High performance prediction of molten steel temperature through gray-box model

Toshinori Okura; Manabu Kano; Shinji Hasebe; Hiroshi Kitada; Noboru Murata

High performance prediction of molten steel temperature through gray-box model

Toshinori Okura, Manabu Kano, Shinji Hasebe, Hiroshi Kitada, Noboru Murata

School of Advanced Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	English
Title of host publication	Computing and Systems Technology Division - Core Programming Topic at the 2011 AIChE Annual Meeting
Publisher	AIChE
Pages	1153-1154
Number of pages	2
ISBN (Print)	9781618397317
Publication status	Published - 2011
Event	Computing and Systems Technology Division - Core Programming Topic at the 2011 AIChE Annual Meeting - Minneapolis, United States Duration: 2011 Oct 16 → 2011 Oct 21

Publication series

Name	Computing and Systems Technology Division - Core Programming Topic at the 2011 AIChE Annual Meeting
Volume	2

Other

Other	Computing and Systems Technology Division - Core Programming Topic at the 2011 AIChE Annual Meeting
Country/Territory	United States
City	Minneapolis
Period	11/10/16 → 11/10/21

ASJC Scopus subject areas

Chemical Health and Safety
Safety, Risk, Reliability and Quality
Safety Research

Cite this

Okura, T., Kano, M., Hasebe, S., Kitada, H., & Murata, N. (2011). High performance prediction of molten steel temperature through gray-box model. In Computing and Systems Technology Division - Core Programming Topic at the 2011 AIChE Annual Meeting (pp. 1153-1154). (Computing and Systems Technology Division - Core Programming Topic at the 2011 AIChE Annual Meeting; Vol. 2). AIChE.

High performance prediction of molten steel temperature through gray-box model. / Okura, Toshinori; Kano, Manabu; Hasebe, Shinji et al.

Computing and Systems Technology Division - Core Programming Topic at the 2011 AIChE Annual Meeting. AIChE, 2011. p. 1153-1154 (Computing and Systems Technology Division - Core Programming Topic at the 2011 AIChE Annual Meeting; Vol. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Okura, T, Kano, M, Hasebe, S, Kitada, H & Murata, N 2011, High performance prediction of molten steel temperature through gray-box model. in Computing and Systems Technology Division - Core Programming Topic at the 2011 AIChE Annual Meeting. Computing and Systems Technology Division - Core Programming Topic at the 2011 AIChE Annual Meeting, vol. 2, AIChE, pp. 1153-1154, Computing and Systems Technology Division - Core Programming Topic at the 2011 AIChE Annual Meeting, Minneapolis, United States, 11/10/16.

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title = "High performance prediction of molten steel temperature through gray-box model",

author = "Toshinori Okura and Manabu Kano and Shinji Hasebe and Hiroshi Kitada and Noboru Murata",

note = "Funding Information: We wish to thank Dr. Ahmad Afaghi, assistant professor of the Qazvin University of Medical Sciences, for his excellent comments and editing of the manuscript.; Computing and Systems Technology Division - Core Programming Topic at the 2011 AIChE Annual Meeting ; Conference date: 16-10-2011 Through 21-10-2011",

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AU - Okura, Toshinori

AU - Kano, Manabu

AU - Hasebe, Shinji

AU - Kitada, Hiroshi

AU - Murata, Noboru

N1 - Funding Information: We wish to thank Dr. Ahmad Afaghi, assistant professor of the Qazvin University of Medical Sciences, for his excellent comments and editing of the manuscript.

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M3 - Conference contribution

AN - SCOPUS:85054544840

SN - 9781618397317

T3 - Computing and Systems Technology Division - Core Programming Topic at the 2011 AIChE Annual Meeting

SP - 1153

EP - 1154

BT - Computing and Systems Technology Division - Core Programming Topic at the 2011 AIChE Annual Meeting

PB - AIChE

T2 - Computing and Systems Technology Division - Core Programming Topic at the 2011 AIChE Annual Meeting

Y2 - 16 October 2011 through 21 October 2011

ER -

High performance prediction of molten steel temperature through gray-box model

Publication series

Other

ASJC Scopus subject areas

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Cite this