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### Detection of seepages in flood embankments using the ElasticNET method DOI:10.15199/48.2019.01.40

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Electric tomography is based on the transformation of data taken from the surface of the tested object into the image of its cross-section. There are many methods to optimize the obtained image by solving the appropriate objective function [1-5,13,15,16,20-25,32]. The algorithm based on the ElasticNET presented in this article is a new proposal in tomography. Fig. 1. Model of measuremnt system. The way of working of electrical impedance tomography (EIT) consists in introducing electrical voltage to the tested object by means of a set of electrodes located on the surface of the object. Next, the measured values of electrical potentials between individual electrode pairs are collected. Conductance of individual sections of the crosssection of the tested object is reconstructed on the basis of known values of voltages and measured values of potentials. Reconstruction of the image obtained by electrical tomography requires sophisticated modeling. This method of imaging consists in the fact that the conductivity distribution of the tested object is estimated on the basis of measurements of electrical voltages and electrode potentials on the surface of their contact with the tested object. In order to obtain quantitative data on changes in the conductivity inside an object, it is more effective to apply a non-linear model in differential imaging [1,6-12,14,17- 199,26-31]. In Fig. 1 shows the model of the measurement system. ElasticNET Let’s consider the problem of recognizing linear dependencies (1) Y  X   where Y Rn , X Rnk1 are the observation matrices of a output variable and predictive variables respectively,   Rk1means a matrix of structural parameters, while  Rn vector of independent random variables. The wellknown method of least squares consists in estimating unknown parameters &[...]

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