Research and evaluation of attribute reduction method based on flight parameter data

The landing phase of an aircraft is a frequent phase of a flight accident. To ensure the safety of aircraft landing is the focus of the aviation field and strive to overcome the problem. With the advent of the data age, landing safety research based on flight parameters is the research trend in the aviation field. At present, there are few studies on landing safety based on the data of flight parameters. In this paper, based on the neighborhood rough set, we use the forward greedy algorithm to compare the attribute reduction with the factor analysis, and use the random forest classification model to evaluate and analyze.