Estimation and optimization of reinforcement parameters for composite material using a machine learning approach

Key Points

• Effective estimation of reinforcement parameters improves performance in composite materials and machine learning techniques play a crucial role.
• Optimization through machine learning yielded significant improvements in reinforcement parameter values, enhancing material properties for practical applications.
• Utilization of a data-driven approach enables precise adjustments in composite material design, leading to enhanced structural integrity and performance.
• The findings imply a transformational shift towards integrating machine learning for future developments in composite material innovations.