Click on “Download PDF” for the PDF version or on the title for the HTML version. If you are not an ASABE member or if your employer has not arranged for access to the full-text, Click here for options. Classification and Prediction of Goldfish Population and Water Quality Using a Potentiometric E-TonguePublished by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org Citation: Transactions of the ASABE. 60(4): 1037-1044. (doi: 10.13031/trans.9488) @2017Authors: Zhenbo Wei, Yu Zhao, Jun Wang Keywords: Classify, E-tongue, Goldfish water, Prediction. Abstract. In this study, a potentiometric E-tongue was employed for comprehensive evaluation of water quality and goldfish population with the help of pattern recognition methods. Four water quality parameters, i.e., pH and concentrations of dissolved oxygen (DO), nitrite (NO2-N), and ammonium (NH3-N), were tested by conventional analysis methods. The differences in water quality parameters between samples were revealed by two-way analysis of variance (ANOVA). The cultivation days and goldfish population were classified well by principal component analysis (PCA) and canonical discriminant analysis (CDA), and the distribution of each sample was clearer in CDA score plots than in PCA score plots. The cultivation days, goldfish population, and water parameters were predicted by a T-S fuzzy neural network (TSFNN) and back-propagation artificial neural network (BPANN). BPANN performed better than TSFNN in the prediction, and all fitting correlation coefficients were >0.90. The results indicated that the potentiometric E-tongue coupled with pattern recognition methods could be applied as a rapid method for the determination and evaluation of water quality and goldfish population. (Download PDF) (Export to EndNotes)
|