Shear Strength Prediction

Shear strength prediction focuses on accurately estimating the force required to initiate sliding or deformation in various materials and systems. Current research emphasizes developing advanced computational models, including neural networks (like Graph Neural Networks and Convolutional Neural Networks) and machine learning algorithms (such as PSO-based FNNs), to improve prediction accuracy and efficiency across diverse applications. These advancements are crucial for optimizing designs in engineering (e.g., reinforced concrete structures), enhancing robotic manipulation through tactile sensing, and improving medical diagnoses (e.g., aneurysm rupture risk assessment) by providing more precise and timely information. The ultimate goal is to replace less accurate methods and improve decision-making in various fields.