Exergy and Energy Analyses of Microwave Dryer for Cantaloupe Slice and Prediction of Thermodynamic Parameters Using ANN and ANFIS Algorithms

The study targeted towards drying of cantaloupe slices with various thicknesses in a microwave dryer. experiments were carried out at three powers 180, 360, and 540 W 2, 4, 6 mm for drying, the weight variations determined. Artificial neural networks (ANN) adaptive neuro-fuzzy inference systems (ANFIS) exploited to investigate energy exergy indices using afore-mentioned input parameters. results indicated that rise power decline sample thickness can significantly decrease specific consumption (SEC), loss, improvement potential (probability level 5%). mean SEC, efficiency, thermal dryer potential, sustainability index ranged 10.48–25.92 MJ/kg water, 16.11–47.24%, 2.65–11.24 7.02–36.46%, 12.36–42.70%, 11.25–38.89%, 3–12.2 1.88–10.83 1.12–1.63, respectively. Based on results, use higher thinner samples improve thermodynamic performance process. ANFIS model offers more accurate forecast compare ANN model.