MODELLINGOF PEPPERCORN DRYING IN A SPOUT FLUID BED DRYER USING ANFIS ALGORITHM

This study investigated the application of an adaptive neuro-fuzzy inference system (ANFIS) to estimate the moisture ratio (MR) of peppercorn dried in a spout fluid bed dryer. The drying tests were conducted across three drying temperatures (70, 80 and 90 oC), at two of spout air flow rates (120 and 160 m3 /hr), and two bed heights (10 and 15 cm).The ANFIS models were trained with the hybrid algorithm under the same drying conditions. The results showed that an ANFIS model, with a bell shaped membership function, provided a high level of performance to calculate MR; as demonstrated by the highest R2 and lowest RMSE values, respectively. The capability of the ANFIS algorithm indicates an excellent ability to predict the drying characteristics of peppercorn in spout fluid bed dryer.