Machine Learning-Based Predictive Model for Tensile and Flexural Strength of 3D-Printed Concrete

Engineering

• Tensiles 100%
• Learning System 100%
• Bending Strength 100%
• Conventional Concrete 50%
• Fine Aggregate 50%
• Mixing Design 50%
• Root Mean Square Error 50%
• Square Mean 50%
• Input Parameter 50%
• Complex Structure 50%
• Coarse Aggregate 50%
• Concrete Construction 50%
• Additive Manufacturing 50%
• Ultimate Tensile Strength 50%
• Gaussians 50%
• Fluid Viscosity 50%
• Mean Square Error 50%
• Mean Absolute Error 50%
• Tensile Property 50%
• Three Dimensional Printing 50%
• Silica Fume 50%
• Support Vector Machine 50%
• Xgboost 50%

Material Science

• Flexural Strength 100%
• Ultimate Tensile Strength 100%
• Three Dimensional Printing 66%
• Silica Fume 33%
• Tensile Property 33%
• Xgboost 33%