Prediction of buckling damage of steel equal angle structural members using hybrid machine learning techniques

NX Ho, TT Le, TH Dinh, VH Nguyen - Scientific Reports, 2025 - nature.com
This article deals with prediction of buckling damage of steel equal angle structural
members using a surrogate model combining machine learning and metaheuristic …

Modeling and optimization of hard turning: predictive analysis of surface roughness and cutting forces in AISI 52100 steel using machine learning

R Kumar, M Rafighi, M Özdemir, A Şahinoğlu… - International Journal on …, 2024 - Springer
This study addresses the critical need for high-strength, corrosion-resistant materials in
renewable energy, biomedical and maritime applications, necessitating effective heat …

R-RAM: A novel hybrid model for option ranking

DD Trung, DV Duc, NC Bao, NH Son… - Yugoslav Journal of …, 2025 - doiserbia.nb.rs
Ranking alternatives considering multiple criteria is a complex task, requiring the selection
of both a weight calculation method and a ranking method. This study proposes a hybrid …

[PDF][PDF] Manufacturing Process Optimization Using Open Data and Different Analyses Methods

M Tahiduzzaman, AK Ghosh, S Ura - 2025 - preprints.org
Machining process optimization involves selecting appropriate control variable (CV) settings
to achieve desired evaluation variable (EV) outcomes. With the emergence of Open Data …

Experimental research of the influence of fiber laser machining parameters on HAZ width in AISI 4140 steels

MŞ Adin - Dicle Üniversitesi Mühendislik Fakültesi Mühendislik … - dergipark.org.tr
In present day, laser beam machining technology attracts great attention due to its cost-
effectiveness, high machining quality, mass manufacturing velocity and broad areas of …