Development of artificial intelligence based systems for prediction of hydration characteristics of wheat

摘要: Display Omitted Three ANFIS models were developed to simulate hydration characteristics of wheat.The results compared with those ANN model.Both and able accurately predict characteristics.An simulation framework was preferred three frameworks. Hydration (moisture content, moisture ratio rate) wheat kernel during soaking process studied simulated. procedure performed at five different experimental water temperatures (30, 40, 50, 60 70 (°C)) respect time changes. samples modeled using one the most popular frameworks artificial intelligence, adaptive neuro-fuzzy inference system (ANFIS). A comparison also made between best model another well-known intelligence technique, neural network (ANN). The temperature used as input parameters rate taken output intelligent modeling To attain highest predictive ability, based on statistical coefficient determination, root mean square error relative deviation modulus. According results, although both characteristics, a simple structure (2-4-3) easier use than structures. surface plots illustrated that increasing increased content decreased ratio. Moreover, indicated in initial middle final phase procedure.