Sustainable renewable energy systems with entropy based step-wise weight assessment ratio analysis and combined compromise solution.

This paper presents a robust technique to evaluate utilization-oriented renewable energy systems (RESs) for sustainable development in Industry 4.0. This goal is accomplished by incorporating circular intuitionistic fuzzy sets (CIFS) into the multi-criteria decision-making (MCDM). The concept of CIFS efficiently expresses decision makers (DMs) preference in the MCDM process with degrees of membership (DM), degrees of non-membership (NDM), and a parameter radius r that represents the degree of information uncertainty. Firstly, weights are allocated to these criteria through an improved entropy based step-wise weight assessment ratio analysis (SWARA) method. Secondly, the combined compromise solution (CoCoSo) technique is modified to match CIFS requirements to complete the ranking of the available solutions. Thirdly, the robustness of the approach is evaluated by the execution of a sensitivity study, which demonstrates the technique's consistency in the face of shifting circumstances. The study develops a robust three-way MCDM framework namely Entropy-SWARA-COCoSo that include evaluation criteria and prospective sources of RESs. The usefulness of this technique in making complex decisions on sustainable energy in the face of unpredictability is further proven by a comparative study that demonstrates how it outperforms other MCDM methods that are already in practice. The application demonstrates the practical usefulness of merging CIFS with decision-making procedures. Policymakers, managers, and stakeholders in the RESs sector might benefit substantially from this framework. • Optimizing renewable energy systems with CIFS environment. • The criterion weights are determined with Entropy-CRITIC method. • Entropy-CRITIC-CoCoSo method is established for MCDM process. • Sentiment analysis and comparative analysis with AI-driven models. [ABSTRACT FROM AUTHOR]