Identification of thermal conductivities for nonhomogeneous materials based on the hybrid machine learning model

Key Points

• Identifying thermal conductivities is crucial for various applications in material science, engineering, and energy sectors.
• A hybrid machine learning approach enhances the accuracy of predictions in nonhomogeneous materials.
• This analysis considers a broad spectrum of material properties to optimize the predictive model's performance.
• Results from the investigation could significantly impact advancements in thermal management solutions for various industries.