Article ID Journal Published Year Pages File Type
4754898 New Biotechnology 2017 26 Pages PDF
Abstract
A methodology based on artificial neural networks (ANNs) and differential evolution (DE), specifically a neuro-evolutionary approach, was applied to model germination rates, dry biomass and root/stem length and proving the robustness of the experimental data. The errors associated with all four variables are small and the correlation coefficients higher than 0.98, which indicate that the selected models can efficiently predict the experimental data.
Related Topics
Physical Sciences and Engineering Chemical Engineering Bioengineering
Authors
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