Reinforcement Model of Green Building Materials Based on Grey Neural Networks

Abstract

With the rapid growth of China’s economy, all kinds of large or super-large buildings are constantly emerging, people pay more and more attention to building safety and environmental protection, and the reinforcement technology of green building materials plays an increasingly important role. The design involves a wide range of reinforcement. In the concrete design, it is necessary to comprehensively consider various factors, improve the safety of material structure through effective measures and ways, and realize the stable development of the construction industry. This paper analyzes and discusses the reinforcement design of green building materials. Grey model and NN model are two commonly used models in building prediction. This paper applies it to the reinforcement of green building materials and constructs a combined grey NN model. It combines the advantages of grey theory model and artificial NN model. Through the organic combination of grey theory and NN model, complex uncertain problems can be solved. It will be used in data processing of reinforcement monitoring and can get ideal calculation results. The reinforcement design in this paper can improve the use safety of buildings and realize the stability and sustainable development of the industry.