Life trend analysis of aircraft air refrigerator based on neighborhood rough set and SVM

For the life of the aircraft air refrigerator trend analysis problems, this paper proposed the research method that based on a combination of SVM and neighborhood rough set attribute reduction. First, to find out the core factors which are the most significant ones affecting the life of the aircraft air refrigerator, the original information of the data is mined by the attribute reduction algorithm. Then place the core factors as the input vectors of SVM for trend analysis. In the life trend analysis of a certain type of aircraft air refrigerator application shows that, compared to the traditional SVM model according to the experience to select the input vectors, the new model greatly improved the analysis precision and had good application value and prospect.