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Ujita, Hiroshi*; Morimoto, Tatsuya*; Futagami, Satoshi; Yamano, Hidemasa; Kurisaka, Kenichi
Proceedings of PSAM 2023 Topical Conference AI & Risk Analysis for Probabilistic Safety/Security Assessment & Management, 8 Pages, 2023/10
This study is intended to develop PRA methodology using the AI technology. For this purpose, as a first step, the authors have been conducting a three-year program including the development of AI tools for automatic fault tree (FT) creation and automatic fault detection methodology for building reliability database. These AI tools are intended to enable any users to easily perform PRA with the same quality without user effect. For the automatic fault detection method, The AI tool is developed for extracting failure occurrence locations (system/equipment), failure modes, and causes from Japanese reliability databases of NUCIA(for light water reactors) and CORDS(for sodium-cooled fast reactors), and transforming them into a database using AI technologies.
Shu, Y.; Nakajima, Norihiro
Proceedings of 11th International Conference on Human-Computer Interaction (HCI International 2005) (CD-ROM), 9 Pages, 2005/07
To understand the behavior of NPP (nuclear power plant) under different operating environment, JAERI is carrying out full-scaled plant simulation. As one part of full scaled plant simulation, our ongoing work is to develop an information inference system to manage and interpret NPP quake-proof data. In this paper, we proposed a hybrid data mining approach, which integrates human cognitive model in a data mining loop. Rule-based mining control agent emulated human analysts directly interacts with the data miner, analyzing and verifying the output of data miner and controlling data mining process. In additional, artificial neural network method, which is adopted as a core component of the proposed hybrid data mining method, is evolved by adding the retraining facility and explaining function for handling complicated nuclear power plant quake-proof data. To demonstrate how the method can be used as a powerful tool for extracting information relevant to plant safety and reliability, plant quake-proof testing data have been applied to the inference system.
Shu, Y.; Nakajima, Norihiro
Proceedings of 1st International Workshop on Risk Management System with Intelligent Data Analysis (RMDA 2005) in Conjunction with 19th Annual Conference of the Japanese Society for Artificial Intelligence (JSAI 2005), p.35 - 44, 2005/06
This paper presents an intelligent information inference system based on a hybrid data mining approach, which integrates human cognitive model in a data mining loop. In the proposed system, the mining control agent emulated human analysts interacts directly with the data miner, analyzing and verifying the output of the data miner and controlling the data mining process. In additional, the neural network method, which is adopted as a core component of the proposed hybrid data mining method, is evolved by adding the retraining facility and explaining function for handling complicated quake-proof data of nuclear power plant. To demonstrate how the method can be used as a powerful tool for extracting information relevant to plant safety and reliability, plant quake-proof testing data have been applied to the inference system.
Ueshima, Yutaka
JAERI-Conf 2004-003, 62 Pages, 2004/03
JAERI-Conf-2004-003.pdf:6.14MB
no abstracts in English