Optimized neural network model for a potato storage system
The postharvest storage process is a highly nonlinear one involving heat and mass transfer. The need to capture these nonlinearities demands the use of intelligent models. In this study a neural network model (for a potato storage process) was normalized using the standard deviation technique and...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Asian Research Publishing Network (ARPN)
2013
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/33583/ http://irep.iium.edu.my/33583/ http://irep.iium.edu.my/33583/1/OPTIMIZED_NEURAL_NETWORK_MODEL_FOR_A_POTATO.pdf |
| Summary: | The postharvest storage process is a highly nonlinear one involving heat and mass transfer. The need to capture
these nonlinearities demands the use of intelligent models. In this study a neural network model (for a potato storage
process) was normalized using the standard deviation technique and optimized through different combinations of network
configurations. The optimum model had a mean squared error (MSE) value of 0.8314 and a coefficient of determination
(R2) value of 0.7347. In comparison to a previous study, where the network was based on the min-max method of
normalization, the network provided a better representation of the storage process. The proposed model would be useful in
simulation processes involving intelligent controllers. |
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