At present, weather is the most important factor causing flight delays, so it is very important to study flight delays caused by weather conditions. In this paper, we propose the airport delay WITI, which is composed of visibility, wind, relative humidity, special weather and executed departure volume, based on the characteristics of airport departure delay. Then a Multiple Linear Regression model is established to calculate the influence weights of each index on airport delay. Next, we establish grey prediction model to predict airport delay rate according to weather prediction data. Finally, we choose the ZUUU Airport weather data and the ZUUU Airport operation data as a research example.

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