Akademik Veri Yönetim Sistemi
3rd International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2019, Ankara, Türkiye, 11 - 13 Ekim 2019, (Tam Metin Bildiri)
The electrochemistry applications were found a very welcoming in the analytical chemistry research among the world. Cyclic voltammetry approved acceptable results in competition with other analytical techniques such as HPLC and atomic absorption. The model solution of ferric cyanide was used for the detection of the redox reactions through cyclic voltammetry by a pencil graphite electrode. Various concentrations were made of that solution and have been analyzed. In addition of the application of cyclic voltammetry, artificial neural networks were applied in the studying of the behavior of chemical solutions. In this paper, Gradient Boosting Algorithm based machine learning has been applied to classify the voltammograms for determining the amount of potassium ferricyanide. Experiments are performed for two times by using 60% and 70% for training instances and 40% and 30% for testing instances respectively. Results are compared and discussed.