A forecasting method of airport traffic flow based on weather data mining

Abstract

The invention discloses an airport traffic flow prediction method based on weather data mining, which comprises the following steps: extracting required weather information from the history data of aselected airport according to preset rules, and identifying the weather information according to preset conditions; Obtain the airport flow statistics data in a specific period of time of the selectedairport, and match the airport flow and weather information, in which, the airport flow is divided into take-off, landing and flying three types; Based on BP neural network, the matching informationof airport traffic is trained and learned respectively, and the influence relationship of different weather types on airport traffic is obtained. The influence relationship is analyzed and verified, and the corresponding BP neural network model is finally obtained. Finally, based on the trained BP neural network model and the forecast weather information, the airport's inflow and outflow are classified and forecasted. The method can effectively solve the normal operation of flights in complex weather and improve the air traffic safety level and efficiency of the terminal airspace.

Description

technical field [0001] The invention relates to an air traffic flow prediction technology, in particular to a traffic flow prediction method in an airport terminal area under different weather types. Background technique [0002] With the development of the civil aviation industry, the imbalance between the airspace capacity of the terminal area and the traffic demand has become more and more obvious. The problem of flight delays often occurs, and the punctuality rate of flights is low. The problem of flight delays significantly affects the development of the air transport industry. In order to reduce delays and improve flight regularity, air traffic flow management under the influence of weather has become imperative. [0003] The vigorous development of my country's air transportation industry has brought about a continuous increase in air traffic demand, and airport delays caused by complex weather are increasing. The future trend of air traffic flow management is to stu...

AI Technical Summary

Problems solved by technology

Most of the existing airport traffic volume forecasts are based on the peak hour of the airport to determine the maximum traffic volume of the airport terminal area, runway and taxiway, but there is a lack of traffic volume forecasts under the influence of different types of weather; or the weather factors are considered, but The amount of calculation is too large, and its applicability is worthy of further study

The impact of weather changes on traffic volume has a certain random regularity. More and more air traffic managers, decision makers and researchers have realized that conventional airport traffic volume forecasting methods cannot fully and effectively reflect and reveal the impact of weather changes on traffic volume. capacity, while statistics consider probability to be a science that studies the regularity of random phenomena

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