Abstract
The financial risk evaluation of new energy vehicle (NEV) industry is conducive to the popularization of NEVs, to encourage more investment into the NEV industry, and to promote the improvement of the risk control system. When evaluating the performance of NEV industry in China, it is usually full of uncertainty and dynamic. q-Rung orthopair fuzzy set (q-ROFS) has the characteristics of non-membership and membership with adjustable parameterization q, which is a very effective mathematical model to capture uncertainty. In this paper, the q-rung orthopair fuzzy (q-ROF) distance measure based triangle orthocenter is given. Then, q-ROF score function (SF) based distance measure is proposed for disposing of comparison issue. Moreover, we present nonlinear comprehensive weighting method by integrating subjective weight information and objective weight information (determining by water-filling theory). In order to solve the counter-intuitive phenomena and dynamic trend issue, the dynamic q-ROF aggregation operators are investigated and their properties are proved. Whereafter, q-ROF multi-criteria decision making (MCDM) approach based projection ranking by similarity to referencing vector (PRSRV) is proposed for evaluating financial risk of NEV industry, along with the sensitivity analysis. Finally, a comparison with some existing MCDM methods states that the presented method has strong data adaptability.
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