Abstract
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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Iranian Food Science and Technology Research Journal
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
