Aiming at the problem of civil aviation flight conflict, combining case-based reasoning and artificial neural network in artificial intelligence, this paper puts forward two kinds of flight conflict relief models, and compares them. In this paper, ADS-B data is quantized according to the requirements of supervised learning for data format. On this basis, a case base is established to provide conflict relief instructions for the target case by calculating the case matching degree. This paper uses the processed data to train the artificial neural network, and uses the validation group data to verify the performance of the artificial neural network. By analyzing the fusion matrix and ROC curve, the classification accuracy and the sensitivity of the neural network are obtained. The results show that the two methods can give the release command of flight conflict, and the accuracy of artificial neural network is higher than that of case-based reasoning.


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    Title :

    Flight Conflict Relief Method Based on Artificial Neural Network and Case-Based Reasoning


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Yan, Liang (editor) / Duan, Haibin (editor) / Yu, Xiang (editor) / Zhaoning, Zhang (author) / Haiyang, Cui (author) / Qingyu, Meng (author)


    Publication date :

    2021-10-30


    Size :

    13 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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