Mie scattering and microparticle-based characterization of heavy metal ions and classification by statistical inference methods.

ABSTRACT: A straightforward method for classifying heavy metal ions in water is proposed using statistical classification and clustering techniques from non-specific microparticle scattering data. A set of carboxylated polystyrene microparticles of sizes 0.91, 0.75 and 0.40 µm was mixed with the solutions of nine heavy metal ions and two control cations, and scattering measurements were collected at two angles optimized for scattering from non-aggregated and aggregated particles. Classification of these observations was conducted and compared among several machine learning techniques, including linear discriminant analysis, support vector machine analysis, K-means clustering and K-medians clustering. This study found the highest classification accuracy using the linear discriminant and support vecto

SUBMITTER: Klug KE 

PROVIDER: S-EPMC6549965 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature