A topological approach to enhancing consistency in machine learning via recurrent neural networks
author
Yatkin, Muhammed Adil
Kõrgesaar, Mihkel
Islak, Umit
statement of authorship
Muhammed Adil Yatkin, Mihkel Kõrgesaar and Ümit Işlak
source
Applied sciences
special issue
Deformation and Fracture Behaviors of Materials
publisher
MDPI
journal volume number month
vol. 15, 2
year of publication
2025
pages
art. 933, 19 p. : ill
url
https://doi.org/10.3390/app15020933
subject term
tehisnärvivõrgud
deformatsioon
tehisõpe
jadad
kompuutermodelleerimine
keyword
consistency
forming limit curves (FLCs)
recurrent neural networks (RNNs)
sequence to sequence learning
surrogate modelling
ISSN
2076-3417
notes
Bibliogr.: 42 ref
Open Access
Open Access
scientific publication
teaduspublikatsioon
classifier
1.1
Scopus
https://www.scopus.com/sourceid/21100829268
https://www.scopus.com/pages/publications/85215694420?origin=resultslist
WOS
https://jcr.clarivate.com/jcr-jp/journal-profile?journal=APPL%20SCI-BASEL&year=2025
https://www.webofscience.com/wos/woscc/full-record/WOS:001404063400001
category (general)
Chemical engineering
Keemiatehnoloogia
Physics and astronomy
Füüsika ja astronoomia
Engineering
Tehnika
Computer science
Arvutiteadus
Materials science
Materjaliteadus
category (sub)
Chemical engineering. Fluid flow and transfer processes
Keemiatehnoloogia. Vedeliku voolu- ja ülekandeprotsessid
Physics and astronomy. Instrumentation
Füüsika ja astronoomia. Instrumentatsioon
Engineering. General engineering
Tehnika. Üldine inseneriteadus
Computer science. Computer science applications
Arvutiteadus. Arvutiteaduse rakendused
Materials science. General materials science
Materjaliteadus. Üldine materjaliteadus
Chemical engineering. Process chemistry and technology
Keemiatehnoloogia. Protsessi keemia ja tehnoloogia
quartile
Q2
TalTech department
Kuressaare kolledž
Kuressaare College
language
English
Inglise