SVMおよびPCAを用いた運転ノウハウの抽出による上水送水系の運転支援システム

カテゴリ: 論文誌(論文単位)

グループ名: 【D】産業応用部門

発行日: 2012/10/01

タイトル(英語): Knowledge Acquisition from In-Operation Data for Water Supply System by Using SVM and PCA

著者名: 松木　洋（横浜国立大学），藤本　康孝（横浜国立大学）

著者名(英語): Hiroshi Matsuki (Yokohama National University), Yasutaka Fujimoto (Yokohama National University)

キーワード: 上水送水系，運転計画，サポートベクトルマシン，主成分分析　　water plant，operation planning，support vector machine，principal component analysis

要約(英語): This study aims to replicate the operations performed by an experienced operator of a water supply system. Steering groups of water supply systems face problems because of the decreasing number of experienced operators. Without the skill of experienced operators, it is difficult to carry out safe and stable operations. Regression analysis was adapted in this study to replicate the operations performed by an experienced operator. To resolve the nonlinear regression problems of knowledge acquisition and decreasing number of experienced operators, a support vector machine (SVM) was used. For knowledge acquisition from sensor data, data mining and principal component analysis (PCA) were used. Experimental results showed that when the proposed method was used, the average of the root mean square values of the water level improved by 29.8% as compared to that obtained by the conventional method. Thus, we confirmed that the proposed method can acquire operation knowledge from experienced operators and use it to prepare an operation plan. This method is expected to compensate for the decrease in the number of experienced operators.

本誌: 電気学会論文誌D（産業応用部門誌） Vol.132 No.10 （2012）

本誌掲載ページ: 990-996 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/ieejias/132/10/132_990/_article/-char/ja/