摘要
Data granulation is a good tool of decision making in various types of real life applications. The basic ideas of data granulation have appeared in many fields, such as interval analysis, quantization, rough set theory, Dempster-Shafer theory of belief functions, divide and conquer, cluster analysis, machine learning, databases, information retrieval, and many others. In this paper, we initiate some new topological tools for data granulation using rough set approximations. Moreover, we define some topological measures of data granulation in topological I formation systems. Topological generalizations using δβ-open sets and their applications of information granulation are developed.
Data granulation is a good tool of decision making in various types of real life applications. The basic ideas of data granulation have appeared in many fields, such as interval analysis, quantization, rough set theory, Dempster-Shafer theory of belief functions, divide and conquer, cluster analysis, machine learning, databases, information retrieval, and many others. In this paper, we initiate some new topological tools for data granulation using rough set approximations. Moreover, we define some topological measures of data granulation in topological I formation systems. Topological generalizations using δβ-open sets and their applications of information granulation are developed.
