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...

• 第一著者: Rodríguez, Lester (author)
• その他の著者: Litardo Unda, Julio Goivanni (author)
• フォーマット: article
• 言語: spa
• 出版事項: 2025
• 主題: Energy Intensity; Artificial Neural Networks; Machine Learning; K-means; DBSCAN; Intensidad energética; Redes neuronales artificiales; Aprendizaje automático
• オンライン･アクセス: https://estudioseconomicos.bce.fin.ec/index.php/RevistaCE/article/view/502