项目名称: 多源直觉模糊数据集知识发现的粒计算方法研究
项目编号: No.61472463
项目类型: 面上项目
立项/批准年度: 2015
项目学科: 其他
项目作者: 徐伟华
作者单位: 重庆理工大学
项目金额: 60万元
中文摘要: 作为知识获取和数据挖掘的重要工具,粒计算是解决大规模复杂问题时模拟人类思考问题自然模式的一个新的理论、技术和方法,其基本思想是在问题求解过程中使用信息粒,从不同角度、不同层次上对现实问题进行描述、推理与求解。本课题以多源直觉模糊数据集为研究对象,以粗糙集、概念格、证据理论等为工具,研究多源直觉模糊信息系统和形式背景中信息融合与知识获取的粒计算理论与方法。主要研究内容包括:(1)发展多源直觉模糊数据集信息粒度的结构表示与融合方法;(2)建立带决策多源直觉模糊数据集信息融合的规则提取与决策分析方法;(3)研究基于证据理论的多源直觉模糊数据集的信息融合及知识获取的粒计算方法;(4)分析多源直觉模糊数据集信息融合前后的不确定性问题。本项目研究成果不但能够丰富粒计算和信息融合理论,为复杂系统的数据挖掘及不确定性分析提供新的理论和方法,而且对空间数据分析、医疗诊断等应用领域有重要的理论意义和应用价值。
中文关键词: 粒计算;知识发现;粗糙集;概念格;直觉模糊集
英文摘要: Granular computing, as an important tool for knowledge acquisition and data mining, is a new theory, technology and method, which aims to simulate human thinking in solving large-scale complex problems. The key idea is to describe, reason and result problem from different views, different levels using information granules. By using the tools of rough sets, random sets, concept lattices and the evidence theory, the main objective of this project is to investigate theory and approach to information fusion, granular computing and knowledge acquisition from multi-source intuitionistic fuzzy data sets. It will be realized through the following specific goals: (1) To build models for the representation and emerging of information granularities form multi-source intuitionistic fuzzy data sets; (2) To explore theory and approach of information fusion and rule induction in multi-source intuitionistic fuzzy data sets; (3) To study algorithms of information fusion based on granular computing in multi-source intuitionistic fuzzy data sets; (4) To investigate uncertainty analysis for multi-source intuitionistic fuzzy information fusion. The results of this projects will not only enrich the theory of granular computing and information fusion by providing new theories and approaches for data mining in complex data, but also will be of theoretic significance and valuable applications in research fields such as spatial analysis, medical diagnosis, and so on.
英文关键词: Granular computing;Knowledge discovery;Rough set;Concept lattice;Intuitionistic fuzzy set