Yagli G.M.
39
Coauthors
14
Documentos
Volumen de publicaciones por año
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| Año de publicación | Num. Publicaciones |
|---|---|
| 2018 | 3 |
| 2019 | 3 |
| 2020 | 3 |
| 2021 | 3 |
| 2022 | 2 |
Publicaciones por áreas de conocimiento
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| Área de conocimiento | Num. Publicaciones |
|---|---|
| Energía renovable | 9 |
| Energía solar | 5 |
| Energía | 5 |
| Aprendizaje automático | 4 |
| Estadísticas | 3 |
| Fotovoltaica | 2 |
| Meteorología | 2 |
| Sensores remotos | 1 |
| Geografía | 1 |
| Ciencia ambiental | 1 |
Publicaciones por áreas temáticas
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| Área temática | Num. Publicaciones |
|---|---|
| Física aplicada | 9 |
| Ciencias de la computación | 3 |
| Economía de la tierra y la energía | 3 |
| Otras ramas de la ingeniería | 3 |
| Geología, hidrología, meteorología | 3 |
| Métodos informáticos especiales | 2 |
| Ingeniería sanitaria | 1 |
| Dirección general | 1 |
| Comunicaciones | 1 |
| Educación, investigación, temas relacionados | 1 |
Principales fuentes de datos
| Origen | Num. Publicaciones |
|---|---|
| Scopus | 14 |
| Google Scholar | 0 |
| RRAAE | 0 |
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Coautores destacados por número de publicaciones
| Coautor | Num. Publicaciones |
|---|---|
| Dazhi Yang | 13 |
| Srinivasan D. | 11 |
| Gandhi O. | 2 |
| Monika | 2 |
| Tay J.W.E. | 1 |
| Carlos David Rodríguez-Gallegos | 1 |
| Manuel S. Alvarez-Alvarado | 1 |
| Sanjib Kumar Panda | 1 |
| Reindl T. | 1 |
| Vinayagam L. | 1 |
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Top Keywords
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Publicaciones del autor
Automatic hourly solar forecasting using machine learning models
ArticleAbstract: Owing to its recent advance, machine learning has spawned a large collection of solar forecasting woPalabras claves:Automatic machine learning, Solar forecasting, R caret packageAutores:Dazhi Yang, Srinivasan D., Yagli G.M.Fuentes:scopusEnsemble kriging for environmental spatial processes
Conference ObjectAbstract: Remote-sensed and reanalysis databases are valuable sources of environmental data that support a widPalabras claves:ensemble, KRIGING, solar irradiance, Solar resources, Spatio-temporal processAutores:Dazhi Yang, Tay J.W.E., Yagli G.M.Fuentes:scopusEnsemble solar forecasting and post-processing using dropout neural network and information from neighboring satellite pixels
ArticleAbstract: Ensemble weather forecasts are often found to be under-dispersed and biased. Post-processing using sPalabras claves:Dropout neural network, Ensemble solar forecasting, Machine learning, Monte Carlo sampling, Post-processing, Satellite-derived irradianceAutores:Dazhi Yang, Srinivasan D., Yagli G.M.Fuentes:scopusEnsemble solar forecasting using data-driven models with probabilistic post-processing through GAMLSS
ArticleAbstract: Forecast performance of data-driven models depends on the local weather and climate regime, which maPalabras claves:Ensemble forecasting, Forecast combination, Machine learning, Post-processing, probabilistic forecasting, TIME SERIESAutores:Dazhi Yang, Srinivasan D., Yagli G.M.Fuentes:scopusQuality Control for Solar Irradiance Data
Conference ObjectAbstract: With the advent of sensing technology, high-resolution data have become ubiquitous among various smaPalabras claves:BSRN, Quality control, solar irradianceAutores:Dazhi Yang, Quan H., Yagli G.M.Fuentes:scopus