This study aimed to develop Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Networks (ANNs) and predict the drying characteristics of potato, garlic and cantaloupe using convective hot air dryer. Drying experiments were conducted at the air temperatures (40, 50, 60 and 70 °C) and the air speeds (0.5, 1 and l.5 m/s). Drying properties was including of kinetic drying, effective moisture diffusivity ( ) and specific energy consumption ( ). The highest value of 9.76×10-9, 0.13×10−9 and 9.97×10-10 m2/s for potato, garlic, and cantaloupe, respectively. The lowest value of for potato, garlic, and cantaloupe were calculated 1.94×105, 4.52×105 and 2.12×105 kJ/kg, respectively. Results revealed that the ANFIS model had the high ability to predict the ( = 0.9900), ( = 0.9917), moisture ratio ( = 0.9974) and drying rate ( = 0.9901) during drying. So ANFIS method had the highe abilaty to evaluate all output as compared to ANNs method.
کلید واژگان :
Convective hot air drying, Drying kinetics, Effective moisture diffusivity, ANFIS, ANNs
