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What is Dissolved Gas Forecasting in Transformers about?

This document presents a method for using Least-Squares Support Vector Machines (LS-SVM) to forecast dissolved gas levels in power transformers using time series data. It preprocesses the time series data using exponential smoothing to handle irregularly sampled, noisy data. It then trains and evaluates LS-SVM models on the preprocessed data both with and without additional features derived from established dissolved gas analysis techniques. The models trained on all transformer data outperformed those trai

Author

Felipe Kaew

Language

EN