Modeling and Prediction of the Energy Intensity Index by Provinces of Ecuador Using Neural Networks and Cluster Analysis with Machine Learning Algorithms

Using a comparative experimental design, four neural network architectures—feedforward, LSTM, sequential feedforward, and robust LSTM—are evaluated to predict the provincial energy intensity index, based on panel data from 2018 to 2023 and key variables related to energy consumption, economic activi...

Celý popis

Uloženo v:

Podrobná bibliografie
Hlavní autor:	Rodríguez, Lester (author)
Další autoři:	Litardo Unda, Julio Goivanni (author)
Médium:	article
Jazyk:	spa
Vydáno:	2025
Témata:	Energy Intensity Artificial Neural Networks Machine Learning K-means DBSCAN Intensidad energética Redes neuronales artificiales Aprendizaje automático
On-line přístup:	https://estudioseconomicos.bce.fin.ec/index.php/RevistaCE/article/view/502
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!

Modeling and Prediction of the Energy Intensity Index by Provinces of Ecuador Using Neural Networks and Cluster Analysis with Machine Learning Algorithms

Podobné jednotky