Research on flight training prediction based on incremental online learning

With the continuous development of civil aviation industry in recent years, the demand for flight training has been increasing and the flight training safety requirements have been improving. To address the problem that the mining of flight training data is not deep enough and the research of flight training data is delayed, the study proposes a flight training data prediction model based on incremental learning to achieve real-time flight training data prediction and ensure flight training safety. The model firstly uses a small amount of data to generate a base model; secondly, on this base model, a specific amount of data is input to the model for learning according to a certain time frequency to continuously optimize the base model; finally, the model is compared with several models for experiments. The experimental results show that compared with the traditional model, the model has high prediction accuracy and good real-time performance in flight training data prediction, which can better ensure flight training safety.