Time series forecasting with multilayer perceptrons; Proceedings of SPIE; Vol. 12780 : Atmospheric and Ocean Optics: Atmospheric Physics
| Parent link: | Proceedings of SPIE.— .— Bellingham: SPIE Vol. 12780 : Atmospheric and Ocean Optics: Atmospheric Physics.— 2023.— 1278072, 4 p. |
|---|---|
| Daljnji autori: | , , , |
| Sažetak: | Title screen An implementation of a week-ahead air temperature and atmospheric pressure forecast using a multilayer perceptron is presented (MLP). According to the specified meteorological parameters, data preparation, implementation and performance evaluation were performed for two MLP models. The MLP architecture was a s upervised feed -forward neural network with five hidden nodes and twenty iterations (repetitions). The obtained values of the ris k function (in this case, the standard deviation of the MSE) in both implementations are quite large Текстовый файл AM_Agreement |
| Jezik: | engleski |
| Izdano: |
2023
|
| Teme: | |
| Online pristup: | https://doi.org/10.1117/12.2690068 Статья на русском языке |
| Format: | Elektronički Poglavlje knjige |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=680003 |
MARC
| LEADER | 00000naa0a2200000 4500 | ||
|---|---|---|---|
| 001 | 680003 | ||
| 005 | 20250429144441.0 | ||
| 090 | |a 680003 | ||
| 100 | |a 20250429d2023 k||y0rusy50 ba | ||
| 101 | 0 | |a eng |c rus | |
| 102 | |a US | ||
| 135 | |a drcn ---uucaa | ||
| 181 | 0 | |a i |b e | |
| 182 | 0 | |a b | |
| 183 | 0 | |a cr |2 RDAcarrier | |
| 200 | 1 | |a Time series forecasting with multilayer perceptrons |d Прогнозирование временных рядов с помощью многослойных персептронов |z rus |f I. A. Botygin, V. A. Tartakovsky, V. S. Sherstnev, A. I. Sherstneva | |
| 203 | |a Текст |c электронный |b визуальный | ||
| 283 | |a online_resource |2 RDAcarrier | ||
| 300 | |a Title screen | ||
| 320 | |a References: 17 tit | ||
| 330 | |a An implementation of a week-ahead air temperature and atmospheric pressure forecast using a multilayer perceptron is presented (MLP). According to the specified meteorological parameters, data preparation, implementation and performance evaluation were performed for two MLP models. The MLP architecture was a s upervised feed -forward neural network with five hidden nodes and twenty iterations (repetitions). The obtained values of the ris k function (in this case, the standard deviation of the MSE) in both implementations are quite large | ||
| 336 | |a Текстовый файл | ||
| 371 | 0 | |a AM_Agreement | |
| 461 | 1 | |0 646891 |9 646891 |t Proceedings of SPIE |c Bellingham |n SPIE | |
| 463 | 1 | |t Vol. 12780 : Atmospheric and Ocean Optics: Atmospheric Physics |l Оптика атмосферы и океана. Физика атмосферы |o proceedings 29th International Symposium, 26-30 June 2023 Moscow, Russian Federation |o материалы XXIX Международного симпозиума, 26-30 июня 2023 года, Москва |f Institute of Atmospheric Optics SB RAS ; eds. O. A. Romanovskii |v 1278072, 4 p. |d 2023 | |
| 610 | 1 | |a time series | |
| 610 | 1 | |a forecasting | |
| 610 | 1 | |a artificial neural network | |
| 610 | 1 | |a multilayer perceptron | |
| 610 | 1 | |a risk function | |
| 610 | 1 | |a электронный ресурс | |
| 610 | 1 | |a труды учёных ТПУ | |
| 701 | 1 | |a Botygin |b I. A. |c specialist in the field of Informatics and computer engineering |c Associate Professor of Tomsk Polytechnic University, candidate of technical sciences |f 1947- |g Igor Aleksandrovich |9 17356 | |
| 701 | 1 | |a Tartakovsky |b V. A. | |
| 701 | 1 | |a Sherstnev |b V. S. |c specialist in the field of Informatics and computer engineering |c associate Professor of Tomsk Polytechnic University, candidate of technical Sciences |f 1974- |g Vladislav Stanislavovich |9 17137 | |
| 701 | 1 | |a Sherstneva |b A. I. |c mathematician |c associate Professor of Tomsk Polytechnic University, candidate of physico-mathematical Sciences |f 1974- |g Anna Igorevna |9 18721 | |
| 801 | 2 | |a RU |b 63413507 |c 20250429 |g RCR | |
| 850 | |a 63413507 | ||
| 856 | 4 | |u https://doi.org/10.1117/12.2690068 |z https://doi.org/10.1117/12.2690068 | |
| 856 | 4 | |u https://symp-pv.iao.ru/files/symp/aoo/29/E.pdf#page=74 |z Статья на русском языке | |
| 942 | |c CF | ||