Comparative Determination of Phosphate and Silicate Using Molybdenum Blue by Radial Basis Function and Feed-Forward Neural Networks Assisted by Principal Component Analysis

Afkhami, Abbas; Tarighat, Maryam Abbasi

doi:10.2116/analsci.24.779

Cited by 11 publications

(7 citation statements)

References 23 publications

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“…Also like as multiplicative calibration methods, all of component should be presented in calibration step. Also, designing architect of ANNs is a time-consuming process and is not easy to perform (Afkhami and Abbasi Tarighat 2008).…”

Section: Introductionmentioning

confidence: 99%

Simultaneous spectrophotometric determination of phosphate and silicate in different water and soil samples using chemometrics approach

Tarighat

2015

Int. J. Environ. Sci. Technol.

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Continuous wavelet transform together with zero-crossing technique was applied to the overlapping visible spectra, as a very simple and accurate method, for the simultaneous determination of phosphate and silicate without any prior separation steps. Daubechies-4, Symlet 8, and Meyer continuous wavelet transforms for signal treatments were found to be suitable. The calibration graphs for estimation of complexes were obtained by measuring the wavelet coefficients at zero-crossing points for silicomolybdenum blue and phosphomolybdenum blue.The constructed calibration functions were tested by analyzing the composition of the different binary mixtures. The experimental data were also analyzed using partial least squares and first-order derivative spectrophotometric method. The proposed method was validated by simultaneous determination of phosphate and silicate in different environmental waters and soil samples. The results of proposed method have been compared with those predicted by partial least squares and standard methods.

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Section: Introductionmentioning

confidence: 99%

Simultaneous spectrophotometric determination of phosphate and silicate in different water and soil samples using chemometrics approach

Tarighat

2015

Int. J. Environ. Sci. Technol.

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“…Unfortunately the derivative spectra are at least partially offset by degradation in signal‐to noise ratio that accompanies the obtaining of derivatives. Thus more sensitive methods for their simultaneous determination were of interest …”

Section: Introductionmentioning

confidence: 99%

“…Accurate and precise simultaneous determination of various metal ions using new, selective, highly sensitive and environmentally safe ligands in environmental, biological, pharmaceutical, food and milk samples is one of the main aims of our research. Thus we have carried out some studies on the applicability of new selective ligands for the spectrophotometric determination of metal ions . Recently, we have used bromopyrogallo red (BPR) at pH 9.40 for the simultaneous determination of ternary mixtures of Ca 2+ , Zn 2+ and Mg 2+ in different foodstuffs and pharmaceutical samples, by ratio spectra–continuous wavelet transformation .…”

Section: Introductionmentioning

confidence: 99%

“…Thus more sensitive methods for their simultaneous determination were of interest. 38 The chemometric methods are an effective way to analyse simultaneously several analytes. The main advantage of multicomponent analysis by chemometric methods (multivariate calibration and artificial neural networks in this work) is the rapid determination of the components in mixtures avoiding a prior separation, which is generally necessary owing to the overlapped signals.…”

Section: Introductionmentioning

confidence: 99%

“…Thus we have carried out some studies on the applicability of new selective ligands for the spectrophotometric determination of metal ions. 38,41,42 Recently, we have used bromopyrogallo red (BPR) at pH 9.40 for the simultaneous determination of ternary mixtures of Ca 2+ , Zn 2+ and Mg 2+ in different foodstuffs and pharmaceutical samples, by ratio spectra-continuous wavelet transformation. 53 We have further performed simultaneous determination of Co 2+ , Ni 2+ , Cu 2+ and Zn 2+ in different vegetables, foodstuffs and pharmaceutical product samples with a synthesized Schiff 3,6bis((aminoethyl)thio)pyridazine with ANNs.…”

Section: Introductionmentioning

confidence: 99%

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Spectrophotometric simultaneous determination of metal ions in cows' milk and vegetables with the aid of artificial neural networks using synthetic 2‐benzylspiro[isoindoline‐1,5′‐oxazolidine]‐2′,3,4′‐trione

Tarighat

2013

J Sci Food Agric

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The data obtained from synthetic mixtures of metal ions were processed by radial basis function networks (RBFNs) and back-propagation neural network. The optimal conditions of the neural networks were obtained by adjusting various parameters. Satisfactory precision and accuracy were obtained with all networks, although, because of surprisingly lower root mean square error (%) values, RBFNs were the preferred approach. The proposed approach was tested by analysing the composition of the different mixtures containing Zn(2+) , Mn(2+) and Fe(3+) . The proposed method was successfully applied to the simultaneous determination of Zn(2+) , Mn(2+) and Fe(3+) ions in milk and vegetable samples.

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Simultaneous determination of Mn2+ and Fe3+ as 4,4′[(4-cholorophenyl)methylene] bis(3-methyl-1-phenyl-1H-pyrazol-5-ol) complexes in some foods, vegetable and water samples by artificial neural networks

2013

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Comparative Determination of Phosphate and Silicate Using Molybdenum Blue by Radial Basis Function and Feed-Forward Neural Networks Assisted by Principal Component Analysis

Cited by 11 publications

References 23 publications

Simultaneous spectrophotometric determination of phosphate and silicate in different water and soil samples using chemometrics approach

Simultaneous spectrophotometric determination of phosphate and silicate in different water and soil samples using chemometrics approach

Spectrophotometric simultaneous determination of metal ions in cows' milk and vegetables with the aid of artificial neural networks using synthetic 2‐benzylspiro[isoindoline‐1,5′‐oxazolidine]‐2′,3,4′‐trione

Simultaneous determination of Mn2+ and Fe3+ as 4,4′[(4-cholorophenyl)methylene] bis(3-methyl-1-phenyl-1H-pyrazol-5-ol) complexes in some foods, vegetable and water samples by artificial neural networks

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