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Predicting coastal profile evolution. / Baramiya, Denis; Lavrentiev, Mikhail; Spigler, Renato.

в: International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM, Том 19, № 1.4, 12.2019, стр. 285-292.

Результаты исследований: Научные публикации в периодических изданияхстатья по материалам конференцииРецензирование

Harvard

Baramiya, D, Lavrentiev, M & Spigler, R 2019, 'Predicting coastal profile evolution', International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM, Том. 19, № 1.4, стр. 285-292. https://doi.org/10.5593/sgem2019V/1.4/S01.035

APA

Baramiya, D., Lavrentiev, M., & Spigler, R. (2019). Predicting coastal profile evolution. International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM, 19(1.4), 285-292. https://doi.org/10.5593/sgem2019V/1.4/S01.035

Vancouver

Baramiya D, Lavrentiev M, Spigler R. Predicting coastal profile evolution. International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM. 2019 дек.;19(1.4):285-292. doi: 10.5593/sgem2019V/1.4/S01.035

Author

Baramiya, Denis ; Lavrentiev, Mikhail ; Spigler, Renato. / Predicting coastal profile evolution. в: International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM. 2019 ; Том 19, № 1.4. стр. 285-292.

BibTeX

@article{bce09f0d596f4230a632d3757757e9c9,
title = "Predicting coastal profile evolution",
abstract = "A long-term prediction of coastal profile evolution is done basing on several years' measurements. The adopted diffusion model is first calibrated against real data obtained from over more than 20 years measurements, and then extrapolated. A realistic prediction is then made by solving numerically a diffusion equation with coefficients obtained by the extrapolated values. In previous studies, taking into account the time dependence of the coefficients, we were able to reduce to 10 years the number of time measurements needed for calibration. Here we consider the possibility of predicting coastal profiles using only 5 years measurements. Numerical experiments made by using the JARKUS dataset have shown that our model is indeed able to predict the depth profile evolution occurring 3 years from now with a relative error less than about 10%.",
keywords = "Depth profile evolution, Diffusion model, Prediction",
author = "Denis Baramiya and Mikhail Lavrentiev and Renato Spigler",
year = "2019",
month = dec,
doi = "10.5593/sgem2019V/1.4/S01.035",
language = "English",
volume = "19",
pages = "285--292",
journal = "International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM",
issn = "1314-2704",
publisher = "International Multidisciplinary Scientific Geoconference",
number = "1.4",
note = "19th International Multidisciplinary Scientific Geoconference, SGEM 2019 ; Conference date: 30-06-2019 Through 06-07-2019",

}

RIS

TY - JOUR

T1 - Predicting coastal profile evolution

AU - Baramiya, Denis

AU - Lavrentiev, Mikhail

AU - Spigler, Renato

PY - 2019/12

Y1 - 2019/12

N2 - A long-term prediction of coastal profile evolution is done basing on several years' measurements. The adopted diffusion model is first calibrated against real data obtained from over more than 20 years measurements, and then extrapolated. A realistic prediction is then made by solving numerically a diffusion equation with coefficients obtained by the extrapolated values. In previous studies, taking into account the time dependence of the coefficients, we were able to reduce to 10 years the number of time measurements needed for calibration. Here we consider the possibility of predicting coastal profiles using only 5 years measurements. Numerical experiments made by using the JARKUS dataset have shown that our model is indeed able to predict the depth profile evolution occurring 3 years from now with a relative error less than about 10%.

AB - A long-term prediction of coastal profile evolution is done basing on several years' measurements. The adopted diffusion model is first calibrated against real data obtained from over more than 20 years measurements, and then extrapolated. A realistic prediction is then made by solving numerically a diffusion equation with coefficients obtained by the extrapolated values. In previous studies, taking into account the time dependence of the coefficients, we were able to reduce to 10 years the number of time measurements needed for calibration. Here we consider the possibility of predicting coastal profiles using only 5 years measurements. Numerical experiments made by using the JARKUS dataset have shown that our model is indeed able to predict the depth profile evolution occurring 3 years from now with a relative error less than about 10%.

KW - Depth profile evolution

KW - Diffusion model

KW - Prediction

UR - http://www.scopus.com/inward/record.url?scp=85092307767&partnerID=8YFLogxK

U2 - 10.5593/sgem2019V/1.4/S01.035

DO - 10.5593/sgem2019V/1.4/S01.035

M3 - Conference article

AN - SCOPUS:85092307767

VL - 19

SP - 285

EP - 292

JO - International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM

JF - International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM

SN - 1314-2704

IS - 1.4

T2 - 19th International Multidisciplinary Scientific Geoconference, SGEM 2019

Y2 - 30 June 2019 through 6 July 2019

ER -

ID: 25615699