Transformer Fault Diagnosis Model Based on Improved Gray Wolf Optimizer and Probabilistic Neural Network
Dissolved gas analysis (DGA) based in insulating oil has become a more mature method in the field of transformer fault diagnosis. However, due to the complexity and diversity of fault types, the traditional modeling method based on oil sample analysis is struggling to meet the industrial demand for...
Main Authors: | Yichen Zhou, Xiaohui Yang, Lingyu Tao, Li Yang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-05-01
|
Series: | Energies |
Subjects: | |
Online Access: | https://www.mdpi.com/1996-1073/14/11/3029 |
Similar Items
-
A Novel Transformers Fault Diagnosis Method Based on Probabilistic Neural Network and Bio-Inspired Optimizer
by: Lingyu Tao, et al.
Published: (2021-05-01) -
Parameter Extraction of Three Diode Solar Photovoltaic Model Using Improved Grey Wolf Optimizer
by: Abd-ElHady Ramadan, et al.
Published: (2021-06-01) -
Improving the performance of support-vector machine by selecting the best features by Gray Wolf algorithm to increase the accuracy of diagnosis of breast cancer
by: Seyed Reza Kamel, et al.
Published: (2019-10-01) -
Gray Wolf Optimization Algorithm for Multi-Constraints Second-Order Stochastic Dominance Portfolio Optimization
by: Yixuan Ren, et al.
Published: (2018-05-01) -
Indirect Effect of African Swine Fever on the Diet Composition of the Gray Wolf <i>Canis lupus</i>—A Case Study in Belarus
by: Daniel Klich, et al.
Published: (2021-06-01)