Prediction of dissolved gases content in power transformer oil using BASA-based mixed kernel RVR model
| Autor: | Chuang-Xin He, Sheng-Wei Fei |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
020401 chemical engineering
Renewable Energy Sustainability and the Environment Search algorithm 020209 energy Kernel (statistics) Content (measure theory) Radial basis function kernel 0202 electrical engineering electronic engineering information engineering 02 engineering and technology Sigmoid function 0204 chemical engineering Biological system Mathematics |
| Zdroj: | International Journal of Green Energy. 16:652-656 |
| ISSN: | 1543-5083 1543-5075 |
| DOI: | 10.1080/15435075.2019.1602534 |
| Popis: | In this paper, beetle antennae search algorithm-based mixed kernel relevance vector regression (BASA-MkRVR) model is presented and applied to predict the dissolved gases content in power transformer, and beetle antennae search algorithm (BASA) is used to select the appropriate kernel parameters and controlled parameter. The RVR model with RBF kernel (RBFRVR) and the RVR model with Sigmoid kernel (SigmoidRVR) are, respectively, used to compare with the proposed BASA-MkRVR model in order to testify the superiority of BASA-MkRVR compared with RBFRVR and SigmoidRVR. The experimental results indicate that BASA-MkRVR has more excellent prediction ability for the dissolved gases content in power transformer oil than RBFRVR and SigmoidRVR. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|