Big data mining-based method for deleting flight parameter outliers in classified manner
A technology of flight parameters and big data, applied in data mining, electrical digital data processing, special data processing applications, etc., can solve the problems of complex calculation methods, long processing time, and large amount of calculation, so as to ensure accuracy and improve processing ability, the effect of meeting the needs of fault detection and normal processing of data
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[0028] In the present invention, the unmanned aerial vehicle adopts GPS to realize navigation and positioning, and the data recorder records the GPS signal and other sensor signals during the flight, and when the unmanned aerial vehicle stops flying, the GPS data recorded in the data recorder is read out , for post processing and analysis. However, in GPS signals, unreasonable outliers are often encountered. Their existence will adversely affect the analysis of aircraft flight performance and interfere with people's understanding of aircraft performance. Therefore, before processing GPS data, it is necessary to first Outliers are processed to meet the needs of subsequent analysis.
[0029] like figure 1 As shown, a kind of method that the present invention provides is based on big data mining classification and eliminates the method of flight parameter outlier, and the steps are as follows:
[0030] (1) The present invention first needs to train the RBN neural network as the...
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