Research On Airspace Sector Capacity Evaluation Technology In Severe Convective Weather

With the rapid development of the civil aviation transportation industry,air traffic congestion is becoming increasingly serious.Once affected by severe convective weather,it will cause flight delays and aggravate air traffic congestion.Air traffic flow management is an important means to alleviate congestion,and airspace sector capacity assessment is the basis of traffic management,and accurate capacity assessment is an important factor in improving the efficiency of traffic management.Accurate assessment of airspace sector capacity under severe convective weather is of great significance for improving flight operation efficiency and alleviating airspace congestion.First of all,the weather level was divided according to the degree of influence of severe convective weather on air traffic,and the coordinate ordering Graham-scan model was constructed,which solved the problem of increasing complexity due to a large number of scanning discrete points.And proposed a time rate index to evaluate the speed and accuracy of the flight forbidden area design.The example shows that the Grahamscan algorithm based on coordinate sorting is 3% faster than the Graham-scan algorithm.Secondly,based on the design of the flight forbidden area,the risk probability was introduced,and the improved WITI model was established to solve the uncertainty problem of sector capacity evaluation.Based on the capacity evaluation index system,which was established by analyzing the factors of severe convective weather affecting airspace sector capacity,a sector capacity evaluation model optimized by GA-BP neural network was constructed.And the accuracy of capacity evaluation was enhanced by improving the weight and threshold of BP neural network.Finally,a certain airspace sector was taken as an example to verify.The results show that the improved WITI method is suitable for evaluating small sample data and sector capacity under saturation,and the calculation is relatively simple.The GA-BP neural network method to improve the accuracy of airspace sector capacity assessment by 90%,but its calculation principle and process are more complicated.Figure 29;Table 16;Reference 67...