Time series forecasting with multilayer perceptrons
| Parent link: | Proceedings of SPIE.— .— Bellingham: SPIE Vol. 12780 : Atmospheric and Ocean Optics: Atmospheric Physics.— 2023.— 1278072, 4 p. |
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| 其他作者: | , , , |
| 總結: | 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 |
| 語言: | 英语 |
| 出版: |
2023
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| 主題: | |
| 在線閱讀: | https://doi.org/10.1117/12.2690068 Статья на русском языке |
| 格式: | 電子 Book Chapter |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=680003 |
| 總結: | 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 |
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| DOI: | 10.1117/12.2690068 |