基于Prophet-ARIMA模型的民航周转量预测研究

周转量作为计算运输成本、客货运收入、劳动生产率、客货运平均行程和运输密度等指标的依据,能比较全面和确切地反映运输的成果以及运输生产产品的数量,其预测对民航的科学化发展有重要意义.与民航业的快速发展和民航市场的不断扩大相比,目前民航的预测模型种类较少.为探索一种更为有效的方法来提高民航周转量预测准确率,较为新颖的Prop...

Application of Prophet-ARIMA Combined Model in Forecast of Civil Aviation Turnover

As the basis for calculation of transport costs, passenger and freight income, labor productivity, average passenger and freight travel and transportation density, turnover can reflect the results of transportation comprehensively and accurately and the number of products produced in transportation, and its prediction is of great significance to the scientific development of civil aviation. Compared with the rapid development of civil aviation industry and the continuous expansion of civil aviation market, there are few forecasting models for civil aviation at present. To explore a more effective way to improve civil aviation prediction, we introduce novel Prophet model and NeuralProphet model pairs to predict civil aviation cargo turnover, cargo and mail turnover, passenger turnover and total turnover of civil aviation. In comparison with a single model, it is found that the Prophet model and the NeuralProphet model predict better results compared to the traditional model cubic exponential smoothing method and ARIMA model. In order to further optimize the model and make the prediction results more accurate, a weighting method is used to create the Prophet-ARIMA composite model. The result is the Prophet-ARIMA model has the best performance compared with other models, which provides a new idea for civil aviation forecast.