Application of fuzzy credibility graph in climate mitigation strategy assessment

The challenges posed to our environment by climate change are immense and are increasing every day. Its impacts on ecosystems, weather patterns, and human health are extensive. It is imperative that we tackle climate change to save the environment and ensure a sustainable future. It is essential to implement effective climate change mitigation and control strategies to conserve natural resources and improve global well-being. Therefore, we develop a novel decision making model based on the fuzzy credibility graph to select the best climate change mitigation strategies. In this article, the fuzzy credibility graph, the direct product of fuzzy credibility graphs, the degree of a vertex, and the total degree of a vertex are defined first. After that, we apply the proposed decision making model to select the best climate change mitigation strategy. For this, we collect the expert information and the fuzzy credibility edges information about the climate change mitigation strategies, and process the proposed model to compute the relative closeness of the alternatives and identify the most suitable climate change mitigation strategy. To evaluate the performance of the proposed model, we compare it with existing decision making methods. The results demonstrate that our model provides accurate and effective decision support. Additionally, we use Spearman's correlation coefficient to verify the consistency of the rankings. The comparative analysis confirms the validity and reliability of the proposed model in supporting climate mitigation decisions.

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Publication Details

Journal
Scientific Reports
Published
2025-08-15
DOI
https://doi.org/10.1038/s41598-025-15775-2
Citations
3
Primary Topic
Multi-Criteria Decision Making
Type
article
Field-Weighted Citation Impact
6.32
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article

Application of fuzzy credibility graph in climate mitigation strategy assessment

Muhammad Nawaz, Ihsan Ullah, Saleem Abdullah, Hameed Gul Ahmadzai
3 citations
Scientific Reports
Multi-Criteria Decision Making
6.32
article

Application of fuzzy credibility graph in climate mitigation strategy assessment

Muhammad Nawaz, Ihsan Ullah, Saleem Abdullah, Hameed Gul Ahmadzai
article en
3 citations

Abstract

The challenges posed to our environment by climate change are immense and are increasing every day. Its impacts on ecosystems, weather patterns, and human health are extensive. It is imperative that we tackle climate change to save the environment and ensure a sustainable future. It is essential to implement effective climate change mitigation and control strategies to conserve natural resources and improve global well-being. Therefore, we develop a novel decision making model based on the fuzzy credibility graph to select the best climate change mitigation strategies. In this article, the fuzzy credibility graph, the direct product of fuzzy credibility graphs, the degree of a vertex, and the total degree of a vertex are defined first. After that, we apply the proposed decision making model to select the best climate change mitigation strategy. For this, we collect the expert information and the fuzzy credibility edges information about the climate change mitigation strategies, and process the proposed model to compute the relative closeness of the alternatives and identify the most suitable climate change mitigation strategy. To evaluate the performance of the proposed model, we compare it with existing decision making methods. The results demonstrate that our model provides accurate and effective decision support. Additionally, we use Spearman's correlation coefficient to verify the consistency of the rankings. The comparative analysis confirms the validity and reliability of the proposed model in supporting climate mitigation decisions.

Scientific ReportsVol. 15(1)
Abdul Wali Khan University Mardan (PK), Paktia University (AF)
Climate action
Openalex Percentile: Top 3%
Multi-Criteria Decision Making
6.32
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Application of fuzzy credibility graph in climate mitigation strategy assessment — Muhammad Nawaz, Ihsan Ullah, et al. · Scientific Reports (2025) | TGRS Research Map | TGRS