Civil Aviation Passenger Traffic Prediction Based on IGABP Algorithm Considering Data Volume Limitation

Understanding civil aviation passenger traffic is critical for airlines to make key scientific decisions and feasible plans, and is an important safeguard to ensure successful implementation. An accurate prediction of China's civil aviation passenger traffic will provide effective decision support for airlines, helping them rationalize resources, optimize flight schedules, and improve operational efficiency. In this paper, considering the limitation of the amount of civil aviation passenger traffic data, an IGABP model is established under the condition of grasping the data characteristics, and a Genetic Algorithm (GA) is used to filter the features of the neural network and optimize the input features as well as the number of features, so as to predict the amount of civil aviation passenger traffic.