Least-squares support vector machines for simultaneous voltammetric determination of lead and tin: A comparison between LS-SVM and PLS in voltammetric data

Ниази, Али; Sharifi, Sasan; Amjadi, Effat

doi:10.1016/j.jelechem.2008.06.021

Cited by 33 publications

(17 citation statements)

References 41 publications

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“…22,23 According to mobility data (Table 1), data classified to training and prediction sets according to KennardStones algorithm. The optimum number of factors to be included in the calibration model was determined by computing the prediction error sum of squares (PRESS) fro cross-validated models using a high number of factors (half of the number of total training set + 1).…”

Section: Partial Least Squares Analysismentioning

confidence: 99%

Quantitative Structure Property Relationships Study of Mobility of Some Benzoaromatic Carboxylate Derivatives by Partial Least Squares and Least-square Support Vector Machine

Hamzehali¹,

Ниази²

2013

Orientjchem.

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A quantitative structure-property relationship (QSPR) study is suggested for the prediction of mobilities (m) of benzoaromatic carboxylates. Ab initio theory was used to calculate some quantum chemical descriptors including electrostatic potentials and local charges at each atom, HOMO and LUMO energies, etc. Also, Dragon software was used to calculate some descriptors such as WIHM and GETAWAY. Modeling of the mobility of benzoaromatic carboxylate derivatives as a function of molecular structures was established by means of the least squares support vector machines (LS-SVM). This model was applied for the prediction of the mobility of benzoaromatic carboxylates, which were not in the modeling procedure. The resulted model showed high prediction ability with root mean square error of prediction (RMSEP) of 3.734, 1.931 and 0.018 for MLR, PLS and LS-SVM, respectively. Results have shown that the introduction of LS-SVM for quantum chemical, WIHM and GETAWAY descriptors drastically enhances the ability of prediction in QSAR studies superior to multiple linear regression (MLR) and partial least squares (PLS).

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Section: Partial Least Squares Analysismentioning

confidence: 99%

Quantitative Structure Property Relationships Study of Mobility of Some Benzoaromatic Carboxylate Derivatives by Partial Least Squares and Least-square Support Vector Machine

Hamzehali¹,

Ниази²

2013

Orientjchem.

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“…However, the kernel function more used is the radial basis function (RBF), exp À jjx i À x j jj 2 =2r 2 , a simple Gaussian function, and polynomial functions x i ; x j d , where r 2 is the width of the Gaussian function and d is the polynomial degree, which should be optimized by the user, to obtain the support vector. For r of the RBF kernel and d of the polynomial kernel it should be stressed that it is very important to do a careful model selection of the tuning parameters, in combination with the regularization constant c, in order to achieve a good generalization model [46]. The free LS-SVM toolbox (LS-SVM V-1.5, Suykens, Leuven, Belgium) was used with MATLAB Version 7.6 to derive all the LS-SVM models [45].…”

Section: Descriptors Calculationmentioning

confidence: 99%

Docking, molecular dynamics simulation studies, and structure-based QSAR model on cytochrome P450 2A6 inhibitors

2011

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In this study, we used molecular docking and molecular dynamics (MD) simulation studies to analyze the interactions of a series of naphthalene and non-naphthalene derivatives (n = 38) as potent inhibitors of cytochrome P450 2A6 (CYP2A6) and to construct a structure-based quantitative structure activity relationship (QSAR) model. A 6000 ps MD simulation in a cubic water box were employed to build 3D structure of the CYP2A6 in a water environment. After reaching the equilibrium, the most potent inhibitor (2-bromonaphthalene) was docked into the CYP2A6 to realize the binding site of the enzyme. The docking analysis showed that p-p interaction of the inhibitors with four phenylalanine residues at positions of 107, 111, 118, and 480 plays an important role in the activities of the inhibitors. Then, an additional 6000 ps MD simulation was performed on the complex of the CYP2A6-2-bromonaphthalene to explore the effect of the inhibitor on the stability of the protein-inhibitor complex. Radius of gyration values for CYP2A6 and CYP2A6-2-bromonaphthalene complex were 2.23 ± 0.01 and 2.21 ± 0.01 nm, respectively, which revealed that the structure of the CYP2A6 in the presence of 2-bromonaphthalene has not changed. Finally, all the inhibitors docked into the enzyme and the docked configuration of the inhibitors with the lowest free energy was used to calculate the most feasible descriptors. The selected descriptors were related to the inhibitory activities using multiple linear regression (MLR) and least squares support vector regression (LS-SVR) models. The Q 2 values for MLR and LS-SVR were 0.695 and 0.728, respectively.

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“…When conducting the LS-SVM simulation, selection of the kernel function is a crucial problem need to be solved [23,24]. In principle, the LS-SVM always fits a linear relation (y = ωx + b) between the regression x and the dependent variable y.…”

Section: Kernel Function Selectionmentioning

confidence: 99%

Effect of assembly error of bipolar plate on the contact pressure distribution and stress failure of membrane electrode assembly in proton exchange membrane fuel cell

Liu

Peng

Lai

2010

Journal of Power Sources

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Least-squares support vector machines for simultaneous voltammetric determination of lead and tin: A comparison between LS-SVM and PLS in voltammetric data

Cited by 33 publications

References 41 publications

Quantitative Structure Property Relationships Study of Mobility of Some Benzoaromatic Carboxylate Derivatives by Partial Least Squares and Least-square Support Vector Machine

Quantitative Structure Property Relationships Study of Mobility of Some Benzoaromatic Carboxylate Derivatives by Partial Least Squares and Least-square Support Vector Machine

Docking, molecular dynamics simulation studies, and structure-based QSAR model on cytochrome P450 2A6 inhibitors

Effect of assembly error of bipolar plate on the contact pressure distribution and stress failure of membrane electrode assembly in proton exchange membrane fuel cell

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