ESTIMATION OF LIQUIDUS TEMPERATURES OF STEEL USING ARTIFICIAL NEURAL NETWORK APPROACH

被引：0

作者：

Machu, Mario ^{[1
,2
]}

Drozdova, Lubomira ^{[1
,2
]}

Smetana, Bedrich ^{[1
,2
]}

Zimny, Ondrej ^{[1
]}

Vlcek, Jozef ^{[1
,2
]}

机构：

[1] VSB Tech Univ Ostrava, Ostrava, Czech Republic

[2] VSB Tech Univ Ostrava, Reg Mat Sci & Technol Ctr, Ostrava, Czech Republic

来源：

27TH INTERNATIONAL CONFERENCE ON METALLURGY AND MATERIALS (METAL 2018) | 2018年

关键词：

Artificial neural networks; liquidus temperature of steel; MATLAB; Thermo-Calc; IDS;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Presented works investigates a possibility of using modeling based on artificial neural network for prediction of liquidus temperatures of low-alloyed steels. Paper describes the methodology of creating such model by tools incorporated in commercial software MATLAB. Neural network is trained, validated and tested and previously unseen data measured by DTA method are used as new input data. Results are then compared to those measured and calculated by commonly used software for such applications like IDS and Thermo-Calc. Performance of these three modeling approaches is discussed.

引用

页码：56 / 62

页数：7

共 50 条

[21] Rainfall estimation using artificial neural network group
Zhang, M
Fulcher, J
Scofield, RA
NEUROCOMPUTING, 1997, 16 (02) : 97 - 115
[22] An artificial neural network approach for cost estimation of engineering services
Matel, Erik
Vahdatikhaki, Faridaddin
Hosseinyalamdary, Siavash
Evers, Thijs
Voordijk, Hans
INTERNATIONAL JOURNAL OF CONSTRUCTION MANAGEMENT, 2022, 22 (07) : 1274 - 1287
[23] Estimation of evapotranspiration using neural network approach
Khedkar, D. D.
Singh, P. K.
Bhakar, S. R.
JOURNAL OF AGROMETEOROLOGY, 2019, 21 (02): : 233 - 235
[24] TEMPERATURES OF SOLIDUS AND LIQUIDUS OF TOOL STEEL
Smetana, Bedrich
Zla, Simona
Kawulokova, Monika
Karel, Gryc
Strouhalova, Michaela
Kalup, Ales
Tkadleckova, Marketa
Dobrovska, Jana
Michalek, Karel
Jonsta, Petr
Susovsky, Michal
Dostal, Petr
Martinik, Ondrej
Drozdova, L'ubomira
METAL 2016: 25TH ANNIVERSARY INTERNATIONAL CONFERENCE ON METALLURGY AND MATERIALS, 2016, : 91 - 96
[25] Polymetallic Nodules Abundance Estimation using Sidescan Sonar: A Quantitative Approach using Artificial Neural Network
Jie, Wong Liang
Kalyan, Bharath
Chitre, Mandar
Vishnu, Hari
OCEANS 2017 - ABERDEEN, 2017,
[26] Estimation of liquidus temperatures in silicate glasses
Karlsson, KH
Backman, R
Cable, M
Peelen, J
Hermans, J
GLASS SCIENCE AND TECHNOLOGY-GLASTECHNISCHE BERICHTE, 2001, 74 (07): : 187 - 191
[27] PREDICTION OF TRIBOLOGICAL BEHAVIOR OF TIN COATED HOT WORK STEEL AT HIGH TEMPERATURES USING ARTIFICIAL NEURAL NETWORK
Tasdelen, M. E.
Dagasan, E.
Gercekcioglu, E.
JOURNAL OF THE BALKAN TRIBOLOGICAL ASSOCIATION, 2016, 22 (2A): : 1808 - 1820
[28] Distribution System State Estimation Using an Artificial Neural Network Approach for Pseudo Measurement Modeling
Manitsas, Efthymios
Singh, Ravindra
Pal, Bikash C.
Strbac, Goran
IEEE TRANSACTIONS ON POWER SYSTEMS, 2012, 27 (04) : 1888 - 1896
[29] Detection of corrosion on steel structures using an artificial neural network
Khayatazad, Mojtaba
Honhon, Matthias
De Waele, Wim
STRUCTURE AND INFRASTRUCTURE ENGINEERING, 2023, 19 (12) : 1860 - 1871
[30] Adaptive Parameter Estimation of the Generalized Extreme Value Distribution Using Artificial Neural Network Approach
Phoophiwfa, Tossapol
Laosuwan, Teerawong
Volodin, Andrei
Papukdee, Nipada
Suraphee, Sujitta
Busababodhin, Piyapatr
ATMOSPHERE, 2023, 14 (08)

← 1 2 3 4 5 →