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Missing values are a common occurrence in a number of real world databases, and various statistical methods have been developed to address this problem, which is referred to as missing data imputation. In the detection and prediction of incipient faults in power transformers using Dissolved Gas Analysis (DGA), the problem of missing values is influential and has resulted in inconclusive decision-making...
Dissolved Gas Analysis (DGA) is an established method for detecting and predicting faults contained in power transformers. Support Vector Machine (SVM) has been actively applied to classify faults using historic DGA data. However, redundant and irrelevant features can reduce SVM classification performance. Therefore, this study proposes the use of GA-SVM wrapper to eliminate these features and select...
Missing values are a common occurrence in a number of real world databases, and statistical methods have been developed to deal with this problem, referred to as missing data imputation. In the detection and prediction of incipient faults in power transformers using dissolved gas analysis (DGA), the problem of missing values is significant and has resulted in inconclusive decision-making. This study...
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