外れ値を含んだ小サンプルに対するMedian-Median Lineを用いたタグチT法

• 資料種別: 記事
• タイトル: 外れ値を含んだ小サンプルに対するMedian-Median Lineを用いたタグチT法
• 著者・編者: 西野 佳祐; 鈴木 新
• 著者標目: 西野 佳祐; 鈴木 新
• 並列タイトル等: Taguchi's T-method using Median-Median Line for Small Sample with Outliers
• タイトル（掲載誌）: 電気学会論文誌. D, 産業応用部門誌 = IEEJ transactions on industry applications
• 巻号年月日等（掲載誌）: 138(7):2018.7
• 掲載巻: 138
• 掲載号: 7
• 掲載ページ: 598-604
• 掲載年月日（W3CDTF）: 2018-07
• ISSN（掲載誌）: 0913-6339
• ISSN-L（掲載誌）: 0913-6339
• 出版事項（掲載誌）: 東京 : 電気学会
• 出版地（国名コード）: JP
• 本文の言語コード: jpn
• 件名標目: タグチT法; Median-Median Line; 重回帰分析; 外れ値; 小サンプル; Taguchi's T-method; median-median line; multiple regression analysis; outlier; small sample
• NDLC: ZN31
• 対象利用者: 一般
• 所蔵機関: 国立国会図書館
• 請求記号: Z16-1608
• 連携機関・データベース: 国立国会図書館 : 国立国会図書館雑誌記事索引; https://ndlsearch.ndl.go.jp
• 書誌ID（NDLBibID）: 029123734; http://id.ndl.go.jp/bib/029123734
• 整理区分コード: 632

• 要約等: <p>This paper proposes an improvement to Taguchi's T-method. In product development, it is difficult to gather sufficient samples at the beginning of the development process. Taguchi's T-method was proposed as a method for constructing an estimation model in such a situation. However, if an outlier exists in the training data, Taguchi's T-method cannot obtain a correct estimation model. This is because Taguchi's T-method uses the least squares. Therefore, in this paper, we propose an improved version of Taguchi's T-method that does not degrade the accuracy of estimation by using a median-median line even for small training samples with outliers. The Effectiveness of the proposed method is confirmed through experiments. We confirmed that the accuracy of the proposed method is superior to that of similar methods.</p>
• DOI: 10.1541/ieejias.138.598
• オンライン閲覧公開範囲: インターネット公開
• 連携機関・データベース: 科学技術振興機構 : J-STAGE; http://www.jstage.jst.go.jp

• 要約等: <p>This paper proposes an improvement to Taguchi's T-method. In product development, it is difficult to gather sufficient samples at the beginning of the development process. Taguchi's T-method was proposed as a method for constructing an estimation model in such a situation. However, if an outlier exists in the training data, Taguchi's T-method cannot obtain a correct estimation model. This is because Taguchi's T-method uses the least squares. Therefore, in this paper, we propose an improved version of Taguchi's T-method that does not degrade the accuracy of estimation by using a median-median line even for small training samples with outliers. The Effectiveness of the proposed method is confirmed through experiments. We confirmed that the accuracy of the proposed method is superior to that of similar methods.</p>
• DOI: 10.1541/ieejias.138.598; https://doi.org/10.1541/ieejias.138.598; 10.1002/ecj.12134; https://doi.org/10.1002/ecj.12134
• オンライン閲覧公開範囲: インターネット公開
• 関連情報（URI）: http://id.ndl.go.jp/bib/029123734; https://ndlsearch.ndl.go.jp/books/R000000004-I029123734; https://www.jstage.jst.go.jp/article/ieejias/138/7/138_598/_pdf; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fecj.12134; https://onlinelibrary.wiley.com/doi/pdf/10.1002/ecj.12134
• 参照: 機械設計における3D CADを中心とした1DCAE Virtual Engineering環境の構築; https://cir.nii.ac.jp/crid/1390295270228051712
• 参照: Predicting vehicle cost using the T-method; https://cir.nii.ac.jp/crid/1361981470282553472; Real time seam tracking system for automated fusion arc welding; https://cir.nii.ac.jp/crid/1362262944819907200; Inverse-model-based cuffless blood pressure estimation using a single photoplethysmography sensor; https://cir.nii.ac.jp/crid/1362825896039871872; Analysis and forecasts about the business model of M2M/IoT: ioT brings great change of the internet business; https://cir.nii.ac.jp/crid/1372260173459440000; Prediction accuracies of improved Taguchi's T methods compared to those of multiple regression analysis; https://cir.nii.ac.jp/crid/1372260173459440002; タグチのT法を用いた翌日最大電力需要予測; https://cir.nii.ac.jp/crid/1390001204609592064; 拡散反射・透過モードの近赤外分光法を用いる10g 未満のトマトの糖度の非破壊計測; https://cir.nii.ac.jp/crid/1390282679058032512; 蛍光指紋による食品の品質計測に関する研究; https://cir.nii.ac.jp/crid/1390282681386623744
• 連携機関・データベース: 国立情報学研究所 : CiNii Research; https://cir.nii.ac.jp/
• 提供元機関・データベース: Japan Link Center; https://japanlinkcenter.org/top; 雑誌記事索引データベース; https://ndlsearch.ndl.go.jp; Crossref; https://www.crossref.org; CiNii Articles
• 書誌ID（NDLBibID）: 029123734; http://id.ndl.go.jp/bib/029123734
• NII論文ID: 130007387179; 210000171398