| Título: | Temporary Variables for Predicting Electricity Consumption Through Data Mining |
| Autores: | Silva, Jesus ; Senior Naveda, Alexa ; Hernández Palma, Hugo ; Niebles Nú?z, William ; Niebles Nú?z, Leonardo |
| Tipo de documento: | texto impreso |
| Editorial: | Institute of Physics Publishing, 2020-06-30T21:57:26Z |
| Dimensiones: | application/pdf |
| Nota general: |
Journal of Physics: Conference Series 1432 1 info:eu-repo/semantics/openAccess Attribution-NonCommercial-ShareAlike 4.0 International http://creativecommons.org/licenses/by-nc-sa/4.0/ |
| Idiomas: | Inglés |
| Palabras clave: | Facultad de Negocios , Pregrado , Artículos científicos , Administración y Finanzas |
| Resumen: | In the new global and local scenario, the advent of intelligent distribution networks or Smart Grids allows real-time collection of data on the operating status of the electricity grid. Based on this availability of data, it is feasible and convenient to predict consumption in the short term, from a few hours to a week. The hypothesis of the study is that the method used to present time variables to a prediction system of electricity consumption affects the results. |
| En línea: | 17426588 |
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