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- W2073156729 abstract "The study adopts Kansei Engineering and back-propagation neural network to forecast the student groups' Kansei evaluation regarding form design of perfume bottles, and the results demonstrates that the cognition are inconsistent between the students with a major in design and the others, with the only exception of the word pair of “Stylish-Classic”. The learning modules of back-propagation model must be inspected under the consistence of cognition. Consequently, the resulting accuracy rate merely reaches 20% due to the diverse cognition. For a better prediction performance, a greater amount of training and learning processes for various groups are required for the back-propagation model." @default.
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- W2073156729 date "2006-01-01" @default.
- W2073156729 modified "2023-10-18" @default.
- W2073156729 title "The Perception of Perfume Bottle's Image by Using Neural Network" @default.
- W2073156729 cites W2039040839 @default.
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- W2073156729 doi "https://doi.org/10.5100/jje.42.supplement_308" @default.
- W2073156729 hasPublicationYear "2006" @default.
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