Author/Authors :
Isha, Azizul university of malaya - Faculty of Science - Department of Chemistry, Malaysia , Yusof, Nor Azah Universiti Putra Malaysia - Faculty of Science - Department of Chemistry, Malaysia , Ahmad, Musa Universiti Kebangsaan Malaysia - Faculty of Science and Technology - School of Chemical Sciences and Food Technology, Malaysia , Suhendra, Dedy Universiti Putra Malaysia - Faculty of Science - department of Chemistry, Malaysia , Yunus, Wan Md. Zin Wan Universiti Putra Malaysia - Faculty of Science - department of Chemistry, Malaysia , Zainal, Zulkarnain Universiti Putra Malaysia - Faculty of Science - Department of Chemistry, Malaysia
Abstract :
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 lirnited 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 backpropagation (BP) algorithm was employed in this study. The in put 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 10 000 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 Iimit of detection of the method was 8.4 mg/L.
Keywords :
Artificial neural network (ANN) , V(V) , fatty hydroxamic acid (FHA) , poly(methyl methacrylate) (PMMA)
