Partial Discharge Diagnosis in GIS based on Pulse Sequence Features and Optimized Machine Learning Classification Techniques

Research article (Electric Power Systems Research, 2022) · cited 19× · AI/ML
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Partial Discharge Diagnosis in GIS based on Pulse Sequence Features and Optimized Machine Learning Classification Techniques

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Partial Discharge Diagnosis in GIS based on Pulse Sequence Features and Optimized Machine Learning Classification Techniques is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Partial Discharge Diagnosis in GIS based on Pulse Sequence Features and Optimized Machine Learning Classification Techniques. Retrieved May 24, 2026, from https://4ort.xyz/entity/partial-discharge-diagnosis-in-gis-based-on-pulse-sequence-features-and-optimized-machine-learning-classification-techni
MLA “Partial Discharge Diagnosis in GIS based on Pulse Sequence Features and Optimized Machine Learning Classification Techniques.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/partial-discharge-diagnosis-in-gis-based-on-pulse-sequence-features-and-optimized-machine-learning-classification-techni.
BibTeX @misc{4ortxyz_partial-discharge-diagnosis-in-gis-based-on-pulse-sequence-features-and-optimized-machine-learning-classification-techni_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Partial Discharge Diagnosis in GIS based on Pulse Sequence Features and Optimized Machine Learning Classification Techniques}}, year = {2026}, url = {https://4ort.xyz/entity/partial-discharge-diagnosis-in-gis-based-on-pulse-sequence-features-and-optimized-machine-learning-classification-techni}, note = {Accessed: 2026-05-24}}
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