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Estimation of low frequency electromagnetic values using machine learning

机译：利用机器学习估计低频电磁值

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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.
机译：几乎不可能完全消除电磁波的影响，但是可以减少它们的效果。机器学习的使用对于估计这些效果非常重要。机器学习一直在加速过去几年的上升趋势。它为人类而且易于解决机器难以提供的问题提供了很大的优势。结果，机器预测变得越来越受欢迎。在该研究中，在校园内的建筑物中测量低频电磁场值，并试图使用机器学习估计输出矢量。评估通过使用线性回归，梯度下降（GD）算法和用于估计的RIDGE回归模型而获得的结果。

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