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http://hdl.handle.net/10553/37091
Title: | Temperature control by its forecasting applying score fusion for sustainable development | Authors: | Hernández-Travieso, José Gustavo Herrera-Jiménez, Antonio L. Travieso-González, Carlos M. Morgado-Dias, F. Alonso-Hernández, Jesús B. Ravelo-García, Antonio G. |
UNESCO Clasification: | 3308 Ingeniería y tecnología del medio ambiente | Keywords: | Temperature forecasting Sustainable development Artificial neural network Score fusion Prediction system |
Issue Date: | 2017 | Journal: | Sustainability (Switzerland) | Abstract: | Temperature control and its prediction has turned into a research challenge for the knowledge of the planet and its effects on different human activities and this will assure, in conjunction with energy efficiency, a sustainable development reducing CO2 emissions and fuel consumption. This work tries to offer a practical solution to temperature forecast and control, which has been traditionally carried out by specialized institutes. For the accomplishment of temperature estimation, a score fusion block based on Artificial Neural Networks was used. The dataset is composed by data from a meteorological station, using 20,000 temperature values and 10,000 samples of several meteorological parameters. Thus, the complexity of the traditional forecasting models is resolved. As a result, a practical system has been obtained, reaching a mean squared error of 0.136 degrees C for short period of time prediction and 5 degrees C for large period of time prediction. | URI: | http://hdl.handle.net/10553/37091 | ISSN: | 2071-1050 | DOI: | 10.3390/su9020193 | Source: | Sustainability (Switzerland) [ISSN 2071-1050],v. 9 (2), 193 |
Appears in Collections: | Artículos |
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