Prediction of activity coefficients at infinite dilution for organic solutes in ionic liquids by artificial neural network

Thermodynamic modeling of the KCl+formamide/glucose/proline+water ternary systems and activity coefficient prediction based on artificial neural network

“…Although, ANN is an applicable 58 tool to predict the properties of mixtures such as heat capacity, viscosity 59 and liquid-liquid extraction data [12,13]. However, a survey of literatures 60 shows that limited publications have been made on the use of ANN to 61 prediction for the activity coefficients [14][15][16][17]. However, it is essential 62 to use predicting technique such as ANN method when the common 63 methods are difficult to use to produce the experimental data.…”

The solubility of gases in ionic liquids

“…Advanced neural networks and machine learning techniques have also been applied to develop more robust models for solubility in ILs . Paduszyński has reviewed much of this and previous QSPR work and then used three different machine learning algorithms to develop new QSPR models for infinite dilution activity coefficients in ILs .…”

Prediction of osmotic coefficients for ionic liquids in various solvents with artificial neural network

“…The descriptors selected by MLR model were collected as input variables for the back propagation (BP) ANN model. A brief description of the ANN has already been given: 33 "A computational neural network consists of simple processing units called neurons. The strength of the neurons is determined by the weights (adjusted) that are first summed (combined) and then passed through a transfer function to produce the output for that neuron."…”

“…The fundamental theory and formulas of BP ANN and transfer functions can be found elsewhere. 33,34 The experimental data of the osmotic coefficients were the output variable. A three-layer BP ANN model usually used to deal with data was set up.…”