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 12. Response of atmospheric (𝜉A) with and without fuzzy rules. https://doi.org/10.1371/journal.pone.0333846.g012 Fig 13. Response of terrestrial biosphere (𝜉T) with and without fuzzy rules. https://doi.org/10.1371/journal.pone.0333846.g013 another suggests that the model’s prediction and the actual temperature are in good agree- ment. A periodic temperature variation that may be impacted by external or control sys- tem elements is suggested by the data’s apparent sinusoidal rhythm. The percentage discrep- ancy between the measured and predicted temperatures is displayed in this graphic. There is a noticeable increase in the error between 4 and 6 seconds, even though it stays minor and steady for the most of the time–line. This implies that the model had trouble correctly pre- dicting the temperature during this time, possibly as a result of abrupt changes in the sur- rounding environment or quick variations. The tight match between the anticipated and mea- sured data in Fig 15 shows how well the model predicts temperature. The steep error spikes in Fig 6 imply that either there was noise in the data during that time period or the model PLOS One https://doi.org/10.1371/journal.pone.0333846 October 14, 2025 19/ 30