A Methodological Comparison of Forecasting Models Using KZ Decomposition and Walk-Forward Validation

The accurate forecasting of surface air temperature (T2M) is crucial for climate analysis, agricultural planning, and energy management. This study proposes a novel forecasting framework grounded in structured temporal decomposition. Using the Kolmogorov–Zurbenko (KZ) filter, all predictor variables...

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Egile Nagusiak:	Khawla Al-Saeedi, Diwei Zhou, Andrew Fish, Katerina Tsakiri, Antonios Marsellos
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	MDPI AG 2025-10-01
Saila:	Mathematics
Gaiak:	time series forecasting Kolmogorov–Zurbenko filter multi-scale decomposition Ridge regression Lasso regression Random Forest
Sarrera elektronikoa:	https://www.mdpi.com/2227-7390/13/21/3410
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