Title :
Reliability prediction of engine systems using least square support vector machine
Author :
Zhang, Xinfeng ; Zhao, Yan ; Wang, Shengchang
Author_Institution :
Key Lab. of Automotive Transp. Safety Enhancement Technol. of the Minist. of Commun., Chang´´an Univ., Xi´´an, China
Abstract :
Accurate reliability prediction is important for assessing product performances and making maintenance plans. This research applies least square support vector machine (LSSVM) in reliability analysis of engine systems. To evaluate the predictive performance of LSSVM, a comparative study is made and the probability distribution of the forecasting outcomes is analyzed. The experiment simulation results show LSSVM can provide accurate predictions.
Keywords :
engines; least squares approximations; mechanical engineering computing; preventive maintenance; reliability; statistical distributions; support vector machines; LSSVM predictive performance; engine systems; least square support vector machines; maintenance planning; probability distribution; product performance assessment; reliability prediction; Educational institutions; Engines; Forecasting; Neural networks; Reliability engineering; Support vector machines; Learning method; Least square support vector machine; Reliability analysis;
Conference_Titel :
Electronics, Communications and Control (ICECC), 2011 International Conference on
Conference_Location :
Ningbo
Print_ISBN :
978-1-4577-0320-1
DOI :
10.1109/ICECC.2011.6067787
