With the improvement of people's living standards, more people are concerned about the air quality and safety of residential cities, and the concept of healthy urban space is gradually becoming deeply rooted in people's hearts. This study is based on long and short term memory neural network algorithms, incorporating AMs into them. The research adjusts the data input to the algorithm according to spatiotemporal characteristics and incorporates a stack-type self-coding network into an improved long and short term memory neural network to predict the concentration of urban air pollutants. The ai...
