Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN) for Predicting the Kinematic Viscosity and Density of Biodiesel-Petroleum Diesel Blends

摘要

Biodiesel is considered as an alternative source of energy obtained from renewable materials. In the present paper, the investigation of the applicability of adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) approaches for modeling the biodiesel blends property including kinematic viscosity and density at various temperatures and the volume fractions of biodiesel. An experimental database of kinematic viscosity and density of biodiesel blends (biodiesel blend with diesel fuel) were used for developing of models, where the input variables in the network were the temperature and volume fractions of biodiesel. The model results were compared with experimental ones for determining the accuracy of the models. The developed models produced idealized results and were found to be useful for predicting the kinematic viscosity and density of biodiesel blends with a limited number of available data. Moreover, the results suggest that the ANFIS approach can be used successfully for predicting the kinematic viscosity and density of biodiesel blends at various volume fractions and temperature compared to another models.