Abstract
Beam-like structures are widespread but essential systems that have been extensively studied for centuries. Although several proposed solutions are effective, the time consumption and the difficulty of reconstructing the problem are the major disadvantages of these methods. This paper offers a new methodology for finding solutions to beam problems based on Machine Learning and Neural Networks with different optimization algorithms. Various regression models are compared on numerically stimulated Euler-Bernoulli beam modelling.
Keywords
Artificial neural network
Deflection (physics)
Computer science
Bernoulli's principle
Beam (structure)
Euler's formula
Artificial intelligence
Deflection angle
Machine learning
Mathematics
Engineering
Structural engineering
Mathematical analysis
Physics
Classical mechanics
Optics
Subject Areas
Structural Health Monitoring Techniques
·Civil and Structural Engineering ·Physical Sciences
Dam Engineering and Safety
·Civil and Structural Engineering ·Physical Sciences
Geotechnical Engineering and Underground Structures
·Civil and Structural Engineering ·Physical Sciences
Citations by Year
2024: 1
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