Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/75954

TítuloDesign of a decision support system for vegetarian food flavoring by using deep learning for the ageing society
Autor(es)Duangsuphasin, Akksatcha
Kengpol, Athakorn
Lima, Rui M.
Palavras-chaveageing society
decision support system
deep learning
multi-layer perceptron neural network
vegetarian food
Data2021
EditoraIEEE
CitaçãoA. Duangsuphasin, A. Kengpol and R. M. Lima, "Design of a Decision Support System for Vegetarian Food Flavoring by Using Deep Learning for the Ageing Society," 2021 Research, Invention, and Innovation Congress: Innovation Electricals and Electronics (RI2C), 2021, pp. 54-59, doi: 10.1109/RI2C51727.2021.9559831.
Resumo(s)The objective of this research is to design a decision support system (DSS) for vegetarian food flavoring by using deep learning methods, which is a multi-layer perceptron neural network model (MLPNN) for the ageing society. Vegetarian food is consisting mainly of fruits and vegetables can help reduce the risk of chronic diseases [10] such as high blood pressure, osteoarthritis, cataract, high cholesterol, and diabetes, there are top 5 of the elderly chronic diseases [21]. The results show which vegetarian food sets are appropriate for three ageing society groups with chronic diseases. The MLPNN can generate the accuracy of a trained dataset at 94.3% and a tested dataset at 85%. The benefit of this model is that the ageing people can choose the appropriate food menu according to their type of chronic diseases and the restaurant can produce the appropriate food menu for them.
TipoArtigo em ata de conferência
URIhttps://hdl.handle.net/1822/75954
ISBN9781665403009
DOI10.1109/RI2C51727.2021.9559831
Versão da editorahttps://ieeexplore.ieee.org/document/9559831
Arbitragem científicayes
AcessoAcesso restrito UMinho
Aparece nas coleções:CAlg - Artigos em livros de atas/Papers in proceedings

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