第10回
SVMを用いた最適な学習変数予測手法
著者:
箕輪 弘嗣,Hirotsugu MINOWA,五福 明夫,Akio GOFUKU
発刊日:
公開日:
キーワードタグ:
Study of diagnostic system using machine learning to reduce the incidents of the plant is in advan because an accident causes large damage about human, economic and social loss. There is a proble m that 2 performances between a classification performance and generalization performance on the m hine diagnostic machine is exclusive. However, multi agent diagnostic system makes it possible to use a diagnostic machine specialized either performance by multi diagnostic machines can be used. We propose method t...
英字タイトル:
Method to predict process signals to learn using SVM
第10回
全体構成および蒸発器と過熱器の熱通過率の推定手法
著者:
五福 明夫,Akio GOFUKU,高橋 信,Makoto TAKAHASHI,長松 隆,Takashi NAGAMATSU,望月 弘保,Hiroyasu MOCHIZUKI,古澤 宏明,Hiroaki FURUSAWA,箕輪 弘嗣,Hirotsugu MINOWA
発刊日:
公開日:
キーワードタグ:
Abstract : A hybrid diagnostic agent system is developed to detect and identify early an anomaly that happens in the fast-breeder reactor “Monju”. The system outputs a diagnostic result by integrating the results of diagnosis by four diagnostic software agents. They are (1) an estimation agent of overall heat transfer coefficient of evaporator and superheater, (2) a state identification agent based on SVM (Support Vector Machine), (3) an anomaly detection agent by WT (Wavelet Transformation), and (4) a...
英字タイトル:
Whole System and Estimation Technique of Overall Heat Transfer Coefficient of Evaporator and Superheater