Restoring the values of geo-fields using a combination of kernel smoothing methods and artificial neural networks models

Geographic Information Systems
UDC: 
52.08:004.62:681.518.3
DOI: 
10.22389/0016-7126-2022-990-12-57-64
1 Gvozdev O.G.
2 Materuhin A.V.
3 Maiorov A.A.
Year: 
2022
№: 
12
990
Pages: 
57-64

Moscow State University of Geodesy and Cartography (MIIGAiK)

1, 
2, 
3, 
Abstract:
The purpose of the study, the results of which are described in the article, was to improve solving the matter of the geo-fields’ values restoring based on processing high-intensity spatial-temporal data streams received from a highly mobile geo-sensors network. Previously, the authors proposed an original approach to solving this task, which means applying the kernel smoothing methods, the nuclear function for which is determined automatically, using discrete stochastic optimization, in particular, the annealing simulation method. The idea of a new approach proposed by the authors is as follows: to apply kernel smoothing methods using an automatic adaptive technique for determining the parameters of the function to build a preliminary geo-field model, and then one based on a neural network to refine it. That enables removing the main limitation of the applicability of the previous solution based on the assumption of all points’ local homogeneity. The method described in this article does not use this assumption and can be applied in situations where it is violated. The article contains a description of the computational experiments carried out as well as a discussion of the outcome obtained. The results of computational experiments showed a clear advantage of the new technology.
The results were obtained as a part of the state task of the Ministry of Science and Higher Education of the Russian Federation (No. FSFE-2022-0002)
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Citation:
Gvozdev O.G., 
Materuhin A.V., 
Maiorov A.A., 
(2022) Restoring the values of geo-fields using a combination of kernel smoothing methods and artificial neural networks models. Geodesy and cartography = Geodezia i Kartografia, 83(12), pp. 57-64. (In Russian). DOI: 10.22389/0016-7126-2022-990-12-57-64
Publication History
Received: 01.12.2022
Accepted: 05.12.2022
Published: 20.01.2023

Content

2022 December DOI:
10.22389/0016-7126-2022-990-12