Complexity Analysis of Air Traffic Flow Based on Sample Entropy

Air traffic flow has complex nonlinear characteristics, and time series is an effective way to study air traffic flow. In order to quantify the complexity, analyze the complex mechanism and provide scientific basis for modeling, forecasting and controlling of air traffic flow, firstly, the calculation method of sample entropy and multi-scale sample entropy was introduced. After that the actual operation data of No.1, No.2 and No.4 sectors of Sanya were collected for 28 consecutive days. Then, the complexity of time series was calculated based on sample entropy, and the influence of different parameters was analyzed. The calculation results show that the air traffic flow in No.2 sector is the most complex, followed by No.4 sector, and the complexity of No.1 sector is the smallest. The calculation results indicate that the sample entropy and the multi-scale sample entropy can quantitatively analyze the complexity of air traffic flow time series, and have little dependence on the length of the time series.