2025-07-082025-07-082021-08-14Martínez Ballesteros, M.d.M., Martínez Ballesteros, M.d.M., Troncoso, A. y Martínez Álvarez, F. (2021). Advances in time series forecasting: innovative methods and applications. AIMS Mathematics, 9 (9), 24163-24165. https://doi.org/10.3934/math.20241174.2473-6988https://hdl.handle.net/11441/175101Time series forecasting plays a critical role in various domains, including finance, economics, environmental science, and healthcare. Time series forecasting has undergone significant evolution with the increasing availability of data and advancements in machine learning and statistical methods. This special issue aimed to bring together the latest advances, innovations, and research in the field of time series forecasting. Thus, a significant theme in this collection is the application of advanced ensemble learning techniques to improve forecasting accuracy.application/pdf3 p.engAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/articleinfo:eu-repo/semantics/openAccesshttps://doi.org/10.3934/math.20241174