Dissertation > Industrial Technology > Automation technology,computer technology > Automated basic theory > Artificial intelligence theory > Expert systems, knowledge engineering

Research on Knowledge Roughness Based on Rough Sets

Author LiHong
Tutor HuXueGang
School Hefei University of Technology
Course Applied Computer Technology
Keywords Rough Sets Theory Knowledge Roughness Knowledge Rough Entropy Mutual Rough Information Knowledge Granularity
Type Master's thesis
Year 2006
Downloads 136
Quotes 4
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The present thesis attempts to investigate knowledge roughness research based on Rough Set Theory.In knowledge processing, knowledge by definition is one or more information connections (relations or relation). Knowledge is to summarize and abstract human experience, characterized with abstraction and universality. While human understanding an object, the object is generalized and abstracted, namely the information is granularized. Although individual details of information lost, the granularized information is more significant, easier to understand. During understanding and explanation of the granularized information, a certain of inaccuracy which will be produced is called the knowledge roughness. Research of knowledge roughness is important in theory, and methodology, moreover, valuable in application.Rough Set Theory, introduced by Professor Pawlak in the early 1980’s, is a mathematical tool to deal with vagueness and uncertainty. Its basic idea goes as follows: Based on viewpoint of classification, classification capability is maintained invariably in the research of approximate space (Knowledge Base). Through knowledge reduction, the concept of the classification rule is derived and applied to the unknown data to decide how to make decisions. Without the need to provide the transcendental information beyond the data, Rough Set Theory serves to discover the latent and useful rule, ie.. the knowledge, and its internal connection relations and features in data, In recent years, great success has been obtained concerning knowledge roughness research and the application based on Rough Set and it has become the important branch of soft computing method. It covers pattern recognition, machine learning, decision analysis and policy-making support, knowledge acquisition, knowledge discovery and so on. So, Rough Set Theory has provided the frame for knowledge roughness research.This thesis based on Rough Set Theory elaborates background, the significance and the present situation of knowledge roughness research summarizes the basic thoughts of Rough Set Theory. Through analyzing its origin, nature and the essence of knowledge roughness based on Rough Set Theory, the thesis discusses the knowledge roughness measurement, the structure, the expression and application, showing its certain impetus to the human cognition and problem solution. The thesis has obtained the achievements as follows: (1) based on elaboration of concepts suchas knowledge rough entropy, knowledge granularity, the concept of mutual rough information of knowledge roughness is proposed for the first time;(2) two kinds of expression of knowledge roughness based on the rough set theory are offered, which one rough entropy expression and granularity expression;(3) some relations among the knowledge roughness with the rough entropy and granularity are discussed and established monotonous relations is between the knowledge roughness, between the rough entropy and granularity;(4) based on two kinds of expression, the basic process of attribute reduction in knowledge expression system respectively, the knowledge reduction algorithm is designed respectively, through the example analysis, it indicates that these two algorithms were effective.

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