Paper Title:
Aero-Engine Adaptive Model Using Recursive Reduced Least Squares Support Vector Regression
  Abstract

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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