Standard
Interval Methods for Data Fitting Under Imprecision and Uncertainty. / Shary, Sergey P.
Proceedings - 2019 IEEE 8th International Conference on Advanced Optoelectronics and Lasers, CAOL 2019 with Scientific Workshop "Data Science in Modern Optoelectronics and Laser Engineering", DSMOLE 2019 and 16th Scientific Workshop "Measurement Uncertainty: Scientific, Normative, Applied and Methodical Aspects", UM 2019. ed. / Oleksiy V. Shulika; Vyacheslav A. Maslov. IEEE Computer Society, 2019. p. 626-631 9019465 (Proceedings of the International Conference on Advanced Optoelectronics and Lasers, CAOL; Vol. 2019-September).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
Harvard
Shary, SP 2019,
Interval Methods for Data Fitting Under Imprecision and Uncertainty. in OV Shulika & VA Maslov (eds),
Proceedings - 2019 IEEE 8th International Conference on Advanced Optoelectronics and Lasers, CAOL 2019 with Scientific Workshop "Data Science in Modern Optoelectronics and Laser Engineering", DSMOLE 2019 and 16th Scientific Workshop "Measurement Uncertainty: Scientific, Normative, Applied and Methodical Aspects", UM 2019., 9019465, Proceedings of the International Conference on Advanced Optoelectronics and Lasers, CAOL, vol. 2019-September, IEEE Computer Society, pp. 626-631, 8th International Conference on Advanced Optoelectronics and Lasers, CAOL 2019, Sozopol, Bulgaria,
06.09.2019.
https://doi.org/10.1109/CAOL46282.2019.9019465
APA
Shary, S. P. (2019).
Interval Methods for Data Fitting Under Imprecision and Uncertainty. In O. V. Shulika, & V. A. Maslov (Eds.),
Proceedings - 2019 IEEE 8th International Conference on Advanced Optoelectronics and Lasers, CAOL 2019 with Scientific Workshop "Data Science in Modern Optoelectronics and Laser Engineering", DSMOLE 2019 and 16th Scientific Workshop "Measurement Uncertainty: Scientific, Normative, Applied and Methodical Aspects", UM 2019 (pp. 626-631). [9019465] (Proceedings of the International Conference on Advanced Optoelectronics and Lasers, CAOL; Vol. 2019-September). IEEE Computer Society.
https://doi.org/10.1109/CAOL46282.2019.9019465
Vancouver
Shary SP.
Interval Methods for Data Fitting Under Imprecision and Uncertainty. In Shulika OV, Maslov VA, editors, Proceedings - 2019 IEEE 8th International Conference on Advanced Optoelectronics and Lasers, CAOL 2019 with Scientific Workshop "Data Science in Modern Optoelectronics and Laser Engineering", DSMOLE 2019 and 16th Scientific Workshop "Measurement Uncertainty: Scientific, Normative, Applied and Methodical Aspects", UM 2019. IEEE Computer Society. 2019. p. 626-631. 9019465. (Proceedings of the International Conference on Advanced Optoelectronics and Lasers, CAOL). doi: 10.1109/CAOL46282.2019.9019465
Author
Shary, Sergey P. /
Interval Methods for Data Fitting Under Imprecision and Uncertainty. Proceedings - 2019 IEEE 8th International Conference on Advanced Optoelectronics and Lasers, CAOL 2019 with Scientific Workshop "Data Science in Modern Optoelectronics and Laser Engineering", DSMOLE 2019 and 16th Scientific Workshop "Measurement Uncertainty: Scientific, Normative, Applied and Methodical Aspects", UM 2019. editor / Oleksiy V. Shulika ; Vyacheslav A. Maslov. IEEE Computer Society, 2019. pp. 626-631 (Proceedings of the International Conference on Advanced Optoelectronics and Lasers, CAOL).
BibTeX
@inproceedings{306e780a460d4663b1f19ee885276270,
title = "Interval Methods for Data Fitting Under Imprecision and Uncertainty",
abstract = "We consider the data fitting problem under interval uncertainty and show that the problem reduces to the solution of interval systems of equations constructed from the data being processed. The paper discusses in detail the so-called strong compatibility of parameters and data, as more practical, more adequate to reality and possessing better theoretical properties. Estimates of function parameters that satisfy the strong compatibility conditions have polynomial computational complexity, are robust, and almost always have finite variability. The paper proposes a computational technology for solving the data fitting problem for linear function, under interval data uncertainty and taking into account the requirement of strong compatibility.",
keywords = "compatibility of parameters and data, data fitting problem, interval system of equations, recognizing functional, tolerable solution set, united solution set",
author = "Shary, {Sergey P.}",
year = "2019",
month = sep,
doi = "10.1109/CAOL46282.2019.9019465",
language = "English",
series = "Proceedings of the International Conference on Advanced Optoelectronics and Lasers, CAOL",
publisher = "IEEE Computer Society",
pages = "626--631",
editor = "Shulika, {Oleksiy V.} and Maslov, {Vyacheslav A.}",
booktitle = "Proceedings - 2019 IEEE 8th International Conference on Advanced Optoelectronics and Lasers, CAOL 2019 with Scientific Workshop {"}Data Science in Modern Optoelectronics and Laser Engineering{"}, DSMOLE 2019 and 16th Scientific Workshop {"}Measurement Uncertainty",
address = "United States",
note = "8th International Conference on Advanced Optoelectronics and Lasers, CAOL 2019 ; Conference date: 06-09-2019 Through 08-09-2019",
}
RIS
TY - GEN
T1 - Interval Methods for Data Fitting Under Imprecision and Uncertainty
AU - Shary, Sergey P.
PY - 2019/9
Y1 - 2019/9
N2 - We consider the data fitting problem under interval uncertainty and show that the problem reduces to the solution of interval systems of equations constructed from the data being processed. The paper discusses in detail the so-called strong compatibility of parameters and data, as more practical, more adequate to reality and possessing better theoretical properties. Estimates of function parameters that satisfy the strong compatibility conditions have polynomial computational complexity, are robust, and almost always have finite variability. The paper proposes a computational technology for solving the data fitting problem for linear function, under interval data uncertainty and taking into account the requirement of strong compatibility.
AB - We consider the data fitting problem under interval uncertainty and show that the problem reduces to the solution of interval systems of equations constructed from the data being processed. The paper discusses in detail the so-called strong compatibility of parameters and data, as more practical, more adequate to reality and possessing better theoretical properties. Estimates of function parameters that satisfy the strong compatibility conditions have polynomial computational complexity, are robust, and almost always have finite variability. The paper proposes a computational technology for solving the data fitting problem for linear function, under interval data uncertainty and taking into account the requirement of strong compatibility.
KW - compatibility of parameters and data
KW - data fitting problem
KW - interval system of equations
KW - recognizing functional
KW - tolerable solution set
KW - united solution set
UR - http://www.scopus.com/inward/record.url?scp=85082004615&partnerID=8YFLogxK
U2 - 10.1109/CAOL46282.2019.9019465
DO - 10.1109/CAOL46282.2019.9019465
M3 - Conference contribution
AN - SCOPUS:85082004615
T3 - Proceedings of the International Conference on Advanced Optoelectronics and Lasers, CAOL
SP - 626
EP - 631
BT - Proceedings - 2019 IEEE 8th International Conference on Advanced Optoelectronics and Lasers, CAOL 2019 with Scientific Workshop "Data Science in Modern Optoelectronics and Laser Engineering", DSMOLE 2019 and 16th Scientific Workshop "Measurement Uncertainty
A2 - Shulika, Oleksiy V.
A2 - Maslov, Vyacheslav A.
PB - IEEE Computer Society
T2 - 8th International Conference on Advanced Optoelectronics and Lasers, CAOL 2019
Y2 - 6 September 2019 through 8 September 2019
ER -
