Estimation of Surface Tension of Molten Silicates Using Neural Network Computation

Nakamoto, Masashi; Hanao, Masahito; Tanaka, Toshihiro; Kawamoto, Masayuki; Holappa, Lauri; Hämäläinen, Marko

doi:https://doi.org/10.2355/isijinternational.47.1075

Estimation of Surface Tension of Molten Silicates Using Neural Network Computation

Nakamoto, Masashi; Hanao, Masahito; Tanaka, Toshihiro et al.

ISIJ International, 2007, 47(8), 1075-1081

Number of Access:733（2025-10-05 09:56 Counts）

Identifier to cite or link to this item: https://hdl.handle.net/11094/26404

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Title	Estimation of Surface Tension of Molten Silicates Using Neural Network Computation
Creator	NRID 1000080467539 1000080467539 ORCID 0000-0003-4684-0200 0000-0003-4684-0200 researchmap permalink read0090330 read0090330 Scopus Author ID 7102132238 7102132238 CreatorName Nakamoto, Masashi
	CreatorName Hanao, Masahito
	NRID 1000010179773 1000010179773 researchmap permalink read0013978 read0013978 CreatorName Tanaka, Toshihiro
	CreatorName Kawamoto, Masayuki
	CreatorName Holappa, Lauri
	CreatorName Hämäläinen, Marko
Subject	surface tension
	silicate
	molten slag
	neural network computation
	estimation
Abstract	Neural network computation was applied to the estimation of surface tension in ternary silicate melts. In addition, the criterion for designing the units in the middle layer of the layer-type neural network computation was discussed. It was found that the Cp-criterion modified by considering the degrees of freedom in the neural network computation was useful for determining the number of units in the middle layer, which gives an optimal estimation. The surface tension calculated by neural network computation using units determined by the C_p-criterion virtually reproduced the experimental data in molten ternary silicates with high precision.
Publisher	日本鉄鋼協会
	The Iron and Steel Institute of Japan
	ニホン　テッコウ　キョウカイ
Source Title	ISIJ International
Volume (Issue)	47(8)
Page	1075-1081
Date of Issued	2007
Language	English
Handle URL	https://hdl.handle.net/11094/26404
PISSN	09151559
NCID	AA10680712
Relation.isIdenticalTo	DOI (Publisher Version) https://doi.org/10.2355/isijinternational.47.1075
Access Rights	open access
CopyRight	© 2007 ISIJ
oaire:version	Version of Record
Category	学術雑誌論文 Journal Article

Resource Type	journal article
Local Type	Journal Article
DCMI Type	Text
DCTERMS.bibliographicCitation	ISIJ International. 2007, 47(8), p. 1075-1081
DC.title	Estimation of Surface Tension of Molten Silicates Using Neural Network Computation
DC.creator	Nakamoto, Masashi
	Hanao, Masahito
	Tanaka, Toshihiro
	Kawamoto, Masayuki
	Holappa, Lauri
	Hämäläinen, Marko
DC.publisher	日本鉄鋼協会
	The Iron and Steel Institute of Japan
	ニホン　テッコウ　キョウカイ
DC.language' scheme='DCTERMS.RFC1766	English
DC.type' scheme='DCTERMS.DCMIType	Text
DCTERMS.issued' scheme='DCTERMS.W3CDTF	2007
DC.identifier	https://doi.org/10.2355/isijinternational.47.1075
DC.subject	surface tension
	silicate
	molten slag
	neural network computation
	estimation
DCTERMS.abstract	Neural network computation was applied to the estimation of surface tension in ternary silicate melts. In addition, the criterion for designing the units in the middle layer of the layer-type neural network computation was discussed. It was found that the Cp-criterion modified by considering the degrees of freedom in the neural network computation was useful for determining the number of units in the middle layer, which gives an optimal estimation. The surface tension calculated by neural network computation using units determined by the C_p-criterion virtually reproduced the experimental data in molten ternary silicates with high precision.
DC.rights	© 2007 ISIJ
DC.format	26404
citation_title	Estimation of Surface Tension of Molten Silicates Using Neural Network Computation
citation_author	Nakamoto, Masashi
	Hanao, Masahito
	Tanaka, Toshihiro
	Kawamoto, Masayuki
	Holappa, Lauri
	Hämäläinen, Marko
citation_publisher	日本鉄鋼協会
citation_language	English
citation_date	2007
citation_journal_title	ISIJ International
citation_volume	47
citation_issue	8
citation_firstpage	1075
citation_lastpage	1081
citation_doi	https://doi.org/10.2355/isijinternational.47.1075
citation_public_url	https://hdl.handle.net/11094/26404

Estimation of Surface Tension of Molten Silicates Using Neural Network Computation

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