| Issue |
E3S Web Conf.
Volume 223, 2020
Regional Problems of Earth Remote Sensing (RPERS 2020)
|
|
|---|---|---|
| Article Number | 02012 | |
| Number of page(s) | 5 | |
| Section | Models and Methods of Remote Sensing Data Processing | |
| DOI | https://doi.org/10.1051/e3sconf/202022302012 | |
| Published online | 21 December 2020 | |
A New Nonparametric Algorithm for Preprocessing Stochastic Data with Uncertainty
Siberian Federal University, School of Information and Space and Technology, 660074 Krasnoyarsk, Russian Federation
* Corresponding author: echzhan@sfu-kras.ru
The article deals with the problem of modeling stochastic processes under uncertainty. The peculiarity of the processes under consideration is that the researcher does not have information about the mathematical structure of the object; the object is represented as a black box. The article proposes to use a nonparametric modeling algorithm based on a nonparametric estimate of the regression function on observations. To improve the accuracy of modeling, it is proposed to use an algorithm for generating training samples. The algorithm differs from the previous modification by the definition of essential variables. The results of computational experiments have shown the effectiveness of the proposed algorithms.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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