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Viscosity of mixed oil is an important parameter which is required in transportation and production processes of mixed crude oils. There is no universal and general model for prediction of viscosity of mixed oils at different conditions. Hence, developing simple, accurate and general models for prediction of mixed oil viscosity is of great importance. In this work three computer based models named MLP-NN, PSO-RBF and Hybrid-ANFIS were developed for prediction of viscosity of mixed oils. A number of 513 experimental data covering wide ranges of influencing parameters were utilized to develop the models. The accuracy of predictions of the developed models was examined by using different... 

Viscosity of mixtures of biodiesels (admixtures) and mixtures of biodiesel/diesel (blends) is a important parameter for determining their combustion behavior. There is no universal and general model for prediction of viscosity of these systems at different conditions. Hence, developing simple, accurate, and general models for prediction of viscosity of these systems is of great importance. In this work, three computer-based models named multilayer perceptron neural network (MLP-NN), radial basis function optimized by particle swarm optimization (PSO-RBF), and adaptive neuro fuzzy inference system optimized by hybrid approach (Hybrid-ANFIS) were developed for prediction of viscosity of blends...