A Neuro-Fuzzy System in Recognizing the Quality of Desiccated Coconut
Journal Title: Journal of Computing and Innovation - Year 2018, Vol 2, Issue 2
Abstract
This paper utilizes the Neuro-Fuzzy Designer tool in MATLAB to provide a more improved method of classifying the quality of the desiccated coconut (DCN) compared to the subjective assessment of visual examination. Having a more accurately identified quality DCN would increase its exportability in the global market. The One hundred (100) data sets used and normalized to be trained in ANFIS using the tool in Matlab, Eighty (80) percent for training and Twenty (20) percent for checking. From the experiments generated, it shows that the error gained during the training with an average error of 0.01434. The study shows that the application of an adaptive neuro-fuzzy inference system (ANFIS) for recognizing the quality of DCN was successfully explored.
Authors and Affiliations
Dindo C. Obediencia, Deborah Go Brosas, Ritchell Solitario Villafuerte
Keywords
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- EP ID EP460010
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