SVMを用いた最適な学習変数予測手法
Method to predict process signals to learn using SVM
著者:
箕輪 弘嗣 Hirotsugu MINOWA 五福 明夫 Akio GOFUKU
発刊日:
公開日:
learning machineMonjuoptimizationplantSVM (Support Vector Machine)
概要
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 to select optimized variables to improve classification performance. The method can also be used for other supervised learning machine but Support Vector Machine. This paper repo rts that our method and result of evaluation experiment applied our method to output 40% of Monju.
