Development of Cognitive Methodology based Data Analysis System

Chiaki Kino (), Yoshio Suzuki (), Noriyuki Kushida (), Akemi Nishida (), Sachiko Hayashi () and Norihiro Nakajima ()
Additional contact information
Chiaki Kino: Japan Atomic Energy Agency
Yoshio Suzuki: Japan Atomic Energy Agency
Noriyuki Kushida: Japan Atomic Energy Agency
Akemi Nishida: Japan Atomic Energy Agency
Sachiko Hayashi: Japan Atomic Energy Agency
Norihiro Nakajima: Japan Atomic Energy Agency

A chapter in High Performance Computing on Vector Systems 2008, 2009, pp 89-97 from Springer

Abstract: Abstract Nuclear engineering is an integrated engineering field of mechanical and civil engineering, partical physics as well as fluid and thermodynamics. Researchers in nuclear engineering fields need to treat extensive physical and engineering information obtained through theories, simulations, experiments and observations in order to promote a nuclear technology safely and securely. To meet the need, the Cognitive methodology-based Data Analysis System (CDAS) which equips information technologies that have recognition abilities similar to those of humans has been developed. The system supports researchers to analyze numerical simulation data by using extensive scientific knowledge. In the present study, information technology is developed for performing these processes and for configuring systems. In addition, a prototype system has been constructed using this information technology and an application experiment using a virtual plant vibration simulator has been performed to confirm the implementability of the system. The results obtained demonstrate that the CDAS enables researchers to dynamically set essential functions for evaluation and judgment, enabling them to readily extract meaningful and reliable information from large-scale data of up to 1 TB.

Date: 2009
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-540-85869-0_9

Ordering information: This item can be ordered from
http://www.springer.com/9783540858690

DOI: 10.1007/978-3-540-85869-0_9

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().