Use of Machine learning Models in structural engineering: Linear Regression algorithms and Gradient Descent algorithms in structural engineering
Machine learning algorithms, including linear regression and gradient descent, have found various applications in structural engineering. Here are a few examples: Structural Health Monitoring: Machine learning algorithms are used to detect and predict structural damage or failure by analyzing sensor data. Linear regression can predict the response of structures under various loads, while gradient descent algorithms can optimize sensor placement for better monitoring accuracy. Structural Design: Machine learning algorithms can be used to optimize the design of structures based on various parameters such as cost, safety, and performance. Linear regression can be used to model the relationship between design parameters and performance metrics, while gradient descent algorithms can be used to minimize the cost or maximize the performance of the structure. Structural Analysis: Machine learning algorithms can be used to predict the behavior of structures under various condi