Prediction of Mianyang Carbon Emission Trend Based on Adaptive GRU Neural Network

In recent years, the issue of carbon emissions has attracted worldwide attention. This innovative research idea is to input the total carbon emission data of Mianyang City from 2000 to 2020 into the GRU network model to predict the carbon emission trend in the next few years. In view of the complexity of neural network model training, this paper introduces adaptive coefficients to dynamically adjust the number of units of GRU to improve model training efficiency and accuracy. Through the processing and analysis of the data, the adaptive GRU network model is used to transform the internal relationship of the data sequence into a higher-order expression, thereby realizing the prediction of the future “carbon neutrality” trend of Mianyang City. The prediction results will provide reference suggestions for many problems existing in the field of green buildings in Mianyang, and provide suggestions for Mianyang to achieve “carbon peak and carbon neutrality” as soon as possible.