Prediction of normalized polarity parameter in binary mixed solvent systems using artificial neural networks

Artificial Neural Network Prediction of Normalized Polarity Parameter for Various Solvents with Diverse Chemical Structures

“…The overtraining causes the ANN to loose its prediction power. 37 Therefore, during training of the networks, it is desirable that iterations are stopped when overtraining begins. To control the overtraining of the network during the training procedure, the values of RMSET and RMSEV were calculated and recorded to monitor the extent of the learning in various iterations.…”

“…For these reason in recent years, ANNs have been used to a wide variety of chemical problems such as simulation of mass spectra, ion interaction chromatography, aqueous solubility and partition coefficient, simulation of nuclear magnetic resonance spectra, prediction of bioconcentration factor, solvent effects on reaction rate, prediction of normalized polarity parameter in mixed solvent systems and dissociation constant of acids. [23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39] The main aim of the present work is to develop a QSPR model based on molecular descriptors using ANN for modeling and prediction of E T N values for various solvents (including 216 solvents) with diverse chemical structures. In the first step, a MLR model was constructed.…”

“…If a network is left to train for too long, however, it will overtrain and will lose the ability to generalize. [34][35][36][37] Methods and Procedure Data set. As first step for developing the MLR and ANN models, the molecular descriptors should be generate.…”

“…There are no rigorous theoretical principles for choosing the proper network topology, so different structures were tested in order to obtain the optimal hidden neurons and training cycles. 37 Before training the network, the number of nodes in the hidden layer was optimized. In order to optimize the number of nodes in the hidden layer, several training sessions were conducted with different numbers of hidden nodes (from one to twelve).…”

Physical Chemistry Research Articles Published in the Bulletin of the Korean Chemical Society: 2003-2007

“…Solvent effects on rate constant of cycloaddition reaction of diethyl azodicarboxylate with ethyl vinyl ether are studied. 255 The complex solvent and the temperature dependence of the NMR shifts for the N-CH 2 protons in tris(N,N-diethyldithiocarbamato) iron(III) in various solvents are investigated to measure the effect of the solvent system on the environment of the transition metal ion. 256 Concentration and pH dependence of β-amyloid peptide conformations is studied.…”