| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 720814 | IFAC Proceedings Volumes | 2009 | 6 Pages |
Abstract
The visible and near infrared reflectance spectra of rock samples from a zinc-copper mine are analyzed by data-based multivariate methods. The effect of data preprocessing to the feature extraction of the spectra is discussed. Based on the measurement data, a classification model is developed to automatically separate gangue rocks from ore. The model is detected to classify rock samples with good accuracy and robustness.
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