K-Means Clustering Applied to Adsorption of Heavy Metals
Arjun Oliveira
Corresponding
National University of Singapore
Kamrul Wang
Bangladesh University of Engineering and Technology
Abstract
The economic importance of thermal power plants justifies a careful examination of adsorption of heavy metals. Field measurements from thermal power plants provide the input data for the analysis, which relies on k-means clustering. The settlement is limited to less than 5 millimetres under the design load. The insights gained may inform policy as well as engineering practice.
Keywords:
adsorption of heavy metalsk-means clusteringgenetic algorithmartificial neural networkinduction motorwater resources management
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