Geospatial Forecasting of Electric Energy in Distribution Systems Using Segmentation and Machine Learning with Convolutional Methods
This paper proposes an innovative methodology for geospatial forecasting of electrical demand across various consumption segments and scales, integrating machine learning and discrete convolution within the framework of global system projections. The study was conducted in two phases: first, machine...
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Main Authors: | Héctor Chávez, Yuri Molina |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-01-01
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Series: | Energies |
Subjects: | |
Online Access: | https://www.mdpi.com/1996-1073/18/2/424 |
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