A new pythagorean fuzzy entropy and knowledge measure-based ranking approach using two-step normalization for the renewable energy source assessment

Journal Article

2026

Published in: https://doi.org/10.1016/j.engappai.2026.115853

Energy demand is increasing tremendously due to the growing world population and rapid technological advancement. In the meantime, dependence on fossil fuels is one of the main causes of environmental problems like climate change and greenhouse gas emissions. These challenges highlight how vital it is to switch from fossil fuels to sustainable renewable energy sources (RESs). Renewable energy technologies can be an option that can help nations achieve sustainable development goals. However, selecting the most appropriate RES for any precise geographic zone is a complicated decision-making problem as of comprising various measured criteria. In this regard, we develop new entropy and knowledge measures for Pythagorean fuzzy sets (PFSs) along with their desirable properties. On the basis of these measures, an integrated Pythagorean fuzzy-entropy−stepwise weight assessment ratio analysis (SWARA)−alternative ranking order method accounting for two-step normalization (AROMAN) methodology is proposed to prioritize and evaluate the various RESs over diverse considered criteria. In this methodology, the developed entropy and score function-based approach is presented to obtain objective weights of criteria, together with determining subjective weights of criteria using the SWARA method. AROMAN is employed to prioritize the RES options on PFSs. Comparative study and sensitivity analysis are discussed to demonstrate the feasibility and applicability.

• Publisher Name: PERGAMON-ELSEVIER SCIENCE LTD
• Publishing City: England
• Volume Number: 182
• Magazine \ Newspaper: Engineering Applications of Artificial Intelligence
• Pages: 1 to 21