Fractional Orthotriple Fuzzy Dombi Power Partitioned Muirhead Mean Operators and Their Application for Evaluating the Government Information Disclosure on Public Health Emergencies

Abstract

Information disclosure is an important prerequisite and guarantee for the government to answer public health incidents in a timely manner, and is also a basic requirement for the management of emergencies. Evaluating the information disclosure on public health incidents is conducive to improving the quality of emergency information disclosure and comprehensively enhancing the emergency answer and treatment ability of public health incidents. In response to the complex uncertainties in the assessment of information disclosure on public health incidents, this paper proposes a new fuzzy multi-attribute evaluation method. First, a multi-attribute evaluation system for the assessment of information disclosure on public health emergencies is proposed. Then, a novel approach to information disclosure assessment is proposed on the basis of Dombi power divided Muirhead mean operators of fractional orthotriple fuzzy, which can fully consider the relationship between properties and the division of relationships within properties and reduce the distortion in the evaluation process. Meanwhile, it can avoid the impact of singular values on the overall evaluation outcomes of the government. In the end, the effectiveness and flexibility of the approach are validated through an empirical study of a real-life case with comparative analysis and sensitivity analysis.