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https://doi.org/10.2139/ssrn.4182582

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inferredcites →https://doi.org/10.1007/s00500-018-3644-5openalex-extracted
A bearing vibration data analysis based on spectral kurtosis and ConvNet
inferredcites →https://doi.org/10.1016/j.apenergy.2018.09.160openalex-extracted
A novel deep learning method for the classification of power quality disturbances using deep convolutional neural network
inferredcites →https://doi.org/10.1016/j.asoc.2008.03.004openalex-extracted
Non-stationary power signal processing for pattern recognition using HS-transform
inferredcites →https://doi.org/10.1016/j.asoc.2015.05.048openalex-extracted
Power quality disturbance detection and classification using wavelet and RBFNN
inferredcites →https://doi.org/10.1016/j.ins.2020.08.104openalex-extracted
Three-way decision with co-training for partially labeled data
inferredcites →https://doi.org/10.1016/j.measurement.2018.06.059openalex-extracted
Real-time system for automatic detection and classification of single and multiple power quality disturbances
inferredcites →https://doi.org/10.1016/j.neucom.2019.01.038openalex-extracted
A classification method for multiple power quality disturbances using EWT based adaptive filtering and multiclass SVM
inferredcites →https://doi.org/10.1016/j.patcog.2020.107543openalex-extracted
Diverse training dataset generation based on a multi-objective optimization for semi-Supervised classification
inferredcites →https://doi.org/10.1016/j.suscom.2020.100417openalex-extracted
A critical and comprehensive review on power quality disturbance detection and classification
inferredcites →https://doi.org/10.1016/j.ymssp.2016.08.042openalex-extracted
Independence-oriented VMD to identify fault feature for wheel set bearing fault diagnosis of high speed locomotive
inferredcites →https://doi.org/10.1016/j.ymssp.2020.106683openalex-extracted
A deep learning method for bearing fault diagnosis based on Cyclic Spectral Coherence and Convolutional Neural Networks
inferredcites →https://doi.org/10.1049/gtd2.12122openalex-extracted
Categorisation of power quality problems using long short‐term memory networks
inferredcites →https://doi.org/10.1049/iet-gtd.2016.0703openalex-extracted
Method for classification of PQ events based on discrete Gabor transform with FIR window and T2FK‐based SVM and its experimental verification
inferredcites →https://doi.org/10.1049/iet-gtd.2018.0093openalex-extracted
High impedance fault detection method based on the short‐time Fourier transform
inferredcites →https://doi.org/10.1109/access.2019.2937193openalex-extracted
Classification of Power Quality Disturbances Using Wigner-Ville Distribution and Deep Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/tie.2016.2521615openalex-extracted
Disturbance Ratio for Optimal Multi-Event Classification in Power Distribution Networks
inferredcites →https://doi.org/10.1109/tie.2017.2726961openalex-extracted
Fault Detection and Classification Based on Co-training of Semisupervised Machine Learning
inferredcites →https://doi.org/10.1109/tie.2019.2952823openalex-extracted
Classification of Complex Power Quality Disturbances Using Optimized S-Transform and Kernel SVM
inferredcites →https://doi.org/10.1109/tii.2019.2920689openalex-extracted
An Automatic Identification Framework for Complex Power Quality Disturbances Based on Multifusion Convolutional Neural Network
inferredcites →https://doi.org/10.1109/tii.2021.3104008openalex-extracted
PowerCog: A Practical Method for Recognizing Power Quality Disturbances Accurately in a Noisy Environment
inferredcites →https://doi.org/10.1109/tim.2016.2578518openalex-extracted
Detection and Classification of Power Quality Disturbances Using Double Resolution S-Transform and DAG-SVMs
inferredcites →https://doi.org/10.1109/tmc.2019.2892440openalex-extracted
RiskCog: Unobtrusive Real-Time User Authentication on Mobile Devices in the Wild
inferredcites →https://doi.org/10.1109/tsg.2016.2626469openalex-extracted
Variational Mode Decomposition and Decision Tree Based Detection and Classification of Power Quality Disturbances in Grid-Connected Distributed Generation System
inferredcites →https://doi.org/10.1109/tsp.2013.2265222openalex-extracted
Empirical Wavelet Transform
inferredcites →https://doi.org/10.1109/tsp.2013.2288675openalex-extracted
Variational Mode Decomposition
inferredcites →https://doi.org/10.1177/1077546317704793openalex-extracted
Gear fault diagnosis based on time–frequency domain de-noising using the generalized S transform
inferredcites →https://doi.org/10.14722/ndss.2021.24126openalex-extracted
Differential Training: A Generic Framework to Reduce Label Noises for Android Malware Detection
inferredcites →https://doi.org/10.3390/app10196755openalex-extracted
A Comparison of Power Quality Disturbance Detection and Classification Methods Using CNN, LSTM and CNN-LSTM
inferredcites →https://doi.org/10.3390/app9224901openalex-extracted
Power Quality Disturbance Recognition Using VMD-Based Feature Extraction and Heuristic Feature Selection
inferredcites →https://doi.org/10.3390/en13143623openalex-extracted
Detection and Classification of Power Quality Disturbances in Power System Using Modified-Combination between the Stockwell Transform and Decision Tree Methods
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