広島大学大学院教育学研究科紀要. 第二部, 文化教育開発関連領域 54号
2006-03-28 発行

布の手触り感とニューロネット

Neural Networks and Fabric Touch
木下 瑞穂
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抄録
By the hand sensory method Shin-gosen fabrics were classified into four groups (New Silky, Peach Skin, Rayon Dry and New Worsted). Neural networks on a personal computer were build by trainnng with the results of mechanical measurements. The results of sensory test were compared with the output of neural networks. The comparison were good in the case of Rayon Dry and Peach Skin type samples. In the case of New Silky and New Worsted type, the results of sensory test were rather dispersed and the dispersion patterns were fairly similar to those of the output figures of the networks. So we are able to expect neural networks to be effective tools to analyze the relation betweeen fabric touch and mechanical properties.
キーワード
手触り
官能検査
ニューロネット
新合繊
摩擦特性
Fablic Touch
Hand Sensory Evaluation
Neural Networks
Shin-gosen
Friction
SelfDOI