A novel SMOreg algorithm based on instance cloned and its research on spectral modeling for hydromica in uranium deposit

J. Wu, Z. H. Cai, Z. C. Gao, C. Yu

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Hydromica is a typical alteration mineral in granite-type uranium deposit, and also an important indication of uranium. The amount of hydromica to some extent reflects the strength of hydromicasization in uranium deposit. Because of the bad performance of the traditional modelling methods in prediction, in the present paper, the authors' adopt SMOreg in the spectral modelling for hydromica, and validate its effectiveness. The authors' also propose a novel method called ICSMOreg. In this method the authors' employ instance cloned method to learn the samples selected by having a strong affinity with the test sets, and then get the new samples into SMOreg to build the spectral model. Finally, we experimentally compare ICSMOreg with SMOreg, artificial neural network, model tree and the common modelling methods like linear regression, multiple linear regression. The result shows that the new method improves the accuracy of prediction, and also reduces the negative impact of noise.
Original languageEnglish
Pages (from-to)1678-1682
Number of pages5
JournalGuang pu xue yu guang pu fen xi= Guang pu
Volume31
Issue number6
Publication statusPublished - 2011
Externally publishedYes

Fingerprint Dive into the research topics of 'A novel SMOreg algorithm based on instance cloned and its research on spectral modeling for hydromica in uranium deposit'. Together they form a unique fingerprint.

Cite this