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| 基于证据理论的覆盖决策信息系统的属性约简 | |
| 引用本文： | 张燕兰,李长清.基于证据理论的覆盖决策信息系统的属性约简[J].模式识别与人工智能,2018,31(9):797-808. |
| 作者姓名： | 张燕兰 李长清 |
| 作者单位： | 1.闽南师范大学 计算机学院 漳州 363000 2.闽南师范大学 数学与统计学院 漳州 363000 3.数据科学与智能应用福建省高等学校重点实验室 漳州 363000 4.闽南师范大学 福建省粒计算及其应用重点实验室 漳州 363000 |
| 基金项目： | 国家自然科学基金项目(No.11701258,11871259,11526109)、福建省自然科学基金项目(No.2016J01671,2016J01315, 2017J01771, 2017J01507)、福建省高校杰出青年科研人才培养计划项目资助 |
| 摘 要： | 覆盖决策信息系统的属性约简是粗糙集理论中的重要研究内容之一.文中讨论决策为覆盖的覆盖决策信息系统的属性约简,针对覆盖决策信息系统的一类约简,利用证据理论中的信任函数和似然函数给出约简的等价刻画.根据决策类的似然函数值定义覆盖的重要度和相对重要度,给出求解约简的算法,并以实例说明算法的有效性. |
| 关 键 词： | 覆盖决策信息系统 属性约简 证据理论 覆盖粗糙集 |
| 收稿时间： | 2017-11-21 |
Attribute Reduction of Covering Decision Information System Based on Evidence Theory |
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| ZHANG Yanlan,LI Changqing.Attribute Reduction of Covering Decision Information System Based on Evidence Theory[J].Pattern Recognition and Artificial Intelligence,2018,31(9):797-808. | |
| Authors: | ZHANG Yanlan LI Changqing |
| Affiliation: | 1.School of Computer Science and Engineering, Minnan Normal University, Zhangzhou 363000 2.School of Mathematics and Statistics, Minnan Normal University, Zhangzhou 363000 3.Key Laboratory of Data Science and Intelligence Application, Fujian Province University, Zhangzhou 363000 4.Key Laboratory of Granular Computing, Minnan Normal University, Zhangzhou 363000 |
| Abstract: | The attribute reduction of covering decision information systems is one of the most important problems of the rough set theory. In this paper, the decisions of covering decision information systems are characterized by coverings, and attribute reductions of the covering decision information systems are explored. The belief and plausibility functions from the evidence theory are employed to characterize attribute reductions in the covering decision information system. By plausibility function values of decision classes, the definitions of significance and relative significance of coverings are also developed. Then, an attribute reduction algorithm based on the evidence theory is proposed in the covering decision information system, and an example is adopted to illustrate the validity of the propose algorithm. |
| Keywords: | Covering Decision Information System Attribute Reduction Evidence Theory Covering Rough Set |
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