Artificial Neural Network Prediction of Viscosity Index and Specific Heat Capacity of Grease Lubricant produced from Selected Oil Seeds and Blends

摘要

Artificial neural network modeling was employed to predict Viscosity index and specific heat capacity of grease lubricant produced from selected oil seeds. These oils were extracted from their seeds using solven t extraction method and characterized in Food Science Laboratory, University of Agriculture, Makurdi, Benue State of Nigeria. The neural model was developed to capture two groups of inputs data namely; materials formulation, and operating conditions. The effects of material formulation were represented by 5 parameters while the operation conditions were represented by 4 parameters. The neural network architecture BR 09 [5 -4- 3-2] 4 2 fitted the input/output relationship for the prediction of viscosity index and specific heat capacity; after series of training using different training algorithms. There were visual checking of predicted and experimental viscosity index and specific heat capacity which confirm that the artificial neural network model was successful in modeling the viscosity index and specific heat capacity.