An Analysis of Climate Change Based on Machine Learning and an Endoreversible Model

Several Sun models suggest a radioactive balance, where the concentration of greenhouse gases and albedo effect are related to Earth’s surface temperature. There is considerable increment in due anthropogenic activities. Climate change correlates with this alteration atmosphere an increase Efficient forecasting climate its impacts could be helpful respond threat c.c. develop sustainably. Many studies have predicted temperature changes coming years. The global community has create model that can realize good predictions ensure best way deal warming. Thus, we propose finite-time thermodynamic (FTT) approach current work. FTT solve problems such as faint young paradox. In addition, use different machine learning evaluate our method compare experimental prediction results.