The Weighted Influence Nonlinear Measurement System (WINGS) method originates from DEMATEL, which has the advantage of analyzing the interweaved determinants and the causal relationships within them. The innovation is mainly reflected in considering both the strength of the influencing factors themselves and the relationship of their mutual influence. To address the problems of ambiguity in assessing information and uncertainty in the judgment of expert group, this paper proposes fuzzy WINGS improved by D numbers (fuzzy D-WINGS). Combining D numbers with Triangular fuzzy numbers can overcome the limitation of mutually exclusive and collectively extensive set. The WINGS method is used to reveal the interdependent causal relationships by recognizing the orientation and strength of the factors. Utilizing the MICMAC method to draw matrix analysis diagrams can further reveal the relationship among them. Finally, a practical case study is conducted to prove the practicability of this fuzzy D-WINGS–MICMAC method.

加权影响非线性测量系统 (WINGS) 方法源自 DEMATEL，其优点是分析交织的行列式及其内部的因果关系。创新主要体现在考虑影响因素本身的强弱和相互影响的关系。针对评估信息的模糊性和专家组判断的不确定性问题，本文提出了由D数改进的模糊WINGS（fuzzy D-WINGS）。将 D 数与三角模糊数结合可以克服互斥集和集体扩展集的限制。WINGS方法用于通过识别因素的方向和强度来揭示相互依赖的因果关系。利用MICMAC方法绘制矩阵分析图可以进一步揭示它们之间的关系。最后，通过一个实际案例研究证明了这种模糊 D-WINGS-MICMAC 方法的实用性。