In this paper, based on the FT dataset, the sample data of 81 research subjects and 1049 lines in the last 2 years, data cleaning was performed to quantify and analyze them, and a Prophet time series model based on time and variable values combined with time series decomposition and machine learning fitting to do so was established for the period 2023-01-01 to 2023-01-31 using python software for forecasting and solving. The results are interpreted and analyzed for the network law. The model predicts well, with a view to providing some implications for forecasting research in other fields.
Research and Application of Time Series Prediction Model Based on Prophet Algorithm
11.10.2023
3449114 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Aviation risk prediction based on Prophet–LSTM hybrid algorithm
Emerald Group Publishing | 2023
|Traffic volume prediction method of Prophet-DeepAR model
Europäisches Patentamt | 2023
|