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Extrapolation of Functions of Many Variables by Means of Metric Analysis
- Source :
- EPJ Web of Conferences, Vol 173, p 03014 (2018)
- Publication Year :
- 2018
- Publisher :
- EDP Sciences, 2018.
-
Abstract
- The paper considers a problem of extrapolating functions of several variables. It is assumed that the values of the function of m variables at a finite number of points in some domain D of the m-dimensional space are given. It is required to restore the value of the function at points outside the domain D. The paper proposes a fundamentally new method for functions of several variables extrapolation. In the presented paper, the method of extrapolating a function of many variables developed by us uses the interpolation scheme of metric analysis. To solve the extrapolation problem, a scheme based on metric analysis methods is proposed. This scheme consists of two stages. In the first stage, using the metric analysis, the function is interpolated to the points of the domain D belonging to the segment of the straight line connecting the center of the domain D with the point M, in which it is necessary to restore the value of the function. In the second stage, based on the auto regression model and metric analysis, the function values are predicted along the above straight-line segment beyond the domain D up to the point M. The presented numerical example demonstrates the efficiency of the method under consideration.
- Subjects :
- 0209 industrial biotechnology
Physics
QC1-999
020208 electrical & electronic engineering
Extrapolation
02 engineering and technology
Function (mathematics)
Domain (mathematical analysis)
020901 industrial engineering & automation
Autoregressive model
Metric (mathematics)
0202 electrical engineering, electronic engineering, information engineering
Applied mathematics
Point (geometry)
Finite set
Interpolation
Subjects
Details
- ISSN :
- 2100014X
- Volume :
- 173
- Database :
- OpenAIRE
- Journal :
- EPJ Web of Conferences
- Accession number :
- edsair.doi.dedup.....588d588d59e5139c9151ae4afb11bf13
- Full Text :
- https://doi.org/10.1051/epjconf/201817303014