Aero-Engine Adaptive Model Using Recursive Reduced Least Squares Support Vector Regression

Abstract:

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In consideration of the problem in traditional aero-engine adaptive model, a new algorithm was proposed based on Recursive Reduced Least Squares Support Vector Regression (RRLSSVR). Feature Selection of model input and flight envelope divided was needed before the model established, then adaptive model was developed in every small envelope. Finally, an adaptive model was applied to validate the effectiveness and feasibility of the proposed feature selection algorithm and sparse model using RRLSSVR.

Info:

Periodical:

Edited by:

Zhenyu Du and Bin Liu

Pages:

218-223

DOI:

10.4028/www.scientific.net/AMM.65.218

Citation:

L. P. Jiang "Aero-Engine Adaptive Model Using Recursive Reduced Least Squares Support Vector Regression", Applied Mechanics and Materials, Vol. 65, pp. 218-223, 2011

Online since:

June 2011

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Price:

$35.00

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