ORIGINAL ARTICLE
Some properties of the basins of attraction of the Newton's method for simple nonlinear geodetic systems
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Department of Civil Engineering and Geodesy, Military University of Technology, Gen. S. Kaliskiego 2, 00-908 Warsaw, Poland
 
These authors had equal contribution to this work
 
 
A - Research concept and design; B - Collection and/or assembly of data; C - Data analysis and interpretation; D - Writing the article; E - Critical revision of the article; F - Final approval of article
 
 
Submission date: 2024-02-11
 
 
Final revision date: 2024-06-05
 
 
Acceptance date: 2024-06-10
 
 
Publication date: 2024-07-15
 
 
Corresponding author
Ireneusz Winnicki   

Department of Civil Engineering and Geodesy, Military University of Technology, Gen. S. Kaliskiego 2, 00-908 Warsaw, Poland
 
 
Reports on Geodesy and Geoinformatics 2024;118:22-40
 
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ABSTRACT
The research presented in this paper concerns the determination of the attraction basins of Newton’s iterative method, which was used to solve the non-linear systems of observational equations associated with the geodetic measurements. The simple observation systems corresponding to the intersections or linear and angular resections used in practice were considered. The main goal was to investigate the properties of the sets of convergent initial points of the applied iterative method. Therefore, the answers to the questions regarding the geometric structure of the basins, their limitations, connectedness, or self-similarity were sought. The research also concerned the iterative structures of the basin: maps of the number of iterations which are necessary to achieve the convergence of the Newton’s method. The determined basins were compared with the areas of convergence that result from theorems on the convergence of the Newton’s method: the conditions imposed on the eigenvalues and norms of the matrices of the studied iterative systems. One of the significant results is the indication that the obtained basins of attraction contain areas resulting from the theoretical premises. Their diameters can be comparable with the sizes of the analyzed geodetic structures. Consequently, in the analyzed cases, it is possible to construct methods that enable quick selection of the initial starting points or automation of such selection. The paper also characterizes the global convergence mechanism of the Newton’s method for disconnected basins and, as a consequence, the non-local initial points located far from the solution points.
ACKNOWLEDGEMENTS
This research is supported by the Faculty of Civil Engineering and Geodesy statutory research founds.
 
REFERENCES (18)
1.
Banach, S. (1922). Sur les opérations dans les ensembles abstraits et leur application aux équations intégrales (On operations in abstract sets and their application to integral equations). Fundamenta Mathematicae, 3(1):133–181.
 
2.
Barnsley, M. F. (2000). Fractals everywhere. Morgan Kaufmann Publishers, 2 edition. Dennis, J. E. J. and Schnabel, R. B. (1996). Numerical Methods for Unconstrained Optimization and Nonlinear Equations, volume 16 of Classics In Applied Mathematics. SIAM, Philadelphia, 2 edition.
 
3.
Ghilani, C. D. (2017). Adjustment computations: Spatial data analysis. Wiley, 6 edition.
 
4.
Guckenheimer, J. and Holmes, P. (1983). Nonlinear Oscillations, Dynamical Systems, and Bifurcations of Vector Fields, volume 42 of Applied Mathematical Sciences. Springer, New York.
 
5.
Kelley, C. T. (1995). Iterative methods for linear and nonlinear equations. SIAM, Philadelphia.
 
6.
Kincaid, D. and Cheney, W. (2002). Numerical Analysis: Mathematics of Scientific Computing. University of Texas, Austin, 3 edition.
 
7.
Kroszczynski, K. and Winnicki, I. (2002). The properties of strange attractor reconstructed from the time series of tropospheric mean temperature. In Proceedings of the 18th International Conference on Interactive Information and Processing Systems for Meteorology, Oceanography and Hydrology (IIPS), pages 199–200, Orlando, FL. American Meteorological Society.
 
8.
Lothar, G. (1993). Developments with respect to the automated processing and analysis of engineering survey data. In Proceedings of the Applications of Geodesy to Engineering, pages 175–184.
 
9.
Nielsen, A. A. (2013). Least squares adjustment: Linear and nonlinear weighted regression analysis.
 
10.
Nusse, H. E. and Yorke, J. A. (1998). Dynamics: Numerical Explorations. Applied Mathematical Sciences. Springer, New York.
 
11.
Ortega, J. M. (1972). Numerical Analysis. A Second Course. Computer Science and Applied Mathematics: Monographs and Textbooks. Academic Press, New York.
 
12.
Ortega, J. M. and Rheinboldt, W. C. (1970). Iterative Solutions of Nonlinear Equations in Several Variables. Academic Press, New York.
 
13.
Ostrowski, A. M. (1966). Solutions of Equations and Systems of Equations, volume 9 of Pure and Applied Mathematics: Monographs and Textbooks. Academic Press, New York, 2 edition.
 
14.
Qureshi, S., Chicharro, F. I., Argyros, I. K., Soomro, A., Alahmadi, J., and Hincal, E. (2024). A new optimal numerical root-solver for solving systems of nonlinear equations using local, semi-local, and stability analysis. Axioms, 13(6), doi:10.3390/axioms13060341.
 
15.
Siki, Z. (2018). Geoeasy an open source project for surveying calculations. Geoinformatics FCE CTU, 17(2):1–8, doi:10.14311/gi.17.2.1.
 
16.
Traub, J. F. (1982). Iterative Methods for the Solution of Equations. American Mathematical Society, New York, 2 edition.
 
17.
Uren, J. and Price, B. (1985). Intersection and resection. Surveying for Engineers, 108:188–196.
 
18.
Čepek, A. (2002). The GNU GaMa Project – Adjustment of geodetic networks. Acta Polytechnica, 42(3):26–30, doi:10.14311/350.
 
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