SciELO - Scientific Electronic Library Online

 
vol.26 issue2OXIDATIVE STABILITY OF A COLOMBIAN CRIOLLO MANGO (Mangifera Indica) DRINK FORTIFIED WITH PEEL author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

  • On index processCited by Google
  • Have no similar articlesSimilars in SciELO
  • On index processSimilars in Google

Share


Vitae

Print version ISSN 0121-4004

Abstract

ROMERO BONILLA, Hugo; RAMIREZ-MORALES, Iván  and  ROMERO FLORES, Cinthia. AUTOMATIC CLASSIFICATION OF WATER SAMPLES USING AN OPTIMIZED SVM MODEL APPLIED TO CYCLIC VOLTAMMETRY SIGNALS. Vitae [online]. 2019, vol.26, n.2, pp.94-103. ISSN 0121-4004.  https://doi.org/10.17533/udea.vitae.v26n2a05.

Background:

concern about the quality of the water for human consumption has become widespread among the population. The taste and some problems associated with drinking water have been the cause of increased demand for bottled water. Due to this, day to day, a large number of companies has manifested their interest in the production of bottled water.

Objective:

to evaluate a novel automatic classification model that differentiates bottled water from tap water.

Methods:

the voltammetric technique consisted of three electrode setup. The output current has been considered for data analysis. From the results of grid search, six pairs of values were pre-selected for the parameters of σ and C whose results were similar. High values of accuracy, specificity and sensitivity were achieved in test dataset. The final decision was made after performing an ANOVA test of 100 repetitions of 5-fold cross-validation, 3000 models were evaluated with the parameter combinations described above for the SVM.

Results:

the oxidation and reduction peaks of the water samples have been observed to be prominent. Absolute values of current (I) increased in the case of public water samples, possibly due to the largest concentration of chloride ions which have higher contributions to the conductivity. 5-fold cross-validation test mean specificity resulted in C parameters values greater than 0 and between 0 and 30; a σ value greater than 10 and between 0 and 15 were found for tap water and bottled water, respectively. The combination (σ = 10, C = 30) presented best results in accuracy 0.988 ± 0.037, specificity 0.973 ± 0.085 and sensitivity 1 ± 0.09.

Conclusions:

results of this research work have shown that voltammograms for values of current increased for tap water samples, 9.94e-6μA, compared to 7.99e-6μA due to higher chloride ions concentration in the former. The parameters combination (σ = 10, C = 20) was selected as optimal parameters since there were no significant difference between this and the former.

Keywords : Electronic tongue; water quality; authenticity; machine learning; voltammetry.

        · abstract in Spanish     · text in English     · English ( pdf )