Estimation of low frequency electromagnetic values using machine learning

It is almost impossible to completely eliminate the effects of electromagnetic waves, but it is possible to reduce their effects. The use of machine learning is important to estimate these effects. Machine learning has been accelerating the upward trend over the last few years. It provides great advantages for problems that are difficult for human but easy to solve for machine. As a result, machine prediction is becoming increasingly popular. In this study, low frequency electromagnetic field values were measured in the buildings inside the campus and the output vector was tried to be estimated using machine learning. The results obtained by using linear regression, Gradient Descent (GD) algorithm and ridge regression models for estimation are evaluated.