Bird Strike Risk Analysis at Airports Based on BP Neural Network

Bird strike events have an increasing threat to flight safety. Bird strike risk analysis is an important part of bird strike prevention at airports. Current mathematical model based on the bird survey at airports has its deficiency. In this paper, a new risk analysis model based on a BP (Back Propagation) neural network is proposed. In this model, 4 risk factors are selected as the input layer of BP neural network and bird strike risk is used as the output layer. Finally, the accurate and reliable results show that this available model can provide a new idea for bird strike risk analysis and serve as an effective method to set bird control priorities.