包絡分析法に関わる実践的な学習ケース自動生成方式

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2016/03/01

タイトル(英語): A Generation Method of Case Study Data for DEA

著者名: 川口　英俊（東京工業大学大学院総合理工学研究科知能システム科学専攻），秋吉　政徳（神奈川大学工学部情報システム創成学科）

著者名(英語): Hidetoshi Kawaguchi (Department of Computational Intelligence and Systems Science., Interdisciplinary Graduate School of Science and Engineering., Tokyo Institute of Technology), Masanori Akiyoshi (Department of Information Systems Creation, Faculty of Engineering., Kanagawa University)

キーワード: ケース生成，学習コンテンツ，自動生成，シミュレータ学習，包絡分析法，進化的計算　　Case generation，Learning content，Auto generation，Simulator learning，Data envelopment analysis，evolutionary computation

要約(英語): This paper addresses a generation method on case data for DEA(Data Envelopment Analysis) study using “agents”. Books include some useful business scenario cases and data for a learner to try analysis based on his/her knowledge, however, they are in a sense limited examples to understand deeply the way of DEA. Since generation of various and appropriate cases takes much time and cost, there exists strong need to generate such cases automatically. We propose agent-based software framework to provide various example cases of business scenario and data, which includes self-validated functionalities. Decision tree analysis and evolutionary computational methods are used to construct our software framework, and experimental results show its effectiveness.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.136 No.3 （2016） 特集：機械学習が拓くシステムイノベーション

本誌掲載ページ: 318-326 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/136/3/136_318/_article/-char/ja/