Abstract

In the field of multi-dimensional intelligent decision-making, the evaluation results rely on the subjective experience of the evaluation experts. However, the evaluation information generated by personal expert preferences can has certain impact on the decision-making results.For this problem, we present an intelligent decision model based on H-convex combination and expert preference. The H-convex combinatorial matrix algorithm is used to assemble the individual judgment matrices, which reduces the inconsistency and non-reciprocity of the group decision matrix. The expert preference quantization formula is used to obtain the preference values of the corresponding experts, which are taken into the H-convex combination as power exponents. This solves the impact of expert preference differences on decision outcomes. The feasibility and effectiveness of the proposed method are verified by some evaluation cases.

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