Determining solidus temperature of steels by artificial neural network approach.
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27360%2F19%3A10243586" target="_blank" >RIV/61989100:27360/19:10243586 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Determining solidus temperature of steels by artificial neural network approach.
Original language description
The potential use of artificial neural networks to determine the solidus temperature for steel based on composition has been investigated. Input data consist of solidus composition and temperatures both from literature and both from measurements. The primary performance testing of the model was then performed for steel grades measured. Several types of network topologies have been designed and trained and the best model selected. Testing was done on previously unseen data measured by differential thermal analysis method as on new input data. The used method is described. Obtained results are then compared to those measured and calculated by commonly used software among the academic and commercial community like IDS and Thermo-Calc. Performance of these three modelling approaches is discussed by means of selected statistic tools.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20500 - Materials engineering
Result continuities
Project
<a href="/en/project/GA17-18668S" target="_blank" >GA17-18668S: Complex experimental research of selected properties of quaternary and quinary Fe-C-O-X(Y), (X,Y=Cr,Ni) systems at high temperatures</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Termoanalytický seminář : sborník příspěvků : 10.10.2019, Brno, Česko
ISBN
978-80-88307-03-7
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
113-117
Publisher name
Česká společnost chemická
Place of publication
Praha
Event location
Brno
Event date
Oct 10, 2019
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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