investigation of malting process using artificial neural network

malting is a complex biotechnological process that includes steeping; germination and drying of cereal grains under controlled conditions of temperature and humidity. in this research malting process parameters were predict by modular neural network with different activation function included, logsig-logsig, tanh-tanh, logsigtanh, logsig-identity and tanh-identity. steeping time (x1) and germination time (x2) were used as input parameters and hot water extract (y1), malting yield (y2) and enzyme activity (β-gluconase) (y3) were selected as output parameters. the results showed that using perceptron neural network with tanh-identity activation function had the best result among all of activation functions to predict effective parameters of malting process. as well, this network was able to predict hot water extract, malting yield and enzyme activity (β - gluconase) with r2 value of 1, 0.984 and 0.995, respectively.