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- W2370747810 abstract "A least squares-support vector machine (LS-SVM)-based method was proposed to construct functional link artificial neural networks (FLANN), which was used to correct non-linearity of thermocouple sensor based on the principle of positive feedback. The principle and algorithms of LS-SVM-based FLANN were discussed and the non-linearity compensation model for thermocouple was given. Compared with traditional BP-based FLANN, the new LS-SVM-based FLANN had more advantages: ① the LS-SVM solution solved a set of linear equations instead of an iterative problem, so it was faster in speed; ② FLANN, which was uniquely obtained due to the global maximum in the whole training process, was higher in accuracy. Finally, Platinum-Rhodium 30-Platinum-Rhodium 6 thermocouple (B) sensor was taken as an example to non-linearity compensation, and experimental results show the presented method is effective." @default.
- W2370747810 created "2016-06-24" @default.
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- W2370747810 date "2007-01-01" @default.
- W2370747810 modified "2023-09-26" @default.
- W2370747810 title "Rectification of Non-Linearity for Thermocouple Based on FLANN Constructed by LS-SVM" @default.
- W2370747810 hasPublicationYear "2007" @default.
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