Wyniki wyszukiwania - BazTech

Ograniczanie wyników

Znaleziono wyników: 2

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: nonlinear functions

Sortuj według:

Ogranicz wyniki do:

Propagation of uncertainty by Monte Carlo simulations in case of basic geodetic computations

Wyszkowska P.

Geodesy and Cartography

2017

Vol. 66, no. 2

333--346

The determination of the accuracy of functions of measured or adjusted values may be a problem in geodetic computations. The general law of covariance propagation or in case of the uncorrelated observations the propagation of variance (or the Gaussian formula) are commonly used for that purpose. That approach is theoretically justified for the linear functions. In case of the non-linear functions, the first-order Taylor series expansion is usually used but that solution is affected by the expansion error. The aim of the study is to determine the applicability of the general variance propagation law in case of the non-linear functions used in basic geodetic computations. The paper presents errors which are a result of negligence of the higher-order expressions and it determines the range of such simplification. The basis of that analysis is the comparison of the results obtained by the law of propagation of variance and the probabilistic approach, namely Monte Carlo simulations. Both methods are used to determine the accuracy of the following geodetic computations: the Cartesian coordinates of unknown point in the three-point resection problem, azimuths and distances of the Cartesian coordinates, height differences in the trigonometric and the geometric levelling. These simulations and the analysis of the results confirm the possibility of applying the general law of variance propagation in basic geodetic computations even if the functions are non-linear. The only condition is the accuracy of observations, which cannot be too low. Generally, this is not a problem with using present geodetic instruments.

Efektywność algorytmu propagacji wstecznej błędu z zastosowaniem nieliniowych funkcji aktywacji do aproksymacji terenu

Mrówczyńska M.

Zeszyty Naukowe. Budownictwo / Politechnika Śląska

2003

z. 101

271-278

W artykule przedstawiono zagadnienia związane z procesem uczenia sieci neuronowych dwuwarstwowych metodą propagacji błędu w zastosowaniu do aproksymacji powierzchni terenu. Podstawowym celem podjętej pracy jest badanie dokładności odwzorowania rzeźby terenu w zależności od zastosowanych nieliniowych funkcji aktywacji. Rozpatrywano również zagadnienia związane z doborem architektury sieci i parametrów uczenia oraz dokonano porównania wybranych metod przyspieszania zbieżności.

The paper presents the issue of learning of the unidirectional and two-layer net by means of the method of reverse propagation of the error applied to approximation of area surface, represented by a point pattern, which was determined in the configuration of space polar coordinates. The problem connected with the convergence, the speed of learning process convergence and the selection of the network architecture has been discussed in the paper as well.