Reconstruction of fields based on physics-informed neural networks with sensor placement optimization

Key Points

• Field reconstruction significantly improves through optimized sensor placement, leading to better data accuracy.
• Tests show a notable 25% enhancement in reconstruction accuracy, highlighting the method's effectiveness.
• Assessment using physics-informed neural networks demonstrates the potential for advanced modeling in diverse applications.
• Optimized sensor placement in field reconstruction emphasizes the need for efficient measurement strategies across various disciplines.