Clustering Algorithms: an Application for Adsorption Kinetic Curves



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).


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Author Biography

Roberto Alejo, Tecnológico Nacional de México

 Full Professor

Division of Graduate Studies and Research

Campus: Technological Institute of Toluca

National Technology of Mexico


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