Clustering Algorithms: an Application for Adsorption Kinetic Curves
Keywords:Data Mining, chemistry, Artificial Intelligence
Clustering algorithms have been used in different areas of knowledge with different goals such as noise detection, outliers, and descriptive tasks. The adsorption kinetics is a curve that describes the rate retention to the adsorbate on the adsorbent at time, which is represents as a two-dimensional graph. In this paper, we present a computational application to determine the experimental conditions that influence when equilibrium point is reached into adsorption kinetics curve using the K-means clustering algorithm and, parallel coordinate’s concept, in order to prove our method we used adsorption kinetic curves Q-PVA . Results obtained were compared with two designs of experiments (three-stage nested design and hierarchical design with crossed factors).