ANFIS modeling of ionic liquids densities

Abstract The aim of this study is to implement an accurate model for prediction of density of ionic liquids at various temperatures based on an extensive data base gathered from literature published works. The data base includes 602 density data points of 146 ionic liquids at various temperatures. The developed model is based on adaptive neuro-fuzzy inference system (ANFIS) algorithms. The predictions of the developed model were analyzed by various methods including both statistical and graphical approaches. The predictions of the developed model were compared with outcomes of literature correlations for predictions of density of pure liquids. Results show that the developed model accurately predicts the experimental data with an overall R2 and AARD% values of 0.985 and 0.657%, respectively. Moreover, the developed model effectively outperforms literature correlations and presents more accurate and reliable predictions.

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