Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
225622 | Journal of Food Engineering | 2007 | 4 Pages |
Abstract
Prediction of oil yield from groundnut kernels in an hydraulic press subject to process variables such as moisture content, pressing time, applied pressure, heating time and heating temperature was investigated. The technique of artificial neural network (ANN) was applied using experimental data from a previous study. These data were then used for network training and testing. The back propagation technique was then used for establishing the network. The prediction accuracy of the neural network model was significantly improved compared to statistical model, (R = 0.99).
Related Topics
Physical Sciences and Engineering
Chemical Engineering
Chemical Engineering (General)
Authors
J.O. Olajide, J.C. Igbeka, T.J. Afolabi, O.A. Emiola,