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Mathematical and neural network modelling of terebinth fruit under fluidized bed drying

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Figure

Fig. 1. Fluidization curve of terebinth fruit and selected points for modellingA, B – fixed bed (0.81 and 1.38 m/s); C – semi fluid bed (2.08 m/s); D, E – fluid bed (3.35 and 4.43 m/s)
Table 1. Input parameters for artificial neural networks and their boundaries for prediction of effective moisture diffusivity, specific energy consumption and shrinkage of terebinth, drying rate and moisture ratio of terebinth
Fig. 3. Artificial neural net-work topology of DR and MR
Table 2. Best selected topologies including training algorithm, different layers and neurons for FFNN and CFNN for effective moisture diffusivity, shrinkage and specific energy consumption
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