2. Then the collected data are cleaned, sorted and preprocessed to ensure the quality and availability of the data.
3. Then, according to the law of temperature change and the actual situation, establish appropriate mathematical models, such as linear regression model and nonlinear fitting model.
4. Then, using appropriate mathematical methods, the established model is solved, and the parameters and predicted values of the model are obtained.
5. Then, the historical data and predicted values are plotted into charts to show the temperature change trend and predicted results more intuitively.
6. Then analyze the chart, compare the difference between the actual data and the predicted value, and evaluate the accuracy and reliability of the model.
7. Finally, according to the analysis results, the model is applied to the actual scene, such as predicting the future temperature change trend and formulating the corresponding control strategy.