A Novel Deep Recurrent Belief Network Model for Trend Prediction of Transformer DGA Data

A Novel Deep Recurrent Belief Network Model for Trend Prediction of Transformer DGA Data

Oil chromatography data together with its variation trend provide the key basis for the evaluation of the transformer health state. The existing studies on deep belief network (DBN) and support vector machine (SVM) have reported a few results in the field of oil chromatography data prediction. Howev...

Full description

Bibliographic Details
Main Authors: Bo Qi, Yiming Wang, Peng Zhang, Chengrong Li, Hongbin Wang
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Transformer
state prediction
deep belief network (DBN)
oil chromatography
self-adaptive delay network
Online Access:https://ieeexplore.ieee.org/document/8736867/

Internet

https://ieeexplore.ieee.org/document/8736867/

Similar Items