Indexed by:Journal Article

Date of Publication:2013-01-01

Journal:ICIC Express Letters

Volume:7

Issue:11

Page Number:3157-3162

ISSN:1881803X

Abstract:The dry point of aviation kerosene is an important quality parameter in the atmospheric distillation column; however, it cannot be measured by hardware sensors directly. A novel selective ensemble compressive sensing LS-SVM (SECSLS-SVM) algorithm based on noise injected is proposed to estimate the dry point of aviation kerosene. At first, the gauss noises are injected to the original training set to generate new training set. Then, the LS-SVM algorithm is used to construct the sub-models in the ensemble model. At last, the ensemble model is obtained by compressive sensing using orthogonal matching pursuit algorithm. The simulation results show that the soft sensor modeling based on the proposed method has better predictive performance. ? 2013 ISSN 1881-803X.