Time series forecasting with multilayer perceptrons

Bibliographic Details
Parent link:	Proceedings of SPIE.— .— Bellingham: SPIE Vol. 12780 : Atmospheric and Ocean Optics: Atmospheric Physics.— 2023.— 1278072, 4 p.
Other Authors:	Botygin I. A. Igor Aleksandrovich, Tartakovsky V. A., Sherstnev V. S. Vladislav Stanislavovich, Sherstneva A. I. Anna Igorevna
Summary:	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
Language:	English
Published:	2023
Subjects:	time series forecasting artificial neural network multilayer perceptron risk function электронный ресурс труды учёных ТПУ
Online Access:	https://doi.org/10.1117/12.2690068 Статья на русском языке
Format:	Electronic Book Chapter
KOHA link:	https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=680003

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