SURFACE AIR TEMPERATURE FORECASTING BASED ON ARTIFICIAL NEURAL NETWORKS AND THE METHOD OF VARIATIONAL MODE DECOMPOSITION

A hybrid method for forecasting surface air temperature for the next day has been developed and implemented, which uses a fully-connected neural network combined with preprocessing of the input signal by the method of variational mode decomposition. The overall value of the mean absolute error for the entire forecast was 0.35 oC.

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Published
2025-06-20
DOI
https://doi.org/10.56820/conferencearticle_685d0a9dc16933.21222212
Primary Topic
Advanced Sensor and Control Systems
Type
article
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article

SURFACE AIR TEMPERATURE FORECASTING BASED ON ARTIFICIAL NEURAL NETWORKS AND THE METHOD OF VARIATIONAL MODE DECOMPOSITION

И.В. Дель, N. O. Melnikov
Advanced Sensor and Control Systems
article

SURFACE AIR TEMPERATURE FORECASTING BASED ON ARTIFICIAL NEURAL NETWORKS AND THE METHOD OF VARIATIONAL MODE DECOMPOSITION

И.В. Дель, N. O. Melnikov
article en

Abstract

A hybrid method for forecasting surface air temperature for the next day has been developed and implemented, which uses a fully-connected neural network combined with preprocessing of the input signal by the method of variational mode decomposition. The overall value of the mean absolute error for the entire forecast was 0.35 oC.

National Research Tomsk State University (RU)
Openalex Percentile: Top 83%
Advanced Sensor and Control Systems
DOISourceOpenAlex
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SURFACE AIR TEMPERATURE FORECASTING BASED ON ARTIFICIAL NEURAL NETWORKS AND THE METHOD OF VARIATIONAL MODE DECOMPOSITION — И.В. Дель, N. O. Melnikov · (2025) | TGRS Research Map | TGRS