A novel interval grey prediction model considering uncertain information

Abstract Current studies on grey systems are mainly focused on known and deterministic information, rather than uncertain one. Different from previous schemes, this paper proposes an innovative prediction model based on grey number information, which extends its application dealing with uncertain information. By exploiting the geometric features of grey numbers on a two-dimensional surface, all grey numbers can be converted into real numbers without losing any information by means of proposed algorithms. Then a prediction model is established based on those real number sequences. In addition, a general case simulation is carried out to verify the effectiveness and practicability of the proposed model.

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