Airspace operation situation evaluation and classification method based on fuzzy reasoning

Abstract

The invention discloses an airspace operation situation evaluation and classification method based on fuzzy reasoning and belongs to the technical field of airspace situation evaluation and classification. The method comprises the following steps: 1, processing airspace operation situation samples in a to-be-processed sector; 2, establishing a primary fuzzy reasoning system based on the airspace operation situation samples in the to-be-processed sector; 3, optimizing interpretability and accuracy of the fuzzy reasoning system on the basis of a multi-target population adaptive immune algorithm.The method provided by the invention can aim at large-scale and high-dimensionality sector operation data and center on airspace operation situation evaluation accuracy and interpretability, the multi-target immune optimization algorithm is used, and the airspace situation evaluation accuracy is optimized. In addition, when the immune algorithm is realized, the condition that the fuzzy matrix scale is in exponential growth in the process of processing high-dimensionality data is avoided, time complexity and space complexity needed by the algorithm are greatly reduced, and the convergence precision is improved.

Description

technical field [0001] The invention belongs to the technical field of airspace situation assessment and classification, and in particular relates to a fuzzy reasoning-based airspace operation situation assessment and classification method. Background technique [0002] With the rapid development of my country's air transport industry, the volume of aviation business is increasing day by day, the number of flights is increasing year by year, and the airspace operation situation is becoming more and more complicated. These situations make the workload of air traffic controllers and the risks of flight operations continuously increase, and thus become an important reason for flight delays and control accidents. [0003] In the current air traffic management system, a sector is the basic unit of airspace for controllers to command aircraft. The complexity of the sector's airspace operation situation is closely related to the workload of air traffic controllers. An overly comp...

AI Technical Summary

Problems solved by technology

Machine learning methods based on large batches of data samples often use the accuracy index as the primary criterion, while ignoring the interpretability of the model

On the other hand, the fuzzy reasoning system makes the established model have obvious physical meaning by establishing the knowledge expression form and reasoning mechanism, but the existing fuzzy reasoning systems with good interpretability are mostly based on expert knowledge, while Data-based fuzzy reasoning systems tend to improve in accuracy but lack in interpretability

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