| 摘要: |
| 模糊目标信息系统(fuzzy objective information systems,简称FOISS)在许多实际应用中存在,这种系统上的知识简化不能采用Pawlak信息系统上的约简方法.因此,提出了模糊目标信息系统上的口分布约简、α最大分布约简、α分配约简、粗糙分布约简,并给出了它们的性质以及与Pawlak信息系统上约简的关系,同时也给出了这些约简的判定定理、对应的可辨识矩阵、约简公式.这些约简推广了Pawlak信息系统上的知识约简方法,为模糊目标信息系统上的知识发现和基于粗糙模糊规则的模糊概念分类器提供了新的低复杂性手段. |
| 关键词: 粗糙集 模糊目标信息系统 知识约简 分布约简 分配约简 |
| DOI： |
| 分类号: |
| 基金项目:Supported by the National High-Tech Research and Development Plan of China under Grant No.2003AA1Z2610(国家高技术研究发展计划(863)) |
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| Knowledge Reduction Methods in Fuzzy Objective Information Systems |
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GUAN Tao,FENG Bo-Qin
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| Abstract: |
| Fuzzy objective information systems (FOISs) exist in many applications, and knowledge reduction in them can抰 be implemented by reduction methods in Pawlak information systems. This paper firstly presents new reduction methods including a distribution, a maximum distribution, a assignment, and rough distribution reductions. It then probes into their properties and the relation between them and the reduction methods on Pawlak information systems. Furthermore, this paper proposes the judgement theorems and discernibility matrixes with respect to these reductions. These reductions extend the corresponding methods in Pawlak information systems and provide a new and low computation complexity way for knowledge discovery and rough-fuzzy rule based fuzzy concept classifiers in fuzzy objective information systems. |
| Key words: rough set fuzzy objective information system knowledge reduction distribution reduction assignment reduction |
