Machine learning techniques to predict solar radiation
The purpose of the research is to develop several machine learning models to predict UV-B radiation and determine the best algorithm, whose type of research is applied and experimental design of preexperimental type with a quantitative approach. The methodology used for the development was the KDD(K...
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| Veröffentlicht in: | NeuroQuantology 2022-01, Vol.20 (6), p.7467 |
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| creator | Giancarlo Sánchez Atuncar Francisco Hilario Falcon |
| description | The purpose of the research is to develop several machine learning models to predict UV-B radiation and determine the best algorithm, whose type of research is applied and experimental design of preexperimental type with a quantitative approach. The methodology used for the development was the KDD(Knowledge Discovery in Database) methodology which consists of the following stages: |
| doi_str_mv | 10.14704/nq.2022.20.6.NQ22747 |
| format | Article |
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| fulltext | fulltext |
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| ispartof | NeuroQuantology, 2022-01, Vol.20 (6), p.7467 |
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| language | eng |
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| source | EZB-FREE-00999 freely available EZB journals |
| subjects | Accuracy Algorithms Artificial intelligence Cancer Decision trees Design of experiments Immune system Machine learning Neural networks Regression analysis Solar radiation Sun Sunburn & sun tanning Ultraviolet radiation |
| title | Machine learning techniques to predict solar radiation |
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