Experimental, regression learner, numerical, and artificial neural network analyses on a complex composite structure subjected to compression loading

Prediction of the ultimate axial load of circular concrete‐filled stainless steel tubular columns using machine learning approaches

“…Recently, machine learning (ML) has been used in different fields including civil engineering. [54][55][56][57][58][59][60][61][62][63][64][65] The ML method is a cost-effective and time-efficient design tool as compared to the experimental and numerical schemes. In the ML method, a database is used to train the complex relationships of input and output variables of composite columns.…”

“…Although the numerical model is a cost‐effective alternative to performing an inelastic analysis of composite columns, the development of such a numerical model is still very tedious and time‐consuming. Recently, machine learning (ML) has been used in different fields including civil engineering 54–65 . The ML method is a cost‐effective and time‐efficient design tool as compared to the experimental and numerical schemes.…”

Neural Network-Based Prediction Model to Investigate the Influence of Temperature and Moisture on Vibration Characteristics of Skew Laminated Composite Sandwich Plates

“…The ANN technique has been extensively and effectively employed in civil engineering applications and is slowly gaining importance in other prominent engineering areas as well. In the recent past, ANNs have been used extensively by researchers for structural engineering applications such as failure prediction, crack detection, delamination identification and quantification of magnitude, predicting the size and position of cutouts [28,29], mechanical characteristics [30,31], etc. Recently, Zenzen et al [32] adopted a transmissibility damage indicator and an ANN to predict damage location and size.…”