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Discovery of fatigue strength models via feature engineering and automated eXplainable machine learning applied to the welded transverse stiffener
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In
International journal of fatigue 203, Seiten/Artikel-Nr.:109324
2026 & 2025
Received 27 June 2025, Revised 5 October 2025, Accepted 6 October 2025, Available online 16 October 2025
Online
DOI: 10.1016/j.ijfatigue.2025.109324
DOI: 10.18154/RWTH-2025-09933
URL: https://publications.rwth-aachen.de/record/1022304/files/1022304.pdf
Einrichtungen
Thematische Einordnung (Klassifikation)
DDC: 600
OpenAccess: 
PDF
Dokumenttyp
Journal Article
Format
online, print
Sprache
English
Anmerkung
Peer reviewed article
Externe Identnummern
SCOPUS: SCOPUS:2-s2.0-105020962708
WOS Core Collection: WOS:001607377600001
Interne Identnummern
RWTH-2025-09933
Datensatz-ID: 1022304
Beteiligte Länder
Germany
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; Clarivate Analytics Master Journal List ; Current Contents - Engineering, Computing and Technology ; Ebsco Academic Search ; Essential Science Indicators ; IF >= 5 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection
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The record appears in these collections: |
| Typ | Amount | VAT | Currency | Share | Status | Cost centre |
| Hybrid-OA | 2575.00 | 180.25 | EUR | 96.26 % | (DEAL) | 021000-311710 |
| Other | 100.00 | 7.00 | EUR | 3.74 % | (DEAL) | 021000-311710 |
| Sum | 2675.00 | 187.25 | EUR | |||
| Total | 2862.25 |
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