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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2021, Vol. 42 ›› Issue (8): 525800-525800.doi: 10.7527/S1000-6893.2021.25800

• Article • Previous Articles     Next Articles

Construction method of flight data mining model based on LSTM

WANG Zhigang, WANG Yeguang, YANG Ning, MI Yufeng, QU Xiaolei   

  1. AVIC Shenyang Aircraft Design and Research Institute, Shenyang 110035, China
  • Received:2021-04-15 Revised:2021-05-08 Published:2021-05-26
  • Supported by:
    National Project

Abstract: Based on Long Short Time Memory (LSTM) model, a method of constructing the flight history data mining model, which can automatically extract the valuable target data in flight data is proposed. First, to obtain the data to be detected by sliding window method. Then, to train the pre-made training sample data into the constructed LSTM model to get the data mining model. And finally, to model the pattern recognition of the detected data into the trained LSTM model. The results show that this method of constructing flight data mining model has high generalization degree, and can be used to mine different kinds of target data. The result also show that the recognition rate has high engineering application value.

Key words: LSTM, flight history data, data mining, pattern recognition, model construction

CLC Number: