Discarded aluminum alloys are a form of recyclable metal materials, and their classification and identification are highly important. In this work, laser‐induced breakdown spectroscopy (LIBS) technique combined with principal component analysis (PCA) and least‐squares support‐vector machine (LSSVM) algorithm were used to classify and identify five types of aluminum alloys. Exploratory analysis of five types of aluminum alloys by PCA was performed to achieve better segregation. The identification accuracy of the support‐vector machine (SVM) and LSSVM for aluminum alloy were 98.33% and 100%, respectively. The higher identification success rate was obtained using the LSSVM algorithm. Therefore, the LIBS technique combined with the PCA and LSSVM algorithms represents an efficient approach to identifying aluminum alloys.
Because of the increasing demand and consumption of ginseng products, rapid and effective technologies verifying the authenticity of ginseng are strongly needed. The constituents of ginseng differ by category, geographical...
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