理想信息系统及粗糙集模型的统一

Ideal information systems and unification of rough set models

粒计算是人工智能的重要方法.为了解决粒计算的基本问题——信息粒及其表示能力,提出了信息粒和信息粒基等概念,并探讨了它们的性质.从传统集合论和离散数学的角度出发,提出了理想信息系统假设,给出了信息粒基表示能力的计算方法及其数学性质;初步回答了“什么是信息粒?”“各种粗糙集模型是否可以统一?”等问题.研究结果为粒计算的进一步发展奠定了一定的数学基础.

Granular computing was usually regarded as an important technique in artificial intelligence.Some fundamental problems including information granules and their expression power were pending in granular computing.The concepts of information granules and information granule basis were proposed,and then their properties were investigated.From the perspectives of the classical set theory and discrete mathematics,ideal information systems were considered,and then a method for the expression power of an information granule basis and its mathematical properties were investigated.Several preliminary answers were given to their corresponding questions:1)what is an information granule?2)can various rough set models be unified?The results provided a mathematical foundation for the further development of granular computing.