On the public citation graph

Research on Fault Diagnosis Method of Vehicle Cable Terminal Based On Time Series Segmentation For Graph Neural Network Model

0 signed · 16 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

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

inferredcites →https://doi.org/10.1016/j.apenergy.2023.121547openalex-extracted
Building cooling load forecasting of IES considering spatiotemporal coupling based on hybrid deep learning model
inferredcites →https://doi.org/10.1016/j.epsr.2019.106053openalex-extracted
Feature extraction and ageing state recognition using partial discharges in cables under HVDC
inferredcites →https://doi.org/10.1016/j.ymssp.2021.108653openalex-extracted
The emerging graph neural networks for intelligent fault diagnostics and prognostics: A guideline and a benchmark study
inferredcites →https://doi.org/10.1038/s41558-021-01190-8openalex-extracted
Impact of high-speed rail on road traffic and greenhouse gas emissions
inferredcites →https://doi.org/10.1109/sibgrapi51738.2020.00035openalex-extracted
Superpixel Image Classification with Graph Attention Networks
inferredcites →https://doi.org/10.1109/tii.2020.3034189openalex-extracted
Semisupervised Graph Convolution Deep Belief Network for Fault Diagnosis of Electormechanical System With Limited Labeled Data
inferredcites →https://doi.org/10.1109/tii.2021.3112696openalex-extracted
Graph Cardinality Preserved Attention Network for Fault Diagnosis of Induction Motor Under Varying Speed and Load Condition
inferredcites →https://doi.org/10.1109/tii.2022.3197839openalex-extracted
Partial Discharge Data Augmentation Based on Improved Wasserstein Generative Adversarial Network With Gradient Penalty
inferredcites →https://doi.org/10.1109/tim.2018.2816438openalex-extracted
A New Partial Discharge Signal Denoising Algorithm Based on Adaptive Dual-Tree Complex Wavelet Transform
inferredcites →https://doi.org/10.1109/tim.2020.2996717openalex-extracted
Partial Discharge Signal Denoising Based on Singular Value Decomposition and Empirical Wavelet Transform
inferredcites →https://doi.org/10.1109/tnn.2008.2005605openalex-extracted
The Graph Neural Network Model
inferredcites →https://doi.org/10.17863/cam.48429openalex-extracted
Graph Attention Networks
inferredcites →https://doi.org/10.2139/ssrn.3813628openalex-extracted
Impact of High-Speed Rail on Road Traffic and Greenhouse Gas Emissions
inferredcites →https://doi.org/10.3390/en11051202openalex-extracted
Recurrent Neural Network for Partial Discharge Diagnosis in Gas-Insulated Switchgear
inferredcites →https://doi.org/10.3390/en13205496openalex-extracted
Classification of Partial Discharge Images Using Deep Convolutional Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1904.08082openalex-extracted
Self-Attention Graph Pooling
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.