Natural Environment Protection Strategy Based on Cyclic Neural Network

Abstract

After years of efforts in ecological environment protection (EP), China has made great progress in environmental protection, but there are still some problems in our ecological EP. In this paper, the strategy of natural environment (NE) protection is studied and analyzed based on recurrent neural network. The principles of NE protection and the basic structure of recurrent neural network are briefly summarized; The design of the cyclic neural network(CNN) model is discussed, and the application of the CNN in air quality prediction(AQP) is analyzed; Taking Shanghai AQP as the research object, combined with information entropy and gray correlation analysis methods, relevant input variables were screened out to build the network model, which helped us to have a general understanding of the future pollution factor concentration from the overall situation, and then put forward NE protection strategies to achieve good and effective protection of the NE.