ArticleScientific reports2025
Multi-experts decision support system for recycling of waste material using some circular pythagorean fuzzy Muirhead means.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Enhancing educational environments: A sustainable approach through creative design and upcycling applications.Scientific reports · 2026Article
- A robust decision making algorithm for handling uncertainty in career planning via a circular intuitionistic fuzzy SWARA WASPAS method.Scientific reports · 2026Article
Corrections and comments
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Authors and funding
4 authors.
Funding
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Abstract
This study tackles the critical challenge of waste material recycling, which is worsened by the growing global population and the necessity for efficient recycling processes. To address this issue, we introduce a pioneering approach that leverages circular Pythagorean fuzzy set theory, a sophisticated extension of fuzzy and intuitionistic fuzzy information. By formulating Muirhead mean and dual Muirhead mean aggregation operators within this framework, we facilitate structured and intelligent decision-making for assessing waste recycling alternatives. Our methodology and algorithm for multi-criteria group decision-making problems are showcased through a practical example, highlighting the efficacy and dependability of our approach. This research makes a significant contribution to the development of more efficient waste recycling processes and informed decision-making. The proposed approach enables decision-makers to evaluate waste recycling alternatives more comprehensively and systematically, taking into account multiple criteria and stakeholder perspectives. The findings of this study have important implications for policymakers, waste management professionals, and stakeholders seeking to improve waste recycling practices and reduce environmental impacts. By providing a more effective and reliable decision-making framework, this research aims to support the development of sustainable waste management systems. A sensitivity analysis illustrates the effectiveness and reliability of the proposed work. Finally, we adopted the comparative study and highlighted the advantages of defined work.
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Registered trials
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