@article{oai:takushoku-u.repo.nii.ac.jp:00000193,
 author = {吉田, 瞬 and 若林, 祐次 and 小川, 毅彦 and 杉林, 俊雄 and Yoshida, Shun and Wakabayashi, Yuji and Ogawa, Takehiko and Sugibayashi, Toshio},
 issue = {1},
 journal = {拓殖大学理工学研究報告, Bulletin of science and engineering, Takushoku University},
 month = {Mar},
 note = {Surface texture of products needs the sensitive information for adding high-value to the products. It needs the technology method to convey sensitive information for designing and producing products. For this purpose, the method using a selforganizing map (an unsupervised learning neural network) was presented in this report. An aluminum alloy, shot blasted, was used for a specimen and its surface texture parameters were evaluated by self-organizing map. The surface texture parameters: arithmetic mean height; arithmetic mean roughness; glossiness; lightness are measured and the relation of these parameters was shown on the self-organizing map. This map showed clearly the relation of these parameters and it indicates that the self-organizing map can be used for the evaluation of aluminum alloy texture shot blasted.},
 pages = {3--10},
 title = {自己組織化マップによるアルミニウム合金のテクスチャ評価方法},
 volume = {16},
 year = {2019},
 yomi = {ヨシダ, シュン and ワカバヤシ, ユウジ and オガワ, タケヒコ and スギバヤシ, トシオ}
}