Application of a new version of GA-RBF neural network for simultaneous spectrophotometric determination of Zn(II), Fe(II), Co(II) and Cu(II) in real samples: An exploratory study of their complexation abilities toward MTB.

The current study for the first time is devoted to the application of whole space genetic algorithm-radial basis function network (wsGA-RBFN) method to determine the content micro minerals of Zn(2+), Fe(2+), Co(2+) and Cu(2+) based on their complexes formation with methylthymol blue (MTB) spectrophotometrically in various pharmaceutical products and vegetable samples. Advantage of wsGA-RBFN compared to GA-RBFN is that centers can be located in any point of the samples spaces. Initially, the parameters controlling behavior of the system were investigated and optimum conditions were selected. Then, an exploratory analysis of complex systems was carried out by chemometrics approaches such as SVD, EFA, MCR-ALS and RAFA. The optimal parameters and conditions for constructing the proposed model of wsGA-RBFN were obtained from processing the data set of synthetic samples. Finally, wsGA-RBFN was successfully applied to the simultaneous determination of Zn(2+), Fe(2+), Co(2+) and Cu(2+) in tomato, white cabbage, red cabbage and lettuce and pharmaceutical products included iron, zinc, multi complete and B12 ampoule.