Edward Preweda

The ambiguity of the results of the strict adjustment of horizontal geodetic networks

This research was financed by the Department of Geomatics of the AGH University of Science and Technology in Krakow statutory research funds.

Outlier detection in surveying networks

The paper refers to the robust estimation methods, which allows to eliminate outliers in surveying networks. Network adjustment is performed by the method of least squares. A key problem is the correct selection of weights, resulting from the different standard deviations of observations. In the case of gross errors their impact on the results of the alignment can be minimized by reducing the weight of outstanding observations. The second solution is the elimination of such observations as they were detected and realignment this network. In addition to the presentation of the well-known features, damping solution, iterative solution was presented based author idea. The calculation is illustrated on the one-dimensional random variable. Also presented the final results of the flat network adjustment by the proposed algorithm to eliminate outliers.

ESTIMATION LINEAR MODEL USING BLOCK GENERALIZED INVERSE OF A MATRIX

The work shows the principle of generalized linear model, point estimation, which can be used as a basis for determining the status of movements and deformations of engineering objects. The structural model can be put on any boundary conditions, for example, to ensure the continuity of the deformations. Estimation by the method of least squares was carried out taking into account the terms and conditions of the GaussMarkov for quadratic forms stored using Lagrange function. The original solution is removal of the generalized inverse of block matrix according to the designs of the fourth degree.