Design of global climate control based on fuzzy systems with concept of carbon emissions

PLOS One Design of global climate control based on fuzzy systems • Uncertainty Management: Developing trustworthy techniques to measure and control uncertainty in T–S models in order to generate forecasts that are more precise and compre- hensible. • Long–Term Modeling: Research techniques to improve the T–S model’s ability to project the climate over the long run while accounting for the dynamic nature of climate systems. • Socio–Economic Consideration: We can bridge the gap between social dynamics and climate science by incorporating socio-economic factors, human behavior, and policy consequences into T–S models. • Interdisciplinary Collaboration: Fostering communication and collaboration between cli- mate scientists, mathematicians, decision-makers, and other experts to manage the com- plex relationships and challenges associated with the application of the T–S model in climate change modeling. The Takagi–Sugeno Fuzzy Models (T–S models) offer a promising approach to understand- ing climate change dynamics, they are not without challenges. These concerns need to be rec- ognized and addressed in order to ensure that T–S models are used in climate change research in an accurate and significant manner. In Data inaccuracy, high–quality climate data is nec- essary for accurate forecasts, but that data gaps and uncertainties can inject mistakes into the models, reducing the reliability of the results. Similarly, model complexity for the T–S mod- els may involve additional variables and rules due to the complexity of climate systems, which

could impact their accessibility and computational efficacy. For the model complexity, the T– S models may involve more factors and rules due to the complexity of climate systems, which could impact their accessibility and computational efficacy. Author contributions Conceptualization: Shamrooz Aslam. Data curation: Shamrooz Aslam. Formal analysis: Wer-Jer Chang. Funding acquisition: Wer-Jer Chang. Investigation: Wer-Jer Chang, Shamrooz Aslam. Methodology: Wer-Jer Chang, Shamrooz Aslam, Hazrat Bilal, Muhammad Javid Nawaz. Project administration: Saira Naseer. Resources: Saira Naseer, Muhammad Javid Nawaz. Software: Muhammad Hashim Bukhari, Hazrat Bilal. Supervision: Shamrooz Aslam. Validation: Hazrat Bilal. Visualization: Saira Naseer. Writing – original draft: Saira Naseer, Shamrooz Aslam. Writing – review & editing: Shamrooz Aslam, Muhammad Hashim Bukhari, Muhammad Javid Nawaz. PLOS One https://doi.org/10.1371/journal.pone.0333846 October 14, 2025 28/ 30