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Weak and Strong Compatibility in Data Fitting Problems Under Interval Uncertainty. / Shary, Sergey P.
в: Advances in data science and adaptive analysis, Том 12, № 1, 2050002, 01.2020.Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
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TY - JOUR
T1 - Weak and Strong Compatibility in Data Fitting Problems Under Interval Uncertainty
AU - Shary, Sergey P.
PY - 2020/1
Y1 - 2020/1
N2 - For the data fitting problem under interval uncertainty, we introduce the concept of strong compatibility between data and parameters. It is shown that the new strengthened formulation of the problem reduces to computing and estimating the so-called tolerable solution set for interval systems of equations constructed from the data being processed. We propose a computational technology for constructing a "best-fit" linear function from interval data, taking into account the strong compatibility requirement. The properties of the new data fitting approach are much better than those of its predecessors: strong compatibility estimates have polynomial computational complexity, the variance of the strong compatibility estimates is almost always finite, and these estimates are rubust. An example considered in the concluding part of the paper illustrates some of these features.
AB - For the data fitting problem under interval uncertainty, we introduce the concept of strong compatibility between data and parameters. It is shown that the new strengthened formulation of the problem reduces to computing and estimating the so-called tolerable solution set for interval systems of equations constructed from the data being processed. We propose a computational technology for constructing a "best-fit" linear function from interval data, taking into account the strong compatibility requirement. The properties of the new data fitting approach are much better than those of its predecessors: strong compatibility estimates have polynomial computational complexity, the variance of the strong compatibility estimates is almost always finite, and these estimates are rubust. An example considered in the concluding part of the paper illustrates some of these features.
KW - Data fitting problem
KW - interval uncertainty
KW - compatibility of data and parameters
KW - strong compatibility
KW - interval system of equations
KW - tolerable solution set
KW - recognizing functional
KW - nondifferentiable optimization
U2 - 10.1142/S2424922X20500023
DO - 10.1142/S2424922X20500023
M3 - Article
VL - 12
JO - Advances in data science and adaptive analysis
JF - Advances in data science and adaptive analysis
SN - 2424-922X
IS - 1
M1 - 2050002
ER -
ID: 26097662