GGDP Global Climate Change Prediction Model Based on BP Neural Network

GDP is often used to measure the economic status of a country. However, the GDP model, which only focuses on economic gains, ignores the price that Mother Earth silently endures behind the shiny economic data. In order to protect the environment and resources as generous gift to our future generations, deserved people, green GDP (GGDP) model is developed.we first define the replacement of GGDP model to represent the change of a country from the maximum GDP as the development strategy to the maximum GGDP.Then, we normalize the commonly used GGDP and GDP accounting methods by the Cobb-Douglas aggregate model to find the relationship between GGDP, environmental damage factors.We also eliminate the GDP-related terms in the original GGDP model to ensure the independence of the GGDP model, and test the model reliability and reconcile it. In order to solve the climate global change, we grouped 233 countries and regions around the world according to their ability to influence the environment, and derived the corresponding parameters, environmental damage factors of the maximum GGDP model established respectively. The relationship between the damage factors and the main components of the climate parameters is then established by neural network model,and the impact of the maximum GGDP model on the global climate is obtained: the rising trend of the temperature component is effectively curbed, and the water cycle component will be flattened in general.