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  2. Examinar por materia

Examinando por Materia "Predicción de series temporales a largo plazo"

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    Cotton Price Long-Term Time Series Forecasting : A look at Transformers Suitability
    (Universidad EAFIT, 2024) Salazar Escobar, Carlos Enrique; Olarte, Tomás
    Recent years have witnessed a surge of Transformer-based models for long-term time series forecasting (LTSF). These models boast impressive results in Natural Language Processing (NLP) and Computer Vision (CV), but their effectiveness in capturing the crucial temporal order inherent in time series data remains a question. This work investigates the suitability of Transformer-based models for long-term commodity price prediction, by replicating the work presented in "Are Transformers Effective for Time Series Forecasting?" by Zeng et al. (2022). We aim to evaluate their effectiveness compared to simpler baselines and analyze their limitations in capturing long-range dependencies. By delving deeper into these limitations, this research seeks to contribute to the development of more effective forecasting models for commodity price prediction.

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