Azizul Isha, Nor Azah Yusof, Musa Ahmad, Dedy Suhendra, Wan Md. Zin Wan Yunus and Zulkarnain Zaina
Pertanika Journal of Tropical Agricultural Science, Volume 15, Issue 2, July 2007
Keywords: Artificial neural network (ANN), V(V), fatty hydroxamic acid (FHA), poly(methylmethacrylate) (PMMA)
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An artificial neural network (ANN) was applied for the determination of V(V) based on immobilized fatty hydroxamic acid (FHA) in poly(methyl methacrylate) (PMMA). Spectra obtained from the V(V)-FHA complex at single wavelengths was used as the input data for the ANN. The V(V)-FHA complex shows a limited linear dynamic range of V(V) concentration of 10 - 100 mg/ L. After training with ANN, the linear dynamic range was extended with low calibration error. A three layer feed forward neural network using back-propagation (BP) algorithm was employed in this study. The input layer consisted of single neurons, 30 neurons in hidden a layer and one output neuron was found appropriate for the multivariate calibration used. The network were trained up to 10000 epochs with 0.003 % learning rate. This reagent also provided a good analytical performance with reproducibility characters of the method yielding relative standard deviation (RSD) of 9.29% and 7.09% for V(V) at concentrations of 50 mg/ L and 200 mg/ L, respectively. The limit of detection of the method was 8.4 mg/ L.
ISSN 1511-3701
e-ISSN 2231-8542