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S-Transform Based FFNN Approach for Distribution Grids Fault Detection and Classification

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

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Neurogenetic modeling of energy demand in the United Arab Emirates, Saudi Arabia, and Qatar
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Rule-based classification of power quality disturbances using S-transform
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Power quality disturbances classification based on S-transform and probabilistic neural network
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Modified S transform and ELM algorithms and their applications in power quality analysis
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A comprehensive overview on signal processing and artificial intelligence techniques applications in classification of power quality disturbances
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Pattern analysis with two-dimensional spectral localisation: Applications of two-dimensional S transforms
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Sparse S‐transform for location of faults on transmission lines operating with unified power flow controller
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Wavelet‐based extreme learning machine for distribution grid fault location
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Localization of the complex spectrum: the S transform
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Research on Distribution Network Fault Recognition Method Based on Time-Frequency Characteristics of Fault Waveforms
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Distribution System Fault Diagnosis Scheme Based on Multiple Information Sources
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Optimized support vector machine & wavelet transform for distribution grid fault location
inferredcites →https://doi.org/10.1109/iaeac.2015.7428636openalex-snapshot
A cost-effective approach for feeder fault detection and location of radial distribution networks
inferredcites →https://doi.org/10.1109/iceceng.2011.6057020openalex-snapshot
Earth fault detection in distribution network based on wide-area measurement information
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Fault Detection Algorithm for Power Distribution Network Based on Sparse Self-Encoding Neural Network
inferredcites →https://doi.org/10.1109/indcon.2008.4768772openalex-snapshot
A wavelet based approach for classification and location of faults in distribution systems
inferredcites →https://doi.org/10.1109/iraniancee.2013.6599760openalex-snapshot
Detection and classification of high impedance faults in power distribution networks using ART neural networks
inferredcites →https://doi.org/10.1109/isap.2015.7325522openalex-snapshot
Classification of power quality disturbances using Wavelet Transform and Optimized ANN
inferredcites →https://doi.org/10.1109/isap.2017.8071380openalex-snapshot
An effective feature extraction method in pattern recognition based high impedance fault detection
inferredcites →https://doi.org/10.1109/isgt-la.2017.8126699openalex-snapshot
Evaluation of the impact of different neural network structure and data input on fault detection
inferredcites →https://doi.org/10.1109/powerafrica.2012.6498611openalex-snapshot
Fault detection and classification in a distribution network integrated with distributed generators
inferredcites →https://doi.org/10.1109/ptc.2017.7981089openalex-snapshot
Detection of fault using local measurements at inverter interfaced distributed energy resources
inferredcites →https://doi.org/10.1109/ssp.2014.6884569openalex-snapshot
Feeder-level fault detection and classification with multiple sensors: A smart grid scenario
inferredcites →https://doi.org/10.1109/tencon.2016.7848519openalex-snapshot
Selection of proper input pattern in fuzzy logic algorithm for classifying the fault type in underground distribution system
inferredcites →https://doi.org/10.1109/tii.2012.2187914openalex-snapshot
Selection of Proper Neural Network Sizes and Architectures—A Comparative Study
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Detection and Classification of Power Quality Disturbances Using S-Transform and Probabilistic Neural Network
inferredcites →https://doi.org/10.1109/tpwrd.2010.2046682openalex-snapshot
Fault Analysis of Multiphase Distribution Systems Using Symmetrical Components
inferredcites →https://doi.org/10.1109/tpwrs.2017.2765311openalex-snapshot
Dynamic Voltage Support by TL-PV Systems to Mitigate Short-Term Voltage Instability in Residential DN
inferredcites →https://doi.org/10.1186/1687-6180-2012-49openalex-snapshot
Evaluation of the modified S-transform for time-frequency synchrony analysis and source localisation
inferredcites →https://doi.org/10.9790/1676-0232631openalex-snapshot
Wavelet Entropy and Neural Network Based Fault Detection on A Non Radial Power System Network

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Intelligent fault diagnosis technique for distribution grid
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Smart grid fault diagnosis under load and renewable energy uncertainty
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Artificial intelligence techniques
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Appendices
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Introduction
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Travel-To-School Mode Choice Modelling Employing Artificial Intelligence Techniques: A Comparative Study
inferred← citeshttps://doi.org/10.46253/jcmps.v2i2.a1openalex-snapshot
Fault Recognition and Diagnosis Based on a Decision Tree for Power Distribution Systems
inferred← citeshttps://doi.org/10.48175/ijarsct-9106openalex-snapshot
Exploring the Dark Side of IoT: A Survey on Blackhole Attacks
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