Optimal Prediction for Patch Design Using YUKI-RANDOM-FOREST in a Cracked Pipeline Repaired with CFRP

This paper presents the effectiveness of a hybrid YUKI-RANDOM-FOREST, Particle Swarm Optimization-YUKI (PSO-YUKI), and balancing composite motion optimization algorithm (BCMO) based on artificial neural networks (ANN) for the best prediction of patch design considering the maximum principal stress....

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Veröffentlicht in:	Arabian journal for science and engineering (2011) 2024, Vol.49 (11), p.15085-15102
Hauptverfasser:	Oulad Brahim, Abdelmoumin, Capozucca, Roberto, Khatir, Samir, Fahem, Noureddine, Benaissa, Brahim, Cuong-Le, Thanh
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial neural networks Crack sensitivity Critical pressure Design optimization Design parameters Effectiveness Engineering Finite element method Humanities and Social Sciences Internal pressure Mechanical properties multidisciplinary Notch sensitivity Notches Numerical models Optimization techniques Parameter sensitivity Particle swarm optimization Pipes Pressure effects Research Article-Mechanical Engineering Science Structural safety
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