A Self-emendation Algorithm for Flight Data based on Interrelated Parameters

Put forward self-emendation algorithm for flight data.The algorithm constructs multi-rank data matrix with interrelated parameters.Firstly,the algorithm estimate missing data in data matrix by Recvrrent Neuron Network(RNN),searchs similar models in history data matrix,emendates the results from RNN based on similar coefficient.Theoretical analysis shows that the algorithm has optimal time complexities in the worst,best cases.The simulation result reveals that compared with results with RNN,self-emendation algorithm not only has smaller error,but also has higher accuracy.