Online Time-sequence Incremental and Decremental Least Squares Support Vector Machines for Engine Air-ratio Prediction

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	Online Time-sequence Incremental and Decremental Least Squares Support Vector Machines for Engine Air-ratio Prediction
	Wong, P. K.; Wong, H.C.; Vong, C.M.
	2012-02-01
Source Publication	International Journal of Engine Research (SCI-E)
ISSN	1468-0874
Pages	28-40
Abstract	Fuel efficiency and pollution reduction relate closely to air-ratio (i.e. lambda) control among all the engine control variables. Lambda indicates the amount that the actual available air-fuel ratio mixture differs from the stoichiometric air-fuel ratio of the fuel being used. Accurate lambda prediction is essential for effective lambda control. This paper employs an emerging online time-sequence incremental algorithm and proposes one novel online timesequence decremental algorithm based on least squares support vector machines (LS-SVMs) to continually update the built LS-SVM lambda function whenever a sample is added to, or removed from, the training dataset. Moreover, the online time-sequence algorithm can also significantly shorten the function updating time as compared with function retraining from scratch. In order to evaluate the effectiveness of this pair of online time-sequence algorithms, three lambda time series obtained from experiments under different operating conditions are employed. The prediction results of the online time-sequence algorithms over unseen cases are compared with those under classical LS-SVMs, typical decremental LS-SVMs, and neural networks. Experimental results show that the online time-sequence incremental and decremental LS-SVMs are superior to the other three typical methods.
Keyword	online least squares support vector machines time sequence air ratio lambda prediction
Language	英語English
The Source to Article	PB_Publication
PUB ID	7238
Document Type	Journal article
Collection	Faculty of Science and Technology
Corresponding Author	Wong, P. K.
Recommended Citation GB/T 7714	Wong, P. K.,Wong, H.C.,Vong, C.M.. Online Time-sequence Incremental and Decremental Least Squares Support Vector Machines for Engine Air-ratio Prediction[J]. International Journal of Engine Research (SCI-E), 2012, 28-40.
APA	Wong, P. K.., Wong, H.C.., & Vong, C.M. (2012). Online Time-sequence Incremental and Decremental Least Squares Support Vector Machines for Engine Air-ratio Prediction. International Journal of Engine Research (SCI-E), 28-40.
MLA	Wong, P. K.,et al."Online Time-sequence Incremental and Decremental Least Squares Support Vector Machines for Engine Air-ratio Prediction".International Journal of Engine Research (SCI-E) (2012):28-40.

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