(1) Discuss the background and significance of research, the progress of research at home and abroad, and where are the innovations of research. Paper structure. The structure of the paper is accompanied by a flowchart to illustrate.
(2) Urban air quality prediction model: data sources, data sources are very important, must be explained in detail, model data characteristics analysis, the relationship between pollutant concentration and time, the relationship between pollutant concentration and weather, the relationship between pollutant concentration and space, summary.
(3) Time prediction model based on machine learning: introduction of machine learning algorithms used, model construction and description, summary.
(4) Spatial prediction model based on machine learning (must use CNN!!!, because I have already told the teacher to use CNN in this chapter, and it cannot be changed): Introduction to the machine learning algorithm used, model construction and description, summary.
(5) Predictive model based on machine learning fusion of time and space: introduction of machine learning methods used, model construction and explanation, summary.
(6) Analysis of experimental results: experimental environment, data preprocessing, model training, model evaluation, model predictive analysis. summary.
(7) Model evaluation: model robustness and shortcomings
(8) Conclusions and prospects: summary, innovations in the thesis, research prospects
(9) references

The method used for machine learning in the headline above should be specified. The construction of the model must be innovative!

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