【作者】 马玉良；

【导师】 赵光宙；

【作者基本信息】 浙江大学 ， 控制理论与控制工程， 2005， 博士

【摘要】 Pawlak提出的粗糙集(Rough Sets,简称RS)理论是处理知识,特别是不精确、不相容知识的一种新的数学工具。该理论对知识给出了形式化的定义,使得对知识能够进行有效的分析和操作。此外,RS理论还提供了一套从数据中自动获取知识的工具,即知识约简。目前,RS理论正在被广泛应用于人工智能、模式识别等很多领域。 基于粗糙集理论的特点,将其应用于知识获取领域,可支持知识获取的多个步骤,如数据预处理、数据约简、规则生成、数据依赖关系获取等。全文主要内容如下: 第一章主要是粗糙集理论综述,包括以下四部分:粗糙集理论的基本概念;粗糙集理论区别于其它智能理论的特点;粗糙集理论比较常用的应用软件;粗糙集理论的研究方向,包括理论研究和应用研究。然后对知识获取进行了概述,最后介绍了论文研究的内容和论文结构。 第二章在引入知识信息熵及互信息概念的基础上,详细讨论了粗糙集理论中知识粗糙性与信息之间的关系,从信息的角度对知识粗糙性给出了定量的刻划。然后从信息的角度对粗糙集理论的主要概念给出了新的表示,我们称之为信息表示,并且对其直观含义和合理性进行了说明。 第三章提出了基于粗糙集理论的信息系统属性重要性评价方法。利用粗糙集理论中的下近似和上近似概念定义一个评定参数α_R(X),并由此参数的大小判断系统属性的重要性。与现有的评价系统参数方法相比,基于粗糙集理论的方法能得到关于系统更多的信息。 第四章首先介绍了信息系统属性离散化的意义、步骤、分类和几种现有的方法。然后利用决策表相容性的反馈信息,提出了一种领域独立的连续属性划分的算法。最后将该算法与目前已有的几种方法做了比较分析,得到了令人满意的结果。 第五章研究了信息系统的约简算法。首先研究了用粗糙集理论对实值信息系统属性进行约简的方法,通过对离散化方法与属性约简的关系进行研究,提出了实值属性离散化的一种自动确定属性类别的方法,并结合粗糙集理论给出了对实值属性信息系统约简的算法;然后结合概率方法对模糊集进行了研究,并利用相更多还原

【Abstract】 Rough Sets (RS) theory, introduced by Pawlak Z., is a new mathematical tool to deal with knowledge, particularly when knowledge is imprecise or inconsistent. The RS theory gives a formal definition of knowledge so that the knowledge can be analyzed and manipulated effectively. This theory also provides a suit of tools, i.e. reduction of knowledge, to acquire knowledge from data automatically. Recently, the RS theory is widely being used in many areas, such as artificial intelligence, pattern recognition etc.Based on the characters of RS theory, it can be used in knowledge acquisition to support such steps as data pretreatment, data reduction, rule generation and acquisition of data dependencies. The details were studied as follows:In chapter one: The summarization of RS theory was introduced firstly, which included four parts: basic concepts of RS theory, characters of RS theory, application software commonly used in RS theory and research fields of RS theory including theoretical and applied fields. Then, knowledge acquisition based on RS theory was briefly introduced. At last, the content and structure of the dissertation were brought forth.In chapter two: The relationship between information and roughness of knowledge in RS theory was discussed in detail based on the concepts of information entropy and mutual information of knowledge. The roughness of knowledge was quantificationally described with information. Then, the new expression of main concepts in RS theory was given based on information, which was called information expression. Also, the intuitionistic signification and rationality of this expression were explained.In chapter three: A method for evaluating the significance of information system attributes based on RS theory was proposed. A parameter a R(X) defined by the concepts of lower and upper approximation in RS theory was used to estimate the significance of system attributes. More information about the studied system can be found by this method compared with others.In chapter four: The meaning, steps, classification and several existing methods of discretization of attribute in information system were introduced firstly. Then, An area-independent automatic approach for discretization of continuous attribute based on dynamic cluster algorithm is presented. The comparisons between this approach and other exiting methods were made, and the results were satisfying.In chapter five: The reduction algorithms of information system were studied. By studying discretization methods and attributes reduction based on RS theory, a method for rules reduction to real value information system was proposed. By researching fuzzy sets with probability method, a approach for rules reduction to fuzzy value information system was brought forth based on RS theory. Combining concept of support in association rules and RS theory, RSVR algorithm was presented. Finally, the above approaches were tested with several databases.In chapter six: The actualities, research fields and problems of information fusion were generally stated and the approach to multisensor fusion with RS theory was discussed. It can improve the fusion speed and decision ability of the system.In chapter seven: All of the work in this dissertation was summed up, and the future researches in this area were prospected.更多还原