TAE Predict: An Ensemble Methodology for Multivariate Time Series Forecasting of Climate Variables in the Context of Climate Change

TAE Predict: An Ensemble Methodology for Multivariate Time Series Forecasting of Climate Variables in the Context of Climate Change

Climate change presents significant challenges due to the increasing frequency and intensity of extreme weather events. Mexico, with its diverse climate and geographic position, is particularly vulnerable, underscoring the need for robust strategies to predict atmospheric variables. This work presen...

Full description

Saved in:
Bibliographic Details
Main Authors: Juan Frausto Solís, Erick Estrada-Patiño, Mirna Ponce Flores, Juan Paulo Sánchez-Hernández, Guadalupe Castilla-Valdez, Javier González-Barbosa
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Mathematical and Computational Applications
Subjects:
climate change
multivariate time series
deep learning
principal component analysis
ensemble methods
particle swarm optimization
Online Access:https://www.mdpi.com/2297-8747/30/3/46
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/2297-8747/30/3/46

Similar Items