Forecasting Strength of CFRP Confined Concrete Using Multi Expression Programming

This study provides the application of a machine learning-based algorithm approach names “Multi Expression Programming” (MEP) to forecast the compressive strength of carbon fiber-reinforced polymer (CFRP) confined concrete. The suggested computational Multiphysics model is based on previously report...

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Veröffentlicht in:	Materials Jg. 14; H. 23; S. 7134
Hauptverfasser:	Ilyas, Israr, Zafar, Adeel, Javed, Muhammad, Farooq, Furqan, Aslam, Fahid, Musarat, Muhammad, Vatin, Nikolai
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 24.11.2021 MDPI
Schlagworte:	Algorithms Artificial intelligence Carbon fiber reinforced concretes Carbon fiber reinforced plastics Civil engineering Compressive strength Concrete Construction materials Diameters Fiber reinforced polymers Gene expression Genetic algorithms Genetic engineering Machine learning Mathematical functions Mathematical models Mechanical properties Modulus of elasticity Parametric analysis Parametric statistics Performance evaluation Rehabilitation Reliability analysis Research methodology Researchers Retrofitting Soft computing Statistical analysis Structural members Thickness Variables
ISSN:	1996-1944, 1996-1944
Online-Zugang:	Volltext
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