Feature extraction and power quality event classification using Curvelet transform and optimized extreme learning machine
Summary
Feature extraction and power quality event classification using Curvelet transform and optimized extreme learning machine is a scholarly article[1].
Key Facts
Feature extraction and power quality event classification using Curvelet transform and optimized extreme learning machine's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Feature extraction and power quality event classification using Curvelet transform and optimized extreme learning machine. Retrieved May 24, 2026, from https://4ort.xyz/entity/feature-extraction-and-power-quality-event-classification-using-curvelet-transform-and-optimized-extreme-learning-machin
MLA“Feature extraction and power quality event classification using Curvelet transform and optimized extreme learning machine.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/feature-extraction-and-power-quality-event-classification-using-curvelet-transform-and-optimized-extreme-learning-machin.
BibTeX@misc{4ortxyz_feature-extraction-and-power-quality-event-classification-using-curvelet-transform-and-optimized-extreme-learning-machin_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Feature extraction and power quality event classification using Curvelet transform and optimized extreme learning machine}}, year = {2026}, url = {https://4ort.xyz/entity/feature-extraction-and-power-quality-event-classification-using-curvelet-transform-and-optimized-extreme-learning-machin}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Feature extraction and power quality event classification using Curvelet transform and optimized extreme learning machine — https://4ort.xyz/entity/feature-extraction-and-power-quality-event-classification-using-curvelet-transform-and-optimized-extreme-learning-machin (retrieved 2026-05-24)