentioned in the financial ratio analysis. Allowing for the advantages of data mining, we also discuss some other methods that can be applied to mine financial data.Chapter 3: after giving some related concept of gray system theory, we put forward the methods of the Growth Rate Mining and the Development Situation Mining to evaluate the companies’ growth and development in some aspects. Then we carry out the gray association and the gray clustering on financial data to get knowledge about the association relations between financial variables and the clustering results among them.Chapter 4: The chapter mainly introduces how the mining system is implemented in software.Chapter 5: a conclusion about this thesis is made and the future expectation of data mining is discussed.更多还原