Research on Regional Carbon Emission Trends Based on LSTM

With the rapid development of the economy, carbon emissions have been increasing year by year. Carbon emission intensity is one of the important reasons for global climate change and environmental pollution. Accurately predicting future carbon emission trends and analyzing their patterns are of great significance for environmental protection and economic development.Traditional prediction methods are basically based on statistical models. However, due to the complexity and non-linearity of carbon emission data, traditional methods often find it difficult to achieve high accuracy and stability. This study uses the Long Short-Term Memory( LSTM) neural network model to predict future carbon emission trends through learning and training historical data. The experimental results indicate that this method has high stability and accuracy, and can provide effective references for carbon reduction and environmental protection.