QSPR based ANFIS model for predicting standard molar chemical exergy of organic materials

Prediction of standard molar chemical exergy value for organic compounds is investigated using a quantitative structure-property relationship (QSPR) model combined with adaptive neuro-fuzzy inference system (ANFIS) strategy. Particle swarm optimization (PSO) method is also implemented to determine the optimal ANFIS structure. The proposed model uses three constitutional descriptors in model development's procedure. The QSPR-ANFIS model represents a great performance in prediction of the standard molar chemical exergy values with 0.9999, 44548, and 1.49 values for R-2, RMSE, and %AARD, respectively.