Applying Logistic Regression with Elastic Net and PCA to Determine the Objects Location in EIT

Abstract

The article presents the application of logistic regression with Principal Components Analysis (PCA) and elastic net to find the localisation location in Electrical Impedance Tomography (EIT). The team's main focus was the use of machine learning algorithms in electrical tomography for object detection in a tank. Tomographic methods represent a dimensional image of the inside of the space rather than the individual points of the section under study. The study showed that the choice of the logistic regression method significantly affects the accuracy of the obtained results. For research purposes, specially designed numerical models were used.