Intelligent allocation and scheduling of airport security-check service resources is one of the effective ways to improve passenger service level and operational efficiency within the airport, while the accurately prediction about the security-check passenger traffic is the prerequisite for dynamic allocation and scheduling. The historical passenger data at Tianjin airport security inspection is taken as the research object, and a prediction method based on BP neural network is put forward so as to establish a prediction model of security-check passenger flow. Besides, the proposed model is verified by the actual passenger flow of Tianjin airport. Results show that the accuracy of the proposed algorithm can reach to above ninety percent. So this prediction method can be well applied to the security-check flow prediction in the airport terminal, which can support a high efficiency solution for the airport operators to dynamically allocate security-check services resources.
The Prediction Model Based on BP Neural Network about Airport Security-check Passenger Flow
2019
Article (Journal)
Electronic Resource
Unknown
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