Due to the limitation of assessors’ knowledge and the uncertainty of risks, risk assessment data reasonably are given in the form of linguistic terms, safety risk assessment in petrochemical industry is often a multi-criterion and multi-expert information fusion based on linguistic terms(MCMEIF-LT) problem. A novel model dealing with the MCMEIF-LT problem is presented in this paper. Firstly, the individual linguistic assessment distributions are fused to collective distributions and multiple criteria are fused to a comprehensive criterion. In the fusion process, the objective weights of assessment experts are calculated with using the credibilities of assessment data and the attitudes of decision makers are considered. Secondly, a Fuzzy Number Weighted Ordered Weighted Aggregation(FN-WOWA) operator which can transform a fuzzy number into a crisp value is proposed. In the FN-WOWA operator, the utility function can incorporate the assessors’ loss-based risk attitudes and the membership function can reflect the importance of the values in the integrated fuzzy number. Based on crisp values, a risk matrix is constructed. Finally, a real application is demonstrated to show the flexibility and practicality of the MCMEIF-LT model.

由于评估者知识的局限性和风险的不确定性，风险评估数据以语言形式合理地给出，石化行业的安全风险评估通常是基于语言术语的多准则，多专家信息融合（ MCMEIF-LT）问题。本文提出了一种新颖的MCMEIF-LT问题模型。首先，将单个语言评估分布与集体分布融合在一起，将多个标准与一个综合标准融合在一起。在融合过程中，使用评估数据的可信度计算评估专家的客观权重，并考虑决策者的态度。其次，提出了一种可以将模糊数转换为清晰值的模糊数加权有序加权聚合算子。在FN-WOWA运算符中，效用函数可以包含评估者基于损失的风险态度，而隶属函数可以反映值在集成模糊数中的重要性。基于清晰的值，构建风险矩阵。最后，演示了一个实际应用程序，以显示MCMEIF-LT模型的灵活性和实用性。