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

Investigating the discrimination potential of linear and nonlinear spectral multivariate calibrations for analysis of phenolic compounds in their binary and ternary mixtures and calculation pKa values

“…But the problem which restricted the application of linear methods in multi-component determination is the intrinsic non-linearity is observed in the system. The artificial neural networks (ANNs) typically the multi-layer feed forward neural networks (FFNNs) or multi-layer perceptron, with the back-propagation learning algorithm are very efficient chemometrics approaches as modelling tool to provide non-linear relations [25][26][27]. This is mainly due to the increases in computing power, which makes it possible to perform calculations on a personal computer that previously required a very powerful mainframe.…”

Sulfonated nanohydroxyapatite functionalized with 2-aminoethyl dihydrogen phosphate (HAP@AEPH2-SO3H) as a new recyclable and eco-friendly catalyst for rapid one-pot synthesis of 4,4′-(aryl methylene)bis(3-methyl-1H-pyrazol-5-ol)s

“…In [11][12][13][14]. It is observed that solvent-free conditions gave the best result for this transformation.…”

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 stability constants of complexes in the current study were derived using RAFA method. In the last few decades, artificial neural networks, typically radial basis function network, have become efficient models to provide non-linear relations especially in the multi component quantitative mixture from different types of data set [36][37][38]. Genetic algorithm is one of the most common ways in optimizing the architecture, the centers and the width of RBFN.…”