Dissolved gas content forecasting in power transformers based on Least Square Support Vector Machine (LSSVM)
Taking into account the chaotic characteristic of gas production within power transformers, a Least Square Support Vector Machine (LSSVM) model is implemented to forecast dissolved gas content based on historical chromatography samples. Additionally, an extending approach is developed with a correla...
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| Autore principale: | |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Escuela Politécnica Nacional (EPN)
2017-11-01
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| Serie: | Latin-American Journal of Computing |
| Soggetti: | |
| Accesso online: | https://lajc.epn.edu.ec/index.php/LAJC/article/view/131 |
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