Fault Line Selection of Distribution Network Based on Modified CEEMDAN and GoogLeNet Neural Network
Author:
Affiliation:
1. School of Control and Computer Engineering, North China Electric Power University, Baoding, China
Funder
National Key Research and Development Program of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/7361/9812846/09791277.pdf?arnumber=9791277
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3. Optimal Denoising and Feature Extraction Methods Using Modified CEEMD Combined with Duffing System and Their Applications in Fault Line Selection of Non-Solid-Earthed Network
4. Pixel matrices: An elementary technique for solving nonlinear systems
5. Fault line detection method based on the improved SVD de‐noising and ideal clustering curve for distribution networks
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