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

Content Provider	IEEE Xplore Digital Library
Author	Jianguo Cui Jiaojiao Hua Qingtian Wang Xiao Cui Haigang Liu Liying Jiang
Copyright Year	2014
Description	Author affiliation: Shenyang Aerodynamics Res. Inst., Shenyang, China (Xiao Cui) \|\| Shenyang Aircraft Design & Res. Inst., Shenyang, China (Haigang Liu) \|\| Sch. of Electron. & Inf. Eng., Shenyang Aerosp. Univ., Shenyang, China (Qingtian Wang) \|\| Sch. of Autom., Shenyang Aerosp. Univ., Shenyang, China (Jianguo Cui; Jiaojiao Hua; Liying Jiang)
Abstract	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.
Starting Page	5002
Ending Page	5006
File Size	267300
Page Count	5
File Format	PDF
ISBN	9781479937073
e-ISBN	9781479937080
DOI	10.1109/CCDC.2014.6853069
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-05-31
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Training Analytical models Aircraft Air Refrigerator Refrigerators Atmospheric modeling Neighborhood Rough Set Life Trend Analysis Market research SVM Aircraft
Content Type	Text
Resource Type	Article

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