日本原子力学会 年会・大会予稿集
2003 Fall Meeting
セッションID: E61
会議情報
動特性・総合解析・炉心管理システム
Development of HTTR Control Parameter Modeling using Recurrent Neural Network
*Muhammad SubektiTomio OhnoKazuhiko KudoKuniyoshi Takamatsu
著者情報
会議録・要旨集 フリー

詳細
抄録
HTTR is a graphite-moderated and helium gas cooled reactor with 30 MW in thermal power. To analyze the reactivity based on central control rod (C-CR) level, modeling system was created using neural network. Neural network is artificial intelligence that has been applied successfully to solve some difficult and diverse problems by its training with a popular error back-propagation algorithm. In this research, C-CR level modeling is to determine the reactivity value.
著者関連情報
© 2003 Atomic Energy Society of Japan
前の記事 次の記事
feedback
Top