Trend Prediction Based on Data Center of Aerospace Test Data

With the intensification of space tasks and the characteristics of long duration and high frequency of launch vehicle tests, a large number of aerospace test data have been generated and stored. In the past, aerospace test data analysis was processed through the analysis programs coded, which had the shortcomings of insufficient mining of data rules due to simple analysis, with high ability threshold of data analysis algorithm and coding. In view of the above pain points, visual deep mining research based on the self-built aerospace test data center is carried out, and the design and implementation of trend prediction model obtains the trend prediction results, which are in good agreement with the actual trend of more than 90%.