Linguistic Z-Number Belief-Based Evidential Reasoning Approach for Energy Assessment

In the face of increasingly severe global issues such as climate change, environmental challenges, and energy constraints, promoting new energy sources has become crucial for accelerating sustainable development worldwide. In this regard, it is significant to establish an effective energy assessment mechanism. However, existing energy assessment methods ignored the uncertainty and reliability of evaluation information, which can lead to an incomplete decision-making process. Additionally, the information heterogeneity may lead to information loss in information fusion. To overcome these limitations, this study proposes a linguistic Z-number belief-based evidential reasoning approach., which can integrate heterogeneous information and its corresponding reliability using linguistic Z-numbers. Firstly, an evaluation matrix based on linguistic Z-number belief is constructed to express the natural language description information of experts. Next, the comprehensive belief degree is obtained according to the evidence reasoning algorithm. The comprehensive ranking result is obtained by the maximum, average and minimum utility values. An example of energy evaluation is taken to verify the effectiveness of this method. In conclusion, decision-makers in the energy sector can make more informed and reliable choices by adopting the proposed approach, ultimately contributing to the sustainable development of the global energy system.