DocumentCode :
2284944
Title :
Generalized PLS regression forecast modeling of warship equipment maintenance cost
Author :
Xie, Li ; Wei, Ru-xiang ; Jiang, Tie-Jun ; Zhang, Ping
Author_Institution :
Dept. of Equip. Econ. & Manage., Naval Univ. of Eng., Wuhan, China
fYear :
2009
fDate :
14-16 Sept. 2009
Firstpage :
607
Lastpage :
612
Abstract :
Aiming at the small sample, more latent variables and the multicollinearity among them in the forecast modeling of warship equipment maintenance cost, a method of improving the generalization ability of PLS was presented, which was on the base of the partial least squares(PLS) regression with shrink-magnifying, and extended the shrinking factor more by shrinking or magnifying the inputs of different sample to different extent, in which the cross training between training set and testing set was implemented. Further more, the foregoing modeling process was applied to the forecast modeling of warship equipment maintenance cost, in which the genetic algorithm was used to seek the best shrinking factor vector. Finally, by comparing with the PLS which distills one, two and three principal components and PLS with shrink-magnifying approach, the method presented in this paper demonstrates the best.
Keywords :
costing; least squares approximations; maintenance engineering; military vehicles; regression analysis; ships; foregoing modeling process; partial least squares regression; regression forecast modeling; warship equipment maintenance cost; Conference management; Costs; Economic forecasting; Engineering management; Genetic algorithms; Least squares methods; Management training; Predictive models; Temperature; Testing; PLS; forecast; maintenance cost; shrink-magnifying approach; shrinking factor; small sample; warship equipment;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Management Science and Engineering, 2009. ICMSE 2009. International Conference on
Conference_Location :
Moscow
Print_ISBN :
978-1-4244-3970-6
Electronic_ISBN :
978-1-4244-3971-3
Type :
conf
DOI :
10.1109/ICMSE.2009.5317378
Filename :
5317378
Link To Document :
بازگشت