IGBT Module DPT Efficiency Enhancement via Multimodal Fusion Networks and Graph Convolution Networks

Zhang, Xiaotian, Hu, Yihua, Zhang, Jingwei et al. (3 more authors) (2024) IGBT Module DPT Efficiency Enhancement via Multimodal Fusion Networks and Graph Convolution Networks. IEEE Transactions on Industrial Electronics. pp. 1-12. ISSN 0278-0046

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Item Type: Article
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This is an author-produced version of the published paper. Uploaded in accordance with the University’s Research Publications and Open Access policy.

Keywords: Behavioral sciences,Double pulse test (DPT),Employee welfare,Estimation,feature fusion,graph convolutional network (GCN),Insulated gate bipolar transistors,insulated-gate bipolar transistor (IGBT),Integrated circuit modeling,Switches,Transient analysis
Dates:
  • Published (online): 7 March 2024
  • Accepted: 13 February 2024
Institution: The University of York
Academic Units: The University of York > Faculty of Sciences (York) > Electronic Engineering (York)
Depositing User: Pure (York)
Date Deposited: 30 Jul 2024 16:20
Last Modified: 07 Nov 2024 01:49
Published Version: https://doi.org/10.1109/TIE.2024.3368165
Status: Published online
Refereed: Yes
Identification Number: 10.1109/TIE.2024.3368165
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Filename: IGBT_Module_DPT_Efficiency_Enhancement_Via_Multimodal_Fusion_Networks_and_Graph_Convolution_Networks.pdf

Description: IGBT Module DPT Efficiency Enhancement Via Multimodal Fusion Networks and Graph Convolution Networks

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