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Detection and Classification of Multiple Power Quality Disturbances based on Temporal Deep Learning

https://doi.org/10.1109/eeeic.2019.8783378

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Deep learning based ensemble approach for probabilistic wind power forecasting

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A novel deep learning method for the classification of power quality disturbances using deep convolutional neural network

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Fuzzy classifiers for power quality events analysis

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Power quality disturbances classification based on S-transform and probabilistic neural network

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Probabilistic deep neural network price forecasting based on residential load and wind speed predictions

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An Independent Component Analysis Classification for Complex Power Quality Disturbances With Sparse Auto Encoder Features

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Integral mathematical model of power quality disturbances

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Real-Time Motor Fault Detection by 1-D Convolutional Neural Networks

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Novel Method Based on Variational Mode Decomposition and a Random Discriminative Projection Extreme Learning Machine for Multiple Power Quality Disturbance Recognition

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A Sequence-to-Sequence Deep Learning Architecture Based on Bidirectional GRU for Type Recognition and Time Location of Combined Power Quality Disturbance

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Automated Classification of Power-Quality Disturbances Using SVM and RBF Networks

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Recurrent Convolutional Neural Networks for Text Classification

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What points at this work

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Classification of multiple power quality disturbances based on continuous wavelet transform and lightweight convolutional neural network

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Enhancing adversarial robustness in power quality classification systems: an attention-based defense framework

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A Deep Learning Approach for the Detection and Classification of Power Quality Disturbances with Windowed Signals

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Designing a composite deep learning based differential protection scheme of power transformers

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Type identification and time location of multiple power quality disturbances based on KF‐ML‐aided DBN

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Deep learning architecture for direct probability density prediction of small‐scale solar generation

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Amplitude and phase estimations of power system harmonics using deep learning framework

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Fault localisation and diagnosis in transmission networks based on robust deep Gabor convolutional neural network and PMU measurements

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Power Quality Disturbances Classification Using A TCN-CNN Model

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Algoritmos de Detección y Clasificación de Eventos de Calidad de Energía en el Dominio Temporal [Not available in English]

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Detection and Classification of Power Quality Disturbances Using Variational Mode Decomposition and Convolutional Neural Networks

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Deep Learning Based Power Quality Disturbance Recognition using Residual Network in Smart Grid

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Power Quality Disturbances Classification Analysis Using EfficientNet Architecture

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Electric Power Quality Disturbances Classification based on Temporal-Spectral Images and Deep Convolutional Neural Networks

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Fault Location and Faulty Line Selection in Transmission Networks: Application of Improved Gated Recurrent Unit

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Hyperparameter Analysis-Based Long-Short Term Memory (LSTM) for Power Quality Disturbances Classification

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Power Quality Disturbances and Detection Methods: A Brief Review

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Deep Convolutional Neural Network for Multiple Smart Grid Event Classification through Sliding Windows

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Advanced Deep Learning Approach for Probabilistic Wind Speed Forecasting

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Detection and Classification of Multiple Power Quality Disturbances Using Stockwell Transform and Deep Learning

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A Generalized Classification Framework for Power Quality Disturbances Based on Synchrosqueezed Wavelet Transform and Convolutional Neural Networks

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“The Rise of Tech and the Question of Power” A Review on Detection and Classification of Multiple Power Quality Disturbances

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Composite load modeling by spatial-temporal deep attention network based on wide-area monitoring systems

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On the Long-Period Accuracy Behavior of Inductive and Low-Power Instrument Transformers

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