Uncertainty measurement for incomplete interval-valued information systems by θ-rough set model

Incompleteness in interval-valued information systems has leaded to many difficulties in acquiring knowledge. Rough set theory, proposed by Pawlak, has been widely used to deal with uncertainty, granularity and incompleteness of information. In this paper, we propose a θ-rough model for incomplete interval-valued information systems based on tolerance-similarity relation. Moreover, the accuracy, roughness and approximation accuracy are constructed to evaluate the uncertainty in incomplete interval-valued information systems. Our approach is examined and tested by a case study. Results show that the proposed approach supplies a reasonable strategy for interval-valued information with missing values.