Research on green building optimization design of smart city based on deep learning

Abstract

With the advent of the era of "data revolution", the technical development trend of architecture in the future will change greatly; Under the common goal of global sustainable development, improving the relationship between architecture and man, architecture and nature, and realizing and improving the functional requirements of architecture in an efficient way is the main topic of architectural development today. The rapid development of artificial intelligence (AI) technology makes the application of deep learning in various fields possible. The most popular is the application of artificial intelligence to improve urban planning and design. Deep learning has been used in many cities to optimize traffic flow, reduce energy consumption and improve the efficiency of green buildings. Machine learning using multi-layer neurons is called deep learning. Each neuron receives input from other neurons through weighted connections, which are trained by algorithms based on historical data or real-world experience. This makes the prediction more accurate than traditional methods (such as linear regression model or linear regression model).