Information structures in set‐valued information systems from granular computing viewpoint

Granular computing is a mathematical tool in artificial intelligence. An information system is an important model in the field of artificial intelligence, and an information structure is its basic structure. Set‐valued information systems are the generalization of single‐valued information systems. This paper investigates information structures in a set‐valued information system from granular computing viewpoint, that is, information structures are viewed as granular structures. Information structures in a set‐valued information system are first described through set vectors. Then, the dependence between information structures in the same set‐valued information system is depicted from 2 aspects, and information distance for calculating the difference between information structures in the same set‐valued information system is proposed. Next, properties of information structures in a set‐valued information system are given by means of inclusion degree, information distance, condition information amount, and lower approximation operator. Finally, group, mapping, and lattice characterizations of information structures in a set‐valued information system are obtained. These results will be helpful for understanding the essence of structure and uncertainty in set‐valued information systems.

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