Figures & data
Figure 1 Experimental device where the volume of water measures 34 mm in height, 37 mm in width and 113 mm in length. The layer of date paste weights 20 g and was about 5 mm thick. Sugar concentration was measured at a distance of 20 mm from the date pulp layer surface and at a depth of 17 mm. (Figure provided in color online.)
Table 1 Main configuration parameters and their levels of neural networks used to predict D S , the sugar diffusion coefficient
Figure 2 The neural network topologies tested. (a) Neural network topologies I, and (b) Neural network topologies II.
Figure 3 Sugar concentrations obtained over time with (a) Menakher, (b) Lemsi, and (c) Alligue date varieties, at a distance of 20 mm from the date paste layer.
Table 2 Statistical analysis of the effect of temperature, variety and time on water sugar concentration
Table 3 Sugar diffusivity coefficient D S by variety, diffusion time and temperature
Table 4 Performances of various ANN configurations once trained with the data set, for the neural network topology I
Table 5 Performances of various ANN configurations once trained with the data set, for the neural network topology II
Figure 4 Correlation of desired versus neural network values of sugar diffusivity coefficient DS after testing the data set (a) for the ANN with a network topology II, 2 hidden layers, and four neurons in both the upper and lower hidden layers, and (b) for the ANN with network topology II, 2 hidden layers, and seven neurons in both the upper and lower hidden layers.
