Muestra la distribución de la producción WoS, Scopus y SciELO del autor.
Publicaciones WoS (Ediciones: ISSHP, ISTP, AHCI, SSCI, SCI), Scopus, SciELO Chile.
| Firmas del autor | |
| Nombre | ARAYA, BEATRIZ |
| Género | Mujer |
| Área Principal WOS | |
| Afiliación Principal | Universidad De Santiago De Chile |
Publicaciones en Chile
Citas Totales
Afiliaciones Chilenas
| WOS | #Pub |
|---|
| Scopus | #Pub |
|---|---|
| Computer Science (All) | 1 |
| Theoretical Computer Science | 1 |
| SciELO | #Pub |
|---|
| Autor | Género | # Pub |
|---|---|---|
| CUBILLOS-MONTECINOS, FRANCISCO ANIBAL | Hombre | 3 |
| HUANQUILEF, CRISTIAN | Hombre | 2 |
| SEGOVIA, GUISSELLE | - | 2 |
| PEREZ, CARLOS | Hombre | 2 |
| GARRIDO-ORTIZ, FERNANDA PAZ | Mujer | 1 |
| ACUÑA-LEIVA, GONZALO PEDRO | Hombre | 3 |
| CURILEM-SALDIAS, GLORIA MILLARAY | Mujer | 3 |
| MIRANDA, RODRIGO | Hombre | 1 |
| Institución | # Pub |
|---|---|
| Universidad De Santiago De Chile | 2 |
| Directic Soluc Tecnol | 1 |
| Directic Soluciones Tecnológicas | 1 |
| Año | Firma | Institución (Incites asoc.) | H Index | Average Percentile | Impact Citation | Impact Relative World | Impact Journal Normalized Citation | Impact Category Normalized Citation | Percentage Cited | Percentage Top 1 | Percentage Top 10 | Percentage Journal Q1 | Percentage Journal Q2 | Percentage Journal Q3 | Percentage Journal Q4 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2019 | Araya, Beatriz | Universidad de Santiago de Chile | 0.0 | 100.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| Título | Año | Citas | Tipo | Revista | Indexada |
|---|---|---|---|---|---|
| Prediction Of The Criticality Of A Heavy Duty Mining Equipment | 2015 | 0 | proceedings paper | 2015 Latin America Congress On Computational Intelligence (La Cci) | WoS Scopus |
| Narx Neural Network Model For Predicting Availability Of A Heavy Duty Mining Equipment | 2015 | 0 | proceedings paper | 2015 Latin America Congress On Computational Intelligence (La Cci) | WoS Scopus |
| Predictive Models Applied To Heavy Duty Equipment Management | 2014 | 3 | proceedings paper | Lecture Notes In Computer Science | WoS Scopus |
| Palabra Clave | #Pub |
|---|---|
| asset management | 3 |
| availability | 2 |
| narx | 2 |
| svm | 1 |
| support vector machines | 1 |
| spare parts | 1 |
| predictive models | 1 |
| predictive maintenance | 1 |
| prediction | 1 |
| neural network | 1 |
| mining equipment | 1 |
| mean time to repair | 1 |
| mean time between failures | 1 |
| maintenance | 1 |
| criticality prediction | 1 |
| copper mining | 1 |
| classification | 1 |