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 Fig 16. The Global climate model’s outcome for internal temperature differ. https://doi.org/10.1371/journal.pone.0333846.g016 Fig 17. Greenhouse’s exterior temperature and the dynamic model’s prediction. https://doi.org/10.1371/journal.pone.0333846.g017 and actual temperatures, especially during the peak and trough periods, which could indicate model flaws or outside disturbances. The temperature trend shows greater variability during periods of peak temperature, suggesting increased sensitivity to external factors like sunlight intensity, wind patterns, or sensor noise. It also generally corresponds with the sinusoidal pat- tern seen in Fig 15, indicating periodic environmental changes. These variations’ fluctuating amplitudes reflect changing environmental conditions. In Figs 17 and 18 show a significant agreement between the predicted and observed values, indicating that the dynamic model accurately and minimally represents the overall temperature trend. In Fig 17’s temperature variability demonstrates how intricate and dynamic the greenhouse’s external environment is. Although the model seems stable, it might be improved to better manage abrupt changes PLOS One https://doi.org/10.1371/journal.pone.0333846 October 14, 2025 21/ 30