GitHub / AliAmini93 / Fault-Detection-in-DC-microgrids

Using DIgSILENT, a smart-grid case study was designed for data collection, followed by feature extraction using FFT and DWT. Post-extraction, feature selection. CNN-based and extensive machine learning techniques were then applied for fault detection.

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Topics: anova-analysis, cnn, data-augmentation, digsilent, dwt, feature-selection, fft, grid-search-hyperparameters, linear-discriminant-analysis, mutual-information, neural-network, pearson-correlation, random-forest, svm, xgboost-classifier

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