Sulphide Capacity Prediction of Molten Slags by Using a Neural Network Approach

Derin, Bora; Suzuki, Masanori; Tanaka, Toshihiro

ISIJ International, 2010, 50(8), 1059-1063

Number of Access:512（2025-08-16 09:38 Counts）

Identifier to cite or link to this item: https://hdl.handle.net/11094/26389

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Title
Sulphide Capacity Prediction of Molten Slags by Using a Neural Network Approach
Creator
CreatorName
Derin, Bora
NRID
1000020610728 1000020610728
ORCID
0000-0003-1601-2842 0000-0003-1601-2842
researchmap permalink
eternalblue eternalblue
Scopus Author ID
56297002300 56297002300
CreatorName
Suzuki, Masanori
NRID
1000010179773 1000010179773
researchmap permalink
read0013978 read0013978
CreatorName
Tanaka, Toshihiro
Subject
sulfide capacities
molten melts
neural network computation
estimation
Abstract
In the present study, the neural network approach was applied for the estimation of sulfide capacities (Cs) in binary and multi-component melts at different temperatures. The calculated results obtained using neural network computation were plotted against the experimental values for comparison comparative purposes. Besides, iso-sulfide capacity contours on liquid regions of some ternary melt phase diagrams were generated and plotted by using neural network model results. It was found that calculated results obtained through neural network computation agree very well with the experimental results and more precise than those of some models.
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)
50(8)
Page
1059-1063
Date of Issued
2010
Language
English
Handle URL
https://hdl.handle.net/11094/26389
PISSN
09151559
NCID
AA10680712
Relation.isIdenticalTo
DOI (Publisher Version)
https://doi.org/10.2355/isijinternational.50.1059
Access Rights
open access
CopyRight
© 2010 ISIJ
oaire:version
Version of Record
Category
学術雑誌論文 Journal Article